Computational
BiologyComputer
EngineeringGraphics and
User InterfacesMachine Learning Networking NLP and Speech Security and Privacy Software Systems Theory Vision and Robotics
- Faculty
Dana
Pe'er
Itsik
Pe'er
Kenneth
Ross
Yechiam
Yemini
Computational biology and bioinformatics involve development and application of analysis methods for high throughput experimental data in molecular biology to facilitate biomedical research. Active topics of investigation in Columbia involve systems biology, biological networks, massively parallel ("next generation") DNA sequencing, RNA sequencing, ChIP sequencing, analysis of transcription factor binding sites, single nucleotide polymorphisms, population genetics, molecular evolution, personalized medicine, tumor genomics.
- COMS W4761 Computational Genomics
- COMS E6998 Computational Human Genetics
- COMS E6998 Seminar on Biological Networks
- COMS E6998 Seminar in Evolutionary and Comparative Genomics
- COMS E6998 Biological Networks
Dana Pe'er is assistant professor in the biological sciences department at Columbia University in New York.
Pe'er earned her bachelor's degree in mathematics in 1995, her master's degree in 1999 and her doctorate in machine learning and computational biology in 2003, all from Hebrew University in Jerusalem. She conducted postdoctoral work in systems biology at Harvard Medical School.
Pe'er's research is focused on elucidating tumor-specific molecular networks, working towards personalized cancer care. Her lab focuses on the integration and analysis of high-throughput data toward understanding how molecular networks process signals. Pe'er pioneered the use of Bayesian networks for analysis of molecular networks and has demonstrated the success of this approach in a broad number of applications spanning diverse types of biological data.
Computational biology, genomics, medical and population genetics, isolated and admixed populations, analysis of heritable variation in cancer
Itsik Pe'er is an associate professor in the Department of Computer Science and the Center for Computational Biology and Bioinformatics at Columbia University. Dr. Pe'er's research involves developing computational methods for analysis of human genetic variation as part of the Genetic Analysis Information Network and the Cancer Genome Atlas projects. Previously, Dr. Pe'er participated in the International HapMap project during his postdoctoral research at Massachusetts General Hospital and the Broad Institute of Harvard and MIT. He holds B.Sc., M.Sc. and Ph.D. degrees in computer science from Tel Aviv University, where he developed computational solutions to problems in genome sequencing and evolution.
Discovering Origins of Diabetes [PDF]
Databases, query optimization, declarative languages for database systems, logic programming, architecture-sensitive software design
Kenneth Ross is a Professor in the Computer Science Department at Columbia University in New York City. His research interests touch on various aspects of database systems, including query processing, query language design, data warehousing, and architecture-sensitive database system design. He also has an interest in computational biology, including the analysis of large genomic data sets. Professor Ross received his PhD from Stanford University. He has received several awards, including a Packard Foundation Fellowship, a Sloan Foundation Fellowship, and an NSF Young Investigator award.
Processing Parallel Insights [PDF]
Yechiam Yemini (YY) is a Professor of computer science at Columbia University. His current research interests include computational biology and biological networks (for his previous networking research and the DCC lab visit http://www.cs.columbia.edu/dcc). He is currently teaching the Computational Genomics class W4761 (visit www.cs.columbia.edu/4761 for extensive course notes).
Professor Yemini has also been a co-founder of Comverse Technology (1983), http://www.comverse.com, System Management Arts (SMARTS) (1993) http://www.smarts.com , acquired by EMC in 2005, and Arootz (2006), http://www.arootz.com. He has served as a director and advisory board member of several high-tech companies and as a member of several government technology commissions and working groups; :-) his spare time is devoted to eclectic activities ranging from gourmet cooking to sand sculpturing (see http://www.cs.columbia.edu/~yemini/charleston ).
Turning Students into Entrepreneurs [PDF]
Computer engineering research includes computer architecture; VLSI design; hardware security; power- and energy-efficient architectures; interconnection networks; support for emerging technologies and applications; design and optimization of asynchronous and mixed-timing digital circuits and systems; computer-aided design (CAD) tools including system-level design, communication synthesis and logic synthesis; embedded software and distributed embedded systems; and domain-specific language design and compilation.
- COMS W4115 Programming languages and translators
- COMS W4118 Operating systems, I
- COMS W4995 Principles and practice of parallel programming
- COMS W6998 Formal verification of hardware/software systems
- EECS E4340 Computer Hardware Design
- CSEE W4119 Computer networks
- CSEE E6824 Parallel Computer Architecture
- CSEE W4824 Computer Architecture
- CSEE W4823 Advanced Logic Design
- CSEE W3827 Fundamentals of Computer Systems
- CSEE E6847 Distributed Embedded Systems
- CSEE W4840 Embedded Systems Design
- CSEE E6861 Computer-Aided Design of Digital Systems
Computer-aided design, embedded systems, multi-core platform architectures, cyber-physical systems
Luca Carloni is an Associate Professor of Computer Science at Columbia University in the City of New York. He holds a Laurea Degree Summa cum Laude in Electronics Engineering from the University of Bologna, Italy, a Master of Science in Engineering from the University of California at Berkeley, and a Ph.D. in Electrical Engineering and Computer Sciences from the University of California at Berkeley.
At Berkeley Luca was the 2002 recipient of the Demetri Angelakos Memorial Achievement Award in recognition of altruistic attitude towards fellow graduate students. Luca received the Faculty Early Career Development (CAREER) Award from the National Science Foundation in 2006, was selected as an Alfred P. Sloan Research Fellow in 2008, and received the ONR Young Investigator Award in 2010.
His research interests include methodologies and tools for multi-core system-on-chip platforms with emphasis on system-level design and communication synthesis, design and optimization of networks-on-chip, embedded software and distributed embedded systems. Luca coauthored over seventy refereed papers and is the holder of one patent.
Luca is an associate editor of the ACM Transactions in Embedded Computing Systems, the IEEE Transactions on Industrial Informatics, and the Elsevier Journal of Sustainable Computing. He has served in the technical program committee of several conferences including DAC, DATE, ICCAD, and EMSOFT. He has been the tutorial chair of the Embedded Systems Week and the program co-chair of the International Conference on Embedded Software (EMSOFT), the International Symposium on Networks-on-Chip (NOCS), and the International Conference on Formal Methods and Models for Codesign (MEMOCODE).
Luca participates in the Gigascale Systems Research Center (GSRC).
Networking Chips [PDF]
Embedded systems, domain-specific languages, compilers, hardware-software codesign, computer-aided design
Stephen A. Edwards is a tenured associate professor in the Computer Science Department of Columbia University. He obtained his Ph.D from the University of California, Berkeley in 1997, his MS from Berkeley in 1994, and his BS from the California Institute of Technology in 1992, all in Electrical Engineering. Before pursuing his academic career in 2001, he worked for two Electronic Design Automation (EDA) companies, Simplex Solutions, now part of Cadence, and Synopsys.
Professor Edwards and his group explore automating the creation of software for embedded systems: application-specific computers hiding in a growing number of industrial and consumer systems. They have developed numerous compilation techniques for the Esterel synchronous language for real-time control and are also developing domain-specific languages for device drivers and communication protocols.
Testing and Correcting Embedded Processors [PDF]
Computer architecture, hardware systems, hardware/software interaction, parallel hardware and software systems
Martha A. Kim is an Assistant Professor of Computer Science at Columbia University. She joined Columbia after receiving her PhD in Computer Science and Engineering from the University of Washington in December 2008. She holds a bachelors in Computer Science from Harvard University, and and a Masters in embedded systems design from the University of Lugano in Switzerland. Martha's research focus is in computer architecture. Her research has explored application mapping algorithms for the WaveScalar compiler, low-cost chip manufacturing, and reconfigurable network design. Her current focus is on techniques to improve the programmability and usability of hardware accelerators, and methods for explicit expression of on-chip communication.
Accelerating Processing's Family Van [PDF]
Asynchronous and mixed-timing digital circuits and systems, computer-aided design, networks-on-chip, interconnection networks for parallel processors, low-power digital design
Steven M. Nowick is a Professor of Computer Science and Electrical Engineering at Columbia University, and Chair of the Computer Engineering Program. He received a Ph.D. in Computer Science from Stanford University in 1993, and a B.A. from Yale University. Dr. Nowick's main research focus is on asynchronous and mixed-timing (i.e. handling multiple clock domains) digital system design, with a focus on low-power and high-performance. His group has developed novel circuit structures for these designs, as well as automated CAD (computer-aided design) tools and algorithms for their synthesis, analysis and optimization. His recent research projects include: high-performance and low-power GALS (globally-asynchronous locally-synchronous) interconnection networks for shared-memory parallel processors; low-power and fault-tolerant robust bus encoding; and ultra-low-energy DSP's.
Dr. Nowick is an IEEE Fellow (2009), and a recipient of an NSF CAREER Award (1995), an Alfred P. Sloan Research Fellowship (1995) and an NSF Research Initiation Award (RIA) (1993). He received Best Paper Awards at the 1991 International Conference on Computer Design (ICCD) and the 2000 IEEE Async Symposium. He received 2 medium-scale NSF ITR awards in 2000 for asynchronous research, as well as medium-scale NSF awards in 2008 and 2010 (for high-performance asynchronous interconnection networks, and for asynchronous digital design for continuous-time DSP's). In 2005 was brought onto the DARPA "CLASS" project, headed by Boeing, to create a new commercially-viable CAD tool flow for designing asynchronous systems. He was a co-founder of the IEEE "Async" Symposia series, serving as Program Committee Co-Chair (1994, 1999) and General Co-Chair (2005). He has been Program Chair of the 2002 IEEE/ACM International Workshop on Logic and Synthesis (IWLS), and track and topic area chairs at DAC, DATE and ICCD. He is currently an associate editor of IEEE Transactions on Computer-Aided Design and ACM Journal on Emerging Technologies in Computer Systems, and formerly associate editor of IEEE Transactions on VLSI Systems. He holds 10 issued US patents.
Marching Without a Beat [PDF]
Computer architecture, hardware security
Prof. Simha Sethumadhavan is an assistant professor of computer science at Columbia University in New York. At Columbia, he directs the computer architecture and security technologies lab (CASTL). Research at CASTL is targeted at solving two important problems that threaten to stall computing advances: energy-inefficiency and the lack of security and erosion of privacy in computing systems. Prof. Sethumadhavan obtained his PhD from UTAustin in 2007.
Designing Secure Hardware [PDF]
Graphics and user interface research includes animation, geometry processing, computational photography, augmented reality & virtual environments, rendering, human-computer interaction, acquisition of geometry and material properties, 3D user interfaces, computational mechanics, knowledge-based design of graphics and multimedia, mobile and wearable computing, computer games, information visualization, video and image processing, shape modeling.
- COMS W4160 Computer Graphics
- COMS W4162 Advanced Computer Graphics
- COMS W4165 Computational Techniques in Pixel Processing
- COMS W4167 Computer Animation
- COMS W4170 User Interface Design
- COMS W4172 3D User Interfaces and Augmented Reality
- COMS W4735 Visual Interfaces to Computers
- COMS W4995 Discrete Differential Geometry
- COMS E6734 Computational Photography
Computer vision, biometrics, face recognition, computational photography, computer graphics, biological species identification
Peter N. Belhumeur is currently a Professor in the Department of Computer Science at Columbia University and the Director of the Laboratory for the Study of Visual Appearance (VAP LAB). He received a Sc.B. in Information Sciences from Brown University in 1985. He received his Ph.D. in Engineering Sciences from Harvard University under the direction of David Mumford in 1993. He was a postdoctoral fellow at the University of Cambridge's Isaac Newton Institute for Mathematical Sciences in 1994. He was made Assistant, Associate and Professor of Electrical Engineering at Yale University in 1994, 1998, and 2001, respectively. He joined Columbia University as a Professor of Computer Science in 2002. His research focus lies somewhere in the mix of computer vision, computer graphics, and computational photography. He is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) and the National Science Foundation Career Award. He won both the Siemens Best Paper Award at the IEEE Conference on Computer Vision and Pattern Recognition and the Olympus Prize at the European Conference of Computer Vision.
Turning a New Leaf on Face Recognition [PDF]
Human-computer interaction, augmented reality and virtual environments, 3D user interfaces, knowledge-based design of graphics and multimedia, mobile and wearable computing, computer games, information visualization
Steven K. Feiner (PhD, Brown) is Professor of Computer Science at Columbia University, where he directs the Computer Graphics and User Interfaces Lab. His research interests include human-computer interaction, augmented reality and virtual environments, 3D user interfaces, knowledge-based design of graphics and multimedia, mobile and wearable computing, computer games, and information visualization.
Prof. Feiner is coauthor of Computer Graphics: Principles and Practice and of Introduction to Computer Graphics (Addison-Wesley), received an ONR Young Investigator Award, and was elected to the CHI Academy. Together with his students, he has won the ACM UIST 2010 Lasting Impact Award and best paper awards at ACM UIST, ACM CHI, ACM VRST, and IEEE ISMAR. His lab created the first outdoor mobile augmented reality system using a see-through display in 1996, and pioneered experimental applications of augmented reality to fields such as tourism, journalism, maintenance, and construction. In recent years, Prof. Feiner has been program co-chair for IEEE Virtual Reality 2012; general chair or co-chair for ACM VRST 2008 (15th Symposium on Virtual Reality Software and Technology), INTETAIN 2008 (Second International Conference on Intelligent Technologies for Interactive Entertainment), and ACM UIST 2004 (17th Symposium on User Interface Software and Technology); and doctoral symposium chair for ACM UIST 2009-2011.
Augmenting Reality [PDF]
Computer graphics, scientific computing: computational mechanics, mathematical foundations of graphics, discrete differential geometry
Eitan Grinspun is Associate Professor of Computer Science at Columbia University in the City of New York. He was Professeur d'Universite Invite at l'Universite Pierre et Marie Curie in 2009, a Research Scientist at the Courant Institute of Mathematical Sciences from 2003-2004, and a graduate student at the California Institute of Technology from 1997-2003. He was an NVIDIA Fellow in 2001, an Everhart Distinguished Lecturer in 2003, an NSF CAREER Award recipient in 2007, and is currently an Alfred P. Sloan Research Fellow.
Predicting the Motion of Materials [PDF]
Computer vision, computational imaging, computer graphics, robotics, human-computer interfaces
Shree K. Nayar received his PhD degree in Electrical and Computer Engineering from the Robotics Institute at Carnegie Mellon University in 1990. He is currently the T. C. Chang Professor of Computer Science at Columbia University. He co-directs the Columbia Vision and Graphics Center. He also heads the Columbia Computer Vision Laboratory (CAVE), which is dedicated to the development of advanced computer vision systems. His research is focused on three areas; the creation of novel cameras, the design of physics based models for vision, and the development of algorithms for scene understanding. His work is motivated by applications in the fields of digital imaging, computer graphics, and robotics.
He has received best paper awards at ICCV 1990, ICPR 1994, CVPR 1994, ICCV 1995, CVPR 2000 and CVPR 2004. He is the recipient of the David Marr Prize (1990 and 1995), the David and Lucile Packard Fellowship (1992), the National Young Investigator Award (1993), the NTT Distinguished Scientific Achievement Award (1994), the Keck Foundation Award for Excellence in Teaching (1995), the Columbia Great Teacher Award (2006) and Carnegie Mellon University's Alumni Achievement Award. In February 2008, he was elected to the National Academy of Engineering.
Picturing the World in New Ways [PDF]
Computer graphics, physically-based multi-sensory animation, computational acoustics, scientific computing, robotics
Changxi Zheng is an assistant professor of Computer Science at Columbia University. His research spans physically-based animation, computational acoustics, scientific computing and robotics, with a focus on developing practical computational methods to produce realistic dynamics and multi-modal sensations.
Changxi received his PhD in 2012 from Cornell University, where he developed a variety of physically based sound synthesis methods for computer animation. His work has been featured in various press coverage (NPR, BBC, Science Daily, New Scientist, etc.).
Machine learning uses computational, theoretical, and statistical principles to develop algorithms that model data from real-world phenomena and make accurate predictions about the phenomena. Machine learning operates in supervised, unsupervised and semi-supervised settings to perform classification, regression, visualization, clustering, dimensionality reduction, network modeling, graphical modeling, inference and structured prediction.
- COMS W4701 Artificial intelligence
- COMS W4252 Introduction to Computational Learning Theory
- COMS W4771 Machine Learning
- COMS W4772 Advanced Machine Learning
- COMS E6253 Advanced Topics in Computational Learning Theory
Machine learning, statistical pattern recognition, data mining, computer science education, algorithms
Adam Cannon is a lecturer and associate chair for undergraduate education in the Department of Computer Science at Columbia University. He received his Ph.D. in Applied Mathematics from the Department of Mathematical Sciences at The Johns Hopkins University in 2000. His research interests are in machine learning, statistical pattern recognition, data mining, computer science education, and algorithms. He is a SEAS Alumni Association Distinguished Faculty Teaching Award recipient.
Chang is an active researcher leading development of novel theories, algorithms, and systems for content-based image video search, visual communication, multimedia analytics, as well as media forensics. His work has been influential in shaping the vibrant fields of content-based multimedia retrieval. In the 90's, he and his students developed several of the first image/video search engines, such as VisualSEEk, VideoQ, and WebSEEk. He has also been recognized for inventing innovative communication systems that combine content analytics, adaptive mobile streaming, and summarization. Other significant contributions include large-scale concept-based video search engines (e.g., CuZero), a widely used library of image classification models (e.g., Columbia374), international multimedia indexing/communication standards (e.g., MPEG-7 and MPEG-21), and large multimedia ontologies (e.g., LSCOM). In addition, Chang has led cross-disciplinary projects, including a DAVIC Video on Demand international interoperability test, a video library under Columbia's Health Care Digital Library, and the ADVENT university-industry research consortium with the participation of more than 25 industry sponsors. Many video indexing technologies developed by his group have been licensed to companies. He has received the IEEE Kiyo Tomiyasu technical field award, IBM Faculty Award, NSF CAREER Award, and ONR Young Investigator Award. He and his students have won many best paper awards and best student paper awards from IEEE, ACM, and SPIE. He served as the Editor-in-Chief of the IEEE Signal Processing Magazine (2006-8), Chair of Columbia Electrical Engineering Department (2007-2010), general co-chair of ACM Multimedia Conference in 2000 and 2010, and advisor for several media technology companies and research institutions. His research has been broadly supported by government agencies as well as industry sponsors. He is an IEEE Fellow and a Fellow of the American Association for the Advancement of Science.
Developing Next-Generation Visual Search Engines [PDF]
Natural language processing and machine learning
My research interests are in natural language processing, and machine learning. I completed a PhD in computer science from the University of Pennsylvania in December 1998. From January 1999 to November 2002 I was a researcher at AT&T Labs-Research, and from January 2003 until December 2010 I was an assistant/associate professor at MIT. I joined Columbia University in January 2011.
Machine learning, social networks, graphs, vision, and spatio-temporal modeling
Tony Jebara is Associate Professor of Computer Science at Columbia University and co-founder of Sense Networks. He directs the Columbia Machine Learning Laboratory whose research intersects computer science and statistics to develop new frameworks for learning from data with applications in vision, networks, spatio-temporal data, and text. Jebara has published over 75 peer-reviewed papers in conferences and journals including NIPS, ICML, UAI, COLT, JMLR, CVPR, ICCV, and AISTAT. He is the author of the book Machine Learning: Discriminative and Generative and co-inventor on multiple patents in vision, learning and spatio-temporal modeling. In 2004, Jebara was the recipient of the Career award from the National Science Foundation. His work was recognized with a best paper award at the 26th International Conference on Machine Learning, a best student paper award at the 20th International Conference on Machine Learning as well as an outstanding contribution award from the Pattern Recognition Society in 2001. Jebara's research has been featured on television (ABC, BBC, New York One, TechTV, etc.) as well as in the popular press (New York Times, Slash Dot, Wired, Businessweek, IEEE Spectrum, etc.). He obtained his PhD in 2002 from MIT. Esquire magazine named him one of their Best and Brightest of 2008.
Tony serves as Associate Editor for the Journal of Machine Learning Research and Associate Editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence. He is currently on the steering committee of the NYAS Machine Learning Symposium.
Finding Patterns in a Complex World [PDF]
Computational learning theory, computational complexity theory, randomness in comutation, combinatorics cryptography
I am an associate professor in the Computer Science Department of Columbia University, where I do research in theoretical computer science. My main research area is computational learning theory, but I also have strong interests in computational complexity theory, combinatorics, randomized algorithms, cryptography, and quantum computation.
Playing '20 Questions' with Geometry [PDF]
Vladimir Vapnik is an Adjunct Professor at Columbia University. Prof. Vapnik served as Head of the Computer Science Research Department of Institute of Control Sciences, Moscow from 1961 to 1990. He was a Professor of Computer Science and Statistics at Royal Holloway, University of London since 1995. At the end of 1990, he moved to the USA and joined the Adaptive Systems Research Department at Bell Labs. He left Bell Labs in 2002 and joined NEC Laboratories. America, Inc., where he currently works in the Machine Learning group. Prof. Vapnik has taught and researched in computer science, theoretical and applied statistics for over 30 years. He has published seven books and over a hundred research papers. His major achievements have been the development of a general theory for minimizing the expected risk of losses using empirical data, and a new type of learning machine called Support Vector machine that possesses a high level of generalization ability. These techniques have been used to solve many pattern recognition and regression estimation problems and have been applied to the problems of dependency estimation, forecasting, and constructing intelligent machines. Prof. Vapnik has been a Member of Scientific Advisory Board of Health Discovery Corp. since July 2004. He serves as a Member of Scientific Advisory Board at Rules-Based Medicine, Inc. He serves as a Member of the Scientific Board of KXEN, Inc. (also known as Knowledge Extraction Engines). He is the 2003 winner of the Humboldt Research Award. Prof. Vapnik, one of the fathers of Statistical Learning Theory. He received his Masters Degree in Mathematics in 1958 at Uzbek State University, Samarkand, USSR. He received his Ph.D. in statistics at the Institute of Control Sciences, Moscow in 1964.
Unlocking a Complex World Mathematically [PDF]
David L. Waltz has been Director of the Center for Computational Learning Systems (CCLS) at Columbia University since 2003. He was formerly President of the NEC Research Institute in Princeton, and from 1984-1993 was Director of Advanced Information Systems at Thinking Machines Corporation and Professor of Computer Science at Brandeis University. He had also been Professor of Electrical and Computer Engineering at the University of Illinois (CSL and ECE Department) for 11 years. Waltz served as president of AAAI (American Association for Artificial Intelligence) from 1997-1999, and is a Fellow of AAAI and ACM (Association for Computing Machinery), a Senior Member of IEEE (Institute for Electrical and Electronics Engineers), and former Chairman of ACM SIGART (Special Interest Group on Artificial Intelligence). He is currently on the Army Research Lab Technical Advisory Board and the Advisory Board of the Florida Institute for Human and Machine Cognition, the Technical Advisory Board of 4C (Cork Constraint Computation Center, Ireland) and has served on recent external advisory boards for Rutgers University, Carnegie-Mellon University, Brown University, and EPFL (Ecole Polytechnique Federale de Lausanne). He is on the Advisory Board for IEEE Intelligent Systems, and the Computing Community Consortium Board of the CRA (Computing Research Association), and NSF Computer Science Advisory Board.
Dr. Waltz received all his degrees from MIT, including his Ph.D. for work at the MIT AI Lab. His thesis on computer vision originated the field of constraint propagation, and with Craig Stanfill, he originated the field of memory-based reasoning branch of CBR (Case-Based Reasoning). His current primary research interest is in machine learning applications, especially to the electric power grid. His research interests have also included massively parallel information retrieval, data mining, learning and automatic classification with applications protein structure prediction, and natural language processing.
- COMS W4119 Computer Networks
- COMS W4180 Intro to Network Security
- COMS W4261 Intro to Cryptography
- COMS W4995 Intro to Semantic Web
- COMS E6998 Advanced Topic in Machine Learning
Networked Algorithms, Social Networks, Mobile Computing, Stochastic Networks
Augustin Chaintreau is an Assistant Professor of Computer Science at Columbia University. His research, by experience in industry, is centered on real world impact and emerging computing trends, while his training, in mathematics and theoretical computer science, is focused on guiding principles. He designed and proved the first reliable, scalable and network-fair multicast architecture while working at IBM during his Ph.D. He conducted the first measurement experience of human mobility as a communication transport tool while working for Intel and, as member of the Technical Staff of Technicolor (formerly, Thomson), showed that opportunistic caching in mobile networks can optimally take advantage of social properties. He is now working on internetworking social network services through distributed algorithms and opportunistic architecture, to vastly expand how your data and the web deal with everyday objects and your social environment.
An ex student of the Ecole Normale Superieure in Paris, he earned a Ph.D in mathematics and computer science in 2006. He has been an active member of the networking research community, serving in the program commitee of ACM SIGCOMM, ACM CoNEXT, ACM SIGMETRICS, ACM MobiCom, ACM MobiHoc, ACM IMC, IEEE Infocom. He is also an editor for IEEE TMC, ACM SIGCOMM CCR, ACM SIGMOBILE MC2R.
Networking, modeling and performance evaluation,internet economics
Vishal Misra is an Associate Professor and Vice Chair of the Department. He received his B Tech from IIT Bombay (1992), and an MS and PhD from University of Massachusetts at Amherst (2000). He has received an NSF CAREER Award, a DoE CAREER Award and Google and IBM Faculty Awards. His research emphasis is on mathematical modeling of networking systems, bridging the gap between practice and analysis. His recent work includes the areas of Internet economics, wireless, scheduling mechanisms and peer to peer systems. He has served as the guest editor for the Journal of Performance Evaluation, was TPC co-chair of Sigmetrics 2008, General Chair in 2010 and serves on the editorial board of IEEE/ACM Transactions on Networking and Elsevier Journal of Performance Evaluation.
Boosting Profits with Peer-to-Peer Networks [PDF]
Computer networks, network robustness and security, multimedia networking, performance evaluation, algorithms, low-power networking
Dan Rubenstein is an Associate Professor in the Department of Computer Science at Columbia University. He received a B.S. degree in mathematics from M.I.T., an M.A. in math from UCLA, and a PhD in computer science from University of Massachusetts, Amherst. His research interests are in network technologies, applications, and performance analysis, with a recent emphasis on resilient, secure and ultra-low power networking. He is an editor for IEEE/ACM Transactions on Networking, was program chair of IFIP Networking 2010 and ACM Sigmetrics 2011, and has received an NSF CAREER Award, IBM Faculty Award, the Best Student Paper award from the ACM SIGMETRICS 2000 conference, and Paper awards from the IEEE ICNP 2003 Conference, ACM CoNext 2008 Conference, and IEEE Communications 2011.
Networking Your Wallet, Credit Cards, and Keys [PDF]
Computer networks, multimedia systems, mobile and wireless systems, ubiquitous and pervasive computing
Prof. Henning Schulzrinne is Julian Clarence Levi Professor of Computer Science at Columbia University. He received his undergraduate degree in economics and electrical engineering from the Darmstadt University of Technology, Germany, his MSEE degree as a Fulbright scholar from the University of Cincinnati, Ohio and his Ph.D. from the University of Massachusetts in Amherst, Massachusetts. He was a member of technical staff at AT&T Bell Laboratories, Murray Hill and an associate department head at GMD-Fokus (Berlin), before joining the Computer Science and Electrical Engineering departments at Columbia University, New York. From 2004 to 2009, he served as chair of the Department of Computer Science. From 2010 to 2011, he was an Engineering Fellow at the Federal Communications Commission (FCC).
He is editor of the "Computer Communications Journal", the "ACM Transactions on Multimedia Computing", the "ComSoc Surveys & Tutorials" and a former editor of the "IEEE Transactions on Image Processing", "Journal of Communications and Networks", "IEEE/ACM Transactions on Networking" and the "IEEE Internet Computing Magazine".
He has been a member of the Board of Governors of the IEEE Communications Society and is vice chair of ACM SIGCOMM, former chair of the IEEE Communications Society Technical Committees on Computer Communications and the Internet and has been technical program chair of Global Internet, IEEE Infocom 2000, ACM NOSSDAV, IEEE IM, IPTComm 2008, IFIP Networking 2009 and IPtel and general co-Chair of ACM Multimedia 2004 and ICNP 2009. He serves on the Internet2 Applications, Middleware and Services Advisory Council and have led a working in the NSF GENI project. He also has been a member of the IAB (Internet Architecture Board). He serves on a number of conference and journal steering committees, including for the IEEE/ACM Transactions on Networking.
He has published more than 200 journal and conference papers, and more than 50 Internet RFCs. Protocols co-developed by him are now Internet standards, used by almost all Internet telephony and multimedia applications. His research interests include Internet multimedia systems, quality of service, and performance evaluation.
He served as Chief Scientist for FirstHand Technologies and Chief Scientific Advisor for Ubiquity Software Corporation. He is a Fellow of the IEEE, has received the New York City Mayor's Award for Excellence in Science and Technology, the VON Pioneer Award, TCCC service award and the IEEE Region 1 William Terry Award for Lifetime Distinguished Service to IEEE.
Sensing Our Connected World [PDF]
Yechiam Yemini (YY) is a Professor of computer science at Columbia University. His current research interests include computational biology and biological networks (for his previous networking research and the DCC lab visit http://www.cs.columbia.edu/dcc). He is currently teaching the Computational Genomics class W4761 (visit www.cs.columbia.edu/4761 for extensive course notes).
Professor Yemini has also been a co-founder of Comverse Technology (1983), http://www.comverse.com, System Management Arts (SMARTS) (1993) http://www.smarts.com , acquired by EMC in 2005, and Arootz (2006), http://www.arootz.com. He has served as a director and advisory board member of several high-tech companies and as a member of several government technology commissions and working groups; :-) his spare time is devoted to eclectic activities ranging from gourmet cooking to sand sculpturing (see http://www.cs.columbia.edu/~yemini/charleston ).
Turning Students into Entrepreneurs [PDF]
- Faculty
Michael
Collins
Julia
Hirschberg
Kathleen
McKeown- Research Scientists
Mona
Diab
Nizar
Habash
Rebecca
Passonneau
Owen
Rambow
Natural Language Processing and Spoken Language Processing involves computational approaches to the analysis and generation of text and speech. At Columbia these include text and speech summarization, question answering, machine translation, syntax and parsing, language generation, spoken dialogue systems, semantic representation and analysis, and the study of emotional and deceptive speech, in English, Arabic, and Mandarin, inter alia.
- COMS W4705 Natural Language Processing
- COMS W4706 Spoken Language Processing
- COMS E6998 Computational Approaches to Emotional Speech
- COMS E6998 Topic courses that focus on NLP
- COMS E6998 Machine Translation
- COMS E6998 NLP for the Web
- COMS E6998 Search Engine Technologies
- COMS E6998 Statistical Methods for NLP
Natural language processing and machine learning
My research interests are in natural language processing, and machine learning. I completed a PhD in computer science from the University of Pennsylvania in December 1998. From January 1999 to November 2002 I was a researcher at AT&T Labs-Research, and from January 2003 until December 2010 I was an assistant/associate professor at MIT. I joined Columbia University in January 2011.
Natural-language processing, spoken language processing, spoken dialogue systems, deceptive speech
Julia Hirschberg is a professor in the Department of Computer Science at Columbia University. She received her PhD in Computer Science from the University of Pennsylvania, after previously doing a PhD in sixteenth-century Mexican social history at the University of Michigan and teaching history at Smith. She worked at Bell Laboratories and AT&T Laboratories -- Research from 1985-2003 as a Member of Technical Staff and a Department Head, creating the Human-Computer Interface Research Department there. She served as editor-in-chief of Computational Linguistics from 1993-2003 and was an editor-in-chief of Speech Communication from 2003-2006; she is currently on the Editorial Board. She was on the Executive Board of the Association for Computational Linguistics (ACL) from 1993-2003, has been on the Permanent Council of International Conference on Spoken Language Processing (ICSLP) since 1996. She served on the board of the International Speech Communication Association (ISCA) from 1999-2007 (as President 2005-2007). She is on the board of the CRA-W and has been active in working for diversity at AT&T and at Columbia. She has been a fellow of the American Association for Artificial Intelligence since 1994 and an ISCA Fellow since 2008. She received a Columbia Engineering School Alumni Association (CESAA) Distinguished Faculty Teaching Award in 2009 and is a member of the University Senate. Her research focuses on spoken language processing, in particular, spoken dialogue systems, emotional speech, intonation, and text-to-speech synthesis.
Recognizing the Melody of Speech [PDF]
Artificial intelligence, natural-language processing, language generation, multimedia explanation, text summarization, user interfaces, user modeling, digital libraries
Kathleen R. McKeown is the Henry and Gertrude Rothschild Professor of Computer Science at Columbia University. She served as Department Chair from 1998-2003. Her research interests include text summarization, natural language generation, multi-media explanation, digital libraries, concept to speech generation and natural language interfaces. McKeown received the Ph.D. in Computer Science from the University of Pennsylvania in 1982 and has been at Columbia since then. In 1985 she received a National Science Foundation Presidential Young Investigator Award, in 1991 she received a National Science Foundation Faculty Award for Women, in 1994 was selected as a AAAI Fellow, and in 2003 was elected as an ACM Fellow. McKeown is also quite active nationally. She serves as a board member of the Computing Research Association and serves as secretary of the board. She served as President of the Association of Computational Linguistics in 1992, Vice President in 1991, and Secretary Treasurer for 1995-1997. She has served on the Executive Council of the Association for Artificial Intelligence and was co-program chair of their annual conference in 1991.
Summarizing the News (Automatically) [PDF]
Mona Diab is a Research Scientist at the Center for Computational Learning Systems (CCLS). She is also a co-founder of the CADIM group which addresses issues related to Arabic dialect computational processing. Before joining CCLS in February 2005, Mona earned her PhD in Computational Linguistics in the University of Maryland College Park in 2003. Her thesis was in computational lexical semantics specifically looking at issues of multilingual processing and word senses under the supervision of Philip Resnik. You can get a copy of her thesis here. In July 2003, Mona started a postdoc position under the mentorship of Daniel Jurafsky, at the Center for Spoken Language Processing at the University of Colorado, Boulder, then later in December she moved to Stanford University as a postdoctoral research scientist in the NLP group. Mona's research interests span several areas in computational linguistics: computational lexical semantics, multilingual processing, machine translation, computational socio-linguistics, and information extraction & text analytics. Her current research focus is Arabic Natural Language Processing with a special interest in Arabic dialects. Mona is currently the elected secretary for the Association for Computational Linguistics Special Interest Group for Semitic Language Processing (SIG-Semitic) and the elected secretary for SIG Lexical issues (SIGLEX). She is a member of the Editorial board for the Journal of Language Resources and Evaluation. Mona is also an elected University Senator representing the research community at Columbia University.
Nizar Habash is a research scientist at the Center for Computational Learning Systems in Columbia University,where he has worked since 2004.He received a B.Sc.in Computer Engineering and a B.A. in Linguistics and Languages from Old Dominion University in 1997. He received his Ph.D. in 2003 from the Computer Science Department, University of Maryland College Park. His Ph.D. thesis is titled Generation-Heavy Hybrid Machine Translation. In 2005, he co-founded the Columbia Arabic Dialect Modeling (CADIM) group with Mona Diab and Owen Rambow. Nizar�s research includes work on machine translation, natural language generation, lexical semantics, morphological analysis, generation and disambiguation, syntactic parsing and annotation, and computational modeling of Arabic and its dialects.
Nizar currently serves as secretary of the board of AMTA (Association for Machine Translation in the Americas) and of IAMT (International Association for Machine Translation). He served as vice-president of the Semitic Language Special Interest Group in the Association of Computational Linguistics (ACL) (2006-2009). He also served as the research community representative on the AMTA board (2006-2008). He previously served as a research program co-chair for the AMTA 2006 conference, the Workshop on Computational Approaches to Semitic Languages (ACL 2005) and the Workshop on Machine Translation for Semitic Languages (MT Summit 2003).
Nizar has published over 80 papers in international conferences and journals and has given numerous lectures and tutorials for academic and industrial audiences.
Rebecca J. Passonneau is a Senior Research Scientist at Columbia University's Center for Computational Learning Systems, and currently the Acting Director. She received her Ph.D. in Linguistics from the University of Chicago in 1985, where she collaborated heavily with cognitive scientists and statisticians. From the time of her degree to the present, she has worked on problems in computational linguistics and natural language processing at Columbia University, AT&T Research Labs, the University of Maryland, Bellcore, the Educational Testing Service, and the former Paoli Research Center. Her recent research contributions have been in robust spoken dialogue system architectures, methods to integrate unstructured free text data with structured data for machine learning, and linguistically motivated approaches to noisy spoken or textual input. Her work on spoken dialogue systems relies on a combination of ensembles of strategies for spoken language understanding, closer integration of spoken language understanding with dialogue management, and greater reliance on context to resolve noise in recognition output. She has also made significant contributions in evaluation of automated summarization, experimental design, and development of community-wide annotated corpus resources. Her earlier work focused on theoretical and empirical models of discourse structure, reference, and temporal semantics and pragmatics. Her publications include over seventy journal articles and referred conference proceedings.
Owen Rambow is a Research Scientist at the Center for Computational Learning Systems at Columbia University, New York. He received his Ph.D.in Computer and Information Sciences from the University of Pennsylvania in 1994. Rambow's research interests lie in the areas of formal representations for linguistic knowledge, especially syntax and lexical semantics, and applications of such representations to summarization, natural language generation, and dialog systems. His recent work has used machine learning in combination with sophisticated linguistic representations. For example, he has used machine learning to determine optimal ways of achieving communicative goals in dialog systems and to make surface generation choices in natural language generation. Work on email summarization uses features both general and specific to email to automatically learn what information to include in summaries of multi-party email threads. Current work also includes a project aimed at finding an optimal representation for the lexicon, morphology, and syntax of a group of closely related languages (dialects).
- Faculty
Steven
Bellovin
Roxana
Geambasu
Angelos
Keromytis
Tal
Malkin
Simha
Sethmadhavan
Salvatore
Stolfo
Junfeng
Yang
Security and privacy research includes intrusion detection systems, cryptology, privacy-preserving computation and search, usability of security interfaces, self-healing systems, denial of service, system hardening, information accountability, hardware enabled security, and insider threats.
- COMS W4118 Operating systems I
- COMS W4156 Advanced software engineering
- COMS W4180 Network Security
- COMS W4187 Security Architecture and Engineering
- COMS W4261 Introduction to Cryptography
- COMS E6183 Security
- COMS E6184 Privacy & Anonymity
- COMS E6185 Introduction to Cryptography or Intrusion Detection
- COMS E6261 Advanced Cryptography
Internet security, computer security, privacy, information technology policy
Steven M. Bellovin is a professor of computer science at Columbia University, where he does research on networks, security, and especially why the two don't get along. He joined the faculty in 2005 after many years at Bell Labs and AT&T Labs Research, where he was an AT&T Fellow. He received a BA degree from Columbia University, and an MS and PhD in Computer Science from the University of North Carolina at Chapel Hill. While a graduate student, he helped create Netnews; for this, he and the other perpetrators were given the 1995 Usenix Lifetime Achievement Award (The Flame). He is a member of the National Academy of Engineering and is serving on the Computer Science and Telecommunications Board of the National Academies, the Department of Homeland Security's Science and Technology Advisory Committee, and the Technical Guidelines Development Committee of the Election Assistance Commission; he has also received the 2007 NIST/NSA National Computer Systems Security Award.
Bellovin is the co-author of Firewalls and Internet Security: Repelling the Wily Hacker, and holds a number patents on cryptographic and network protocols. He has served on many National Research Council study committees, including those on information systems trustworthiness, the privacy implications of authentication technologies, and cybersecurity research needs; he was also a member of the information technology subcommittee of an NRC study group on science versus terrorism. He was a member of the Internet Architecture Board from 1996-2002; he was co-director of the Security Area of the IETF from 2002 through 2004.
Protecting Privacy in Complex Systems [PDF]
Her research lies in the general operating systems area, centering on cloud computing and computer security. Cloud computing is the computing paradigm today, and likely will be in the foreseeable future; computer security is one of the biggest challenges in computer science. Geambasu has made astounding contributions to both areas. Her prior results have won her two Best Paper Awards at top security and systems conferences and a Google PhD fellowship in cloud computing, and were featured in media outlets ranging from The New York Times to National Public Radio.
Computer and network security
Angelos Keromytis is an associate professor in the Computer Science department at Columbia University, in New York. He is also the director of the Network Security Lab. His general research interests are in systems and network security, and cryptography. His current interests revolve around software hardening, system self-healing, network denial of service, information accountability, and privacy.
In the past, he was an active participant in the IETF (Internet Engineering Task Force), and in particular the IPsec and IPSP Working Groups. He occasionally contributed to the OpenBSD operating system: he was the primary author of the IPsec stack and the OpenBSD Cryptographic Framework (OCF), which was later ported to FreeBSD and NetBSD.
Other large projects he worked on in the past include the KeyNote trust-management system and the STRONGMAN access control management system, the AEGIS secure bootstrap architecture and the SwitchWare Active Network architecture.
Protecting Computers After the Barbarians are Inside the Gate [PDF]
Cryptography, information and network security, foundations of computer science, computational complexity, distributed computation, randomness in computation
Tal Malkin is an associate professor of Computer Science at Columbia University, where she directs the Cryptography Lab. She received her Ph.D. in Computer Science from the Massachusetts Institute of Technology in 2000, and joined Columbia after three years as a research scientist in the Secure Systems Research Department at AT&T Labs - Research. Her research interests are in cryptography, security, complexity theory, and related areas. She has served on program committees and steering committees for over twenty international conferences on cryptography, theoretical computer science, and security. She chaired the CT-RSA conference, and is on the editorial board for the Theory of Computing Journal.
Prof. Malkin is the recipient an NSF CAREER award, an IBM faculty partnership award, Google Faculty Research award, and a research fellowship of the Columbia University Diversity Initiative. Her research has been funded by NSF, NSA, NYSIA, DHS, IARPA, and gifts from Google, IBM, Mitsubishi, and NEC.
Securing the Lock after the Key is Stolen [PDF]
Computer architecture, hardware security
Prof. Simha Sethumadhavan is an assistant professor of computer science at Columbia University in New York. At Columbia, he directs the computer architecture and security technologies lab (CASTL). Research at CASTL is targeted at solving two important problems that threaten to stall computing advances: energy-inefficiency and the lack of security and erosion of privacy in computing systems. Prof. Sethumadhavan obtained his PhD from UTAustin in 2007.
Designing Secure Hardware [PDF]
Computer security, intrusion detection systems, parallel computing, artificial intelligence, machine learning
Salvatore J. Stolfo is Professor of Computer Science at Columbia University. He received his Ph.D. from NYU Courant Institute in 1979 and has been on the faculty of Columbia ever since. He won an IBM Faculty Development Award early in his academic career in 1983. He has published several books and well over 200 scientific papers since then, several winning best paper awards, in the areas of parallel computing, AI knowledge-based systems, data mining and most recently computer security and intrusion detection systems (see www.cs.columbia.edu/ids). He has been granted 26 patents in the areas of parallel computing and database inference and computer security; most have been licensed or sold. His research has been supported by DARPA, NSF, ONR, NSA, CIA, IARPA, AFOSR, ARO, NIST, DHS and numerous companies and state agencies over the years while at Columbia. Professor Stolfo has mentored over 30 PhD students (26 have graduated to date) and many dozens of Master�s students. His most recent research is devoted to payload anomaly detection for zero-day exploits, secure private querying, private and anonymous network trace synthesis for Predict.org, Symbiotic embedded machines, automatic bait generation for trap-based defense to mitigate the insider threat and he recently conducted a study in the area of multi-core parallel computing.
Using Anomalies to Defend Against Insiders [PDF]
Operating systems, software reliability, programming languages, security, distributedsystems,software engineering
Junfeng Yang's research spans operating systems, programming languages, security, and software engineering, with a focus on creating reliable and secure systems. He is currently an assistant professor at Columbia, leading the Reliable Computer Systems lab (RCS). In 2008, he received his PhD from Stanford, where he developed eXplode, a general, lightweight system for effectively finding storage system errors. From 2007-2008, he was at Microsoft Research, Silicon Valley, extending eXplode to check production distributed systems. His work has led to numerous reliability patches to real systems such as the Linux kernel, a technology transfer to the Microsoft Azure platform, and a best paper award at OSDI 04.
Weaving More Reliable Software [PDF]
Our systems research includes a broad range of topics encompassing architecture-sensitive database system design, cloud computing, collaborative work, computer and network privacy and security, concurrent and parallel systems, database systems, data warehousing, deterministic multithreading, distributed systems, information extraction and management, file systems, mobile computing, multicore systems, multimedia systems, operating systems, performance evaluation, programming languages and compilers, quantum computing, query languages and processing, social media mining, software development environments and tools, software engineering, software reliability, software testing, thin-client computing virtualization, web search, and web technologies.
- COMS W4115 Programming languages and translators
- COMS W4118 Operating systems I
- COMS W4156 Advanced software engineering
- COMS W4111 Introduction to Databases
- COMS W4112 Database System Implementation
Alfred V. Aho is Lawrence Gussman Professor in the Computer Science Department at Columbia University. He served as Chair of the department from 1995 to 1997, and in the spring of 2003.
Professor Aho has a B.A.Sc in Engineering Physics from the University of Toronto and a Ph.D. in Electrical Engineering/Computer Science from Princeton University.
Professor Aho won the Great Teacher Award for 2003 from the Society of Columbia Graduates.
Professor Aho has won the IEEE John von Neumann Medal and is a Member of the U.S. National Academy of Engineering and the American Academy of Arts and Sciences. He received honorary doctorates from the Universities of Helsinki and Waterloo, and is a Fellow of the American Association for the Advancement of Science, ACM, Bell Labs, and IEEE.
Professor Aho is well known for his many papers and books on algorithms and data structures, programming languages, compilers, and the foundations of computer science. His book coauthors include John Hopcroft, Brian Kernighan, Monica Lam, Ravi Sethi, Jeff Ullman, and Peter Weinberger.
Professor Aho is the "A" in AWK, a widely used pattern-matching language; "W" is Peter Weinberger and "K" is Brian Kernighan. (Think of AWK as the initial pure version of perl.) He also wrote the initial versions of the string pattern-matching programs egrep and fgrep that first appeared on UNIX.
Professor Aho's current research interests include programming languages, compilers, algorithms, software engineering, and quantum computers.
Professor Aho has served as Chair of ACM's Special Interest Group on Algorithms and Computability Theory, and Chair of the Advisory Committee for the National Science Foundation's Computer and Information Science and Engineering Directorate. He is currently the coeditor-in-chief of the contributed articles section of the Communications of the ACM.
Prior to his current position at Columbia, Professor Aho was Vice President of the Computing Sciences Research Center at Bell Labs, the lab that invented UNIX, C and C++. He was also a member of technical staff, department head, and director of this center. Professor Aho was also the General Manager of the Information Sciences and Technologies Research Laboratory at Bellcore (now Telcordia).
Creating Reliable Programs from Unreliable Programmers [PDF]
Databases, digital libraries, distributed search over text databases, Web search, "top-k" query processing, information extraction, text mining
Luis Gravano has been on the faculty of the Computer Science Department, Columbia University, since September 1997, where he has been an associate professor since July 2002. From January through August 2001, Luis was a Senior Research Scientist at Google (on leave from Columbia University). He received his Ph.D. degree in Computer Science from Stanford University in 1997. He also received an M.S. degree from Stanford University in 1994 and a B.S. degree from the Escuela Superior Latinoamericana de Informatica (ESLAI), Argentina, in 1991. Luis is a recipient of a CAREER award from the National Science Foundation.
Supercharging Search Engines [PDF]
Software testing, collaborative work, computer and network security, parallel computing and distributed systems, self-managing systems, Web technologies, information management, software development environments and tools
Gail E. Kaiser is a Professor of Computer Science and the Director of the Programming Systems Laboratory in the Computer Science Department at Columbia University. She was named an NSF Presidential Young Investigator in Software Engineering and Software Systems in 1988, and has published over 150 refereed papers in a range of software areas. Prof. Kaiser's research interests include software testing, collaborative work, computer and network security, parallel and distributed systems, self-managing systems, Web technologies, information management, and software development environments and tools. She has consulted or worked summers for courseware authoring, software process and networking startups, several defense contractors, the Software Engineering Institute, Bell Labs, IBM, Siemens, Sun and Telcordia. Her lab has been funded by NSF, NIH, DARPA, ONR, NASA, NYS Science & Technology Foundation, and numerous companies. Prof. Kaiser served on the editorial board of IEEE Internet Computing for many years, was a founding associate editor of ACM Transactions on Software Engineering and Methodology, chaired an ACM SIGSOFT Symposium on Foundations of Software Engineering, vice chaired three of the IEEE International Conference on Distributed Computing Systems, and serves frequently on conference program committees. She also served on the Committee of Examiners for the Educational Testing Service's Computer Science Advanced Test (the GRE CS test) for three years, and has chaired her department's doctoral program since 1997. Prof. Kaiser received her PhD and MS from CMU and her ScB from MIT.
Testing What Cannot Be Tested [PDF]
Her research lies in the general operating systems area, centering on cloud computing and computer security. Cloud computing is the computing paradigm today, and likely will be in the foreseeable future; computer security is one of the biggest challenges in computer science. Geambasu has made astounding contributions to both areas. Her prior results have won her two Best Paper Awards at top security and systems conferences and a Google PhD fellowship in cloud computing, and were featured in media outlets ranging from The New York Times to National Public Radio.
Operating systems, distributed systems, mobile computing, thin-client computing, performance evaluation
Jason Nieh is an Associate Professor of Computer Science and Director of the Network Computing Laboratory at Columbia University. He previously served as the technical advisor for nine States on the Microsoft Antitrust Settlement and an expert witness in the Microsoft New York Class Action Settlement. He has made research contributions in software systems across a broad range of areas, including operating systems, virtualization, thin-client computing, utility computing, mobile computing, multimedia, web technologies, and performance evaluation. He was program co-chair of the most recent SIGMETRICS/Performance conference, and has served on numerous conference program committees including MobiCom, MobiSys, OSDI, USENIX, and WWW. Honors for his research work include the Sigma Xi Young Investigator Award, awarded once every two years in the physical sciences and engineering, a National Science Foundation CAREER Award, a Department of Energy Early Career Award, multiple IBM Faculty and Shared University Research Awards, and various best paper awards, including the 2004 MobiCom Best Student Paper Award. A dedicated teacher, he received the Distinguished Faculty Teaching Award from the Columbia Engineering School Alumni Association for his innovations in teaching operating systems and for introducing virtualization as a pedagogical tool. Professor Nieh earned his B.S. from MIT and his M.S. and Ph.D. from Stanford University, all in Electrical Engineering. He is married to Belinda Nieh and they have four children, Joanna, Caleb, Emma, and Zachary. They live in New York City.
Delivering Desktop Computing from the Cloud [PDF]
Databases, query optimization, declarative languages for database systems, logic programming, architecture-sensitive software design
Kenneth Ross is a Professor in the Computer Science Department at Columbia University in New York City. His research interests touch on various aspects of database systems, including query processing, query language design, data warehousing, and architecture-sensitive database system design. He also has an interest in computational biology, including the analysis of large genomic data sets. Professor Ross received his PhD from Stanford University. He has received several awards, including a Packard Foundation Fellowship, a Sloan Foundation Fellowship, and an NSF Young Investigator award.
Processing Parallel Insights [PDF]
Operating systems, software reliability, programming languages, security, distributedsystems,software engineering
Junfeng Yang's research spans operating systems, programming languages, security, and software engineering, with a focus on creating reliable and secure systems. He is currently an assistant professor at Columbia, leading the Reliable Computer Systems lab (RCS). In 2008, he received his PhD from Stanford, where he developed eXplode, a general, lightweight system for effectively finding storage system errors. From 2007-2008, he was at Microsoft Research, Silicon Valley, extending eXplode to check production distributed systems. His work has led to numerous reliability patches to real systems such as the Linux kernel, a technology transfer to the Microsoft Azure platform, and a best paper award at OSDI 04.
Weaving More Reliable Software [PDF]
- Faculty
Xi
Chen
Jonathan
Gross
Tal
Malkin
Rocco
Servedio
Clifford
Stein
Joseph
Traub
Henryk
Wozniakowski
Mihalis
Yannakakis
Theory research includes computational complexity, algorithms and data structures, cryptography, quantum computing, computational geometry, approximation algorithms, computational game theory, algorithmic graph theory and combinatorics, online algorithms, computational learning theory, algebraic computation, optimization, randomness in computing, parallel and distributed computing, algorithmic coding theory, and theoretical aspects of areas such as networks, privacy, information retrieval, computational biology, and databases.
- COMS W3261 Computer Science Theory
- CSOR W4231 Analysis of Algorithms I
- COMS W4236 Intro. to Computational Complexity
- COMS W4203 Graph Theory
- COMS W4205 Combinatorial Theory
- COMS W4241 Numerical Algorithms and Complexity
- COMS W4252 Introduction to Computational Learning Theory
- COMS W4261 Introduction to Cryptography
- COMS W4281 Introduction to Quantum Computing
- CSEE E6180 Performance Analysis
- COMS E6204 Topics in Graph Theory
- COMS E6232 Analysis of Algorithms II
- COMS E6253 Computational Learning Theory II
- COMS E6261 Advanced Cryptography
- COMS E6291 Theoretical Topics in C.S.
- COMS E6717 Information Theory
- COMS E6998 Adv. Topics in Comp. Geometry
- COMS E6998 Adv. Topics in Complexity Theory
- COMS E6998 Algorithmic Game Theory
- COMS E6998 Algorithms for Dealing with Massive Data
- COMS E6998 Algorithmic Graph Theory
Algorithmic Game Theory And Economics, Complexity Theory
Xi Chen is an assistant professor of Computer Science at Columbia University. He received his Ph.D. in Computer Science from Tsinghua University in 2007. Before joining Columbia in 2011, he was a postdoctoral researcher at the Institute for Advanced Study, Princeton University, and the University of Southern California. His main research interests are in algorithmic game theory and economics, and computational complexity theory.
Computational aspects of topological graph theory and knot theory, enumerative analysis, and combinatorial models; applications to network layouts on higher-order surfaces and to interactive computer graphics of weaves and links
Jonathan Gross is Professor of Computer Science at Columbia University. His research in topology, graph theory, and cultural sociometry has earned him an Alfred P. Sloan Fellowship, an IBM postdoctoral fellowship, and various research grants from the Office of Naval Research, the National Science Foundation, and the Russell Sage Foundation. His best-known mathematical invention, the voltage graph, is widely used in the construction of minimum-genus graph imbeddings and of symmetric graph imbeddings. He and Thomas Tucker proved that every covering graph can be realized as a voltage graph construction. He also wrote the pioneering papers on enumerative techniques in topological graph theory, with various co-authors. His biography appears in Who's Who in America.
Professor Gross has created and delivered numerous software-development short courses for Bell Laboratories and for IBM. These include mathematical methods for performance evaluation at the advanced level and for developing reusable software at a basic level. He has received several awards for outstanding teaching at Columbia University, including the career Great Teacher Award from the Society of Columbia Graduates.
His most recent books are Topics in Topological Graph Theory (co-edited with Tom Tucker and series editors Lowell Beineke and Robin Wilson) and Combinatorial Methods with Computer Applications. Other books include Topological Graph Theory (co-authored with Thomas W. Tucker), Graph Theory and Its Applications (co-authored with Jay Yellen), and the Handbook of Graph Theory (co-edited with Jay Yellen). Another previous book, Measuring Culture (co-authored with Steve Rayner) constructs network-theoretic tools for measuring sociological phenomena. Prior to Columbia University, Professor Gross was in the Mathematics Department at Princeton University, where he worked with Ralph Fox. His undergraduate work was at the Massachusetts Institute of Technology. His Ph.D. thesis on 3-dimensional topology at Dartmouth College solved a published problem of Fields Medalist John Milnor.
Untying Knots with Mathematics [PDF]
Cryptography, information and network security, foundations of computer science, computational complexity, distributed computation, randomness in computation
Tal Malkin is an associate professor of Computer Science at Columbia University, where she directs the Cryptography Lab. She received her Ph.D. in Computer Science from the Massachusetts Institute of Technology in 2000, and joined Columbia after three years as a research scientist in the Secure Systems Research Department at AT&T Labs - Research. Her research interests are in cryptography, security, complexity theory, and related areas. She has served on program committees and steering committees for over twenty international conferences on cryptography, theoretical computer science, and security. She chaired the CT-RSA conference, and is on the editorial board for the Theory of Computing Journal.
Prof. Malkin is the recipient an NSF CAREER award, an IBM faculty partnership award, Google Faculty Research award, and a research fellowship of the Columbia University Diversity Initiative. Her research has been funded by NSF, NSA, NYSIA, DHS, IARPA, and gifts from Google, IBM, Mitsubishi, and NEC.
Securing the Lock after the Key is Stolen [PDF]
Computational learning theory, computational complexity theory, randomness in comutation, combinatorics cryptography
I am an associate professor in the Computer Science Department of Columbia University, where I do research in theoretical computer science. My main research area is computational learning theory, but I also have strong interests in computational complexity theory, combinatorics, randomized algorithms, cryptography, and quantum computation.
Playing '20 Questions' with Geometry [PDF]
Clifford Stein is a Professor of IEOR at Columbia University. He also holds an appointment in the Department of Computer Science. He is the director of Undergraduate Programs for the IEOR Department. Prior to joining Columbia, he spent 9 years as an Assistant and Associate Professor in the Dartmouth College Department of Computer Science.
His research interests include the design and analysis of algorithms, combinatorial optimization, operations research, network algorithms, scheduling, algorithm engineering and computational biology. Professor Stein has published many influential papers in the leading conferences and journals in his field, and has occupied a variety of editorial positions including the journals ACM Transactions on Algorithms, Mathematical Programming, Journal of Algorithms, SIAM Journal on Discrete Mathematics and Operations Research Letters. His work has been supported by the National Science Foundation and Sloan Foundation. He is the winner of several prestigious awards including an NSF Career Award, an Alfred Sloan Research Fellowship and the Karen Wetterhahn Award for Distinguished Creative or Scholarly Achievement. He is also the co-author of the two textbook. Introduction to Algorithms, with T. Cormen, C. Leiserson and R. Rivest is currently the best-selling textbook in algorithms and has been translated into 8 languages. Discrete Math for Computer Science , with Ken Bogart and Scot Drysdale, is a new text book which covers discrete math at an undergraduate level.
Estimating Solutions to Difficult Problems [PDF]
Quantum computing, computational complexity, information-based complexity, financial computations
He was Head of the Computer Science Department at Carnegie-Mellon University 1971-1979 and Founding Chairman of the Computer Science Department at Columbia University 1979-1989.
He served as Founding Chair of the Computer Science and Telecommunications Board (CSTB) of the National Academies 1986-1992. He served again as chair 2005-2009. He has been appointed as a member of the Division Committee on Engineering and Physical Sciences (DEPS) of the National Academies.
Traub is author or editor of ten books and some one hundred twenty journal articles. He is Editor-in-Chief of the Journal of Complexity and Associate Editor of Complexity.
His numerous honors include election to the National Academy of Engineering in 1985, the 1991 Emanuel R. Piore Gold Medal from IEEE, and the 1992 Distinguished Service Award, Computer Research Association. He is a Fellow of the American Association for the Advancement of Science, the Association for Computing Machinery, and the New York Academy of Sciences. He has been Sherman Fairchild Distinguished Scholar at the California Institute of Technology and received a Distinguished Senior Scientist Award from the Alexander von Humboldt Foundation. He was selected by the Academia Nazionale dei Lincei in Rome to present the 1993 Lezioni Lincee, a cycle of six lectures. Traub received the 1999 Mayor�s Award for Excellence in Science and Technology. The Award was presented by Mayor Rudy Giuliani at a ceremony in New York City. In May, 2001, he received an honorary Doctorate of Science from the University of Central Florida.
He has served as advisor or consultant to the senior management of numerous organizations including IBM, Hewlett-Packard, Schlumberger, Stanford University, INRIA (Paris), Federal Judiciary Center, DARPA, NSF, and Lucent Technologies. In 2008 he was elected to the Board of Directors of the Marconi Society.
Computing Quantum Potential [PDF]
Computational complexity, information-based complexity, quantum computing, algorithmic analysis, numerical mathematics
I share my time between Columbia University and the University of Warsaw. At Columbia, I am Professor of Computer Science and at Warsaw I am Professor of Applied Mathematics.
I am mostly interested in computational complexity of continuous problems. For most continuous problems, we have only partial information. For problems defined on spaces of functions, this partial information is usually given by a finite number of function values at some points which we can choose. One of the central issues is to determine how many pieces of information, or function values, are needed to solve the computational problem to within a prescribed accuracy. The partial information plays the main role in this line of research and that is why this field is called information-based complexity. The error and cost of algorithms, as well as the complexity, can be defined in various settings including the worst case, the average case, the randomized, the probababilistic, and the recently added setting of quantum computation.
The quantum setting assumes that we can perform computations on classical and quantum computers. Even though building a quantum computer remains a difficult task, a quantum computer can lower the complexity of many continuous problems. Usually we have exponential speedups between the worst case and the quantum complexities, and polynomial speedups between the randomized and quantum complexities for a number of continuous problems such that integration, path integration, approximation, the solution of ordinary or partial differential equations etc.
I am especially interested in tractability of multivariate problems which are defined on spaces of functions of d variables. The main emphasis is on large d, where d is in the hundreds or even thousands. There are many important practical computational problems with such a huge d. They occur in mathematical finance, physics, statistics etc.
Suppose we want to approximate a multivariate problem to within a prescribed error tolerance. Tractability means that we can do it at a cost which is polynomial in d and the reciprocal of the error tolerance. For typical multivariate problems defined on classical spaces we often have intractability in the worst case setting, since the complexity depends exponentially on the number d of variables. This is called the curse of dimensionality. To break this curse we can switch to the randomized or the average case settings. Sometimes this works, and the best example is probably Monte Carlo in the randomized setting for multivariate integration. Monte Carlo breaks the curse if the variances of the functions depend at most polynomially on d. Another alternative, which is recently used in many papers, is to stay in the worst case setting but use additional knowledge about the multivariate problem to shrink the class of functions. This leads to weighted classes of functions. Necessary and sufficient conditions for tractability, in terms of the weights, are known today for many multivariate problems.
Algorithms, complexity theory, combinatorial optimization, databases, testing and verification
Mihalis Yannakakis is the Percy K. and Vida L. W. Hudson Professor of Computer Science at Columbia University. Prior to joining Columbia, he was Director of the Computing Principles Research Department at Bell Labs (1991-2001) and at Avaya Labs (2001-2002), and Professor of Computer Science at Stanford University (2002-2003). Dr. Yannakakis received his PhD from Princeton University in 1979.
His research interests include algorithms, complexity, optimization, databases, testing and verification. He has served on the editorial boards of several journals, including as the past editor-in-chief of the SIAM Journal on Computing, and has chaired various conferences, including the IEEE Symposium on Foundations of Computer Science, the ACM Symposium on Theory of Computing and the ACM Symposium on Principles of Database Systems. Dr. Yannakakis is a Fellow of the ACM and of Bell Labs, and a recipient of the Knuth Prize.
Calculating What Is Possible [PDF]
- COMS W4731 Computer Vision
- COMS W4733 Computational Aspects of Robotics
- COMS W4735 Visual Interfaces to Computers
- COMS W4737 Biometrics
- COMS W4771 Machine Learning
- COMS E6733 3-D Photography
- COMS E6734 Computational Photography
Robotics, computer vision, 3-D modeling
Peter K. Allen is Professor of Computer Science at Columbia University. He received the A.B. degree from Brown University in Mathematics-Economics, the M.S. in Computer Science from the University of Oregon and the Ph.D. in Computer Science from the University of Pennsylvania, where he was the recipient of the CBS Foundation Fellowship, Army Research Office fellowship and the Rubinoff Award for innovative uses of computers. His current research interests include robotic grasping, 3-D vision and modeling, and medical robotics. In recognition of his work, Professor Allen has been named a Presidential Young Investigator by the National Science Foundation.
Building Disposable Surgical Robots [PDF]
Computer vision, biometrics, face recognition, computational photography, computer graphics, biological species identification
Peter N. Belhumeur is currently a Professor in the Department of Computer Science at Columbia University and the Director of the Laboratory for the Study of Visual Appearance (VAP LAB). He received a Sc.B. in Information Sciences from Brown University in 1985. He received his Ph.D. in Engineering Sciences from Harvard University under the direction of David Mumford in 1993. He was a postdoctoral fellow at the University of Cambridge's Isaac Newton Institute for Mathematical Sciences in 1994. He was made Assistant, Associate and Professor of Electrical Engineering at Yale University in 1994, 1998, and 2001, respectively. He joined Columbia University as a Professor of Computer Science in 2002. His research focus lies somewhere in the mix of computer vision, computer graphics, and computational photography. He is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) and the National Science Foundation Career Award. He won both the Siemens Best Paper Award at the IEEE Conference on Computer Vision and Pattern Recognition and the Olympus Prize at the European Conference of Computer Vision.
Turning a New Leaf on Face Recognition [PDF]
Chang is an active researcher leading development of novel theories, algorithms, and systems for content-based image video search, visual communication, multimedia analytics, as well as media forensics. His work has been influential in shaping the vibrant fields of content-based multimedia retrieval. In the 90's, he and his students developed several of the first image/video search engines, such as VisualSEEk, VideoQ, and WebSEEk. He has also been recognized for inventing innovative communication systems that combine content analytics, adaptive mobile streaming, and summarization. Other significant contributions include large-scale concept-based video search engines (e.g., CuZero), a widely used library of image classification models (e.g., Columbia374), international multimedia indexing/communication standards (e.g., MPEG-7 and MPEG-21), and large multimedia ontologies (e.g., LSCOM). In addition, Chang has led cross-disciplinary projects, including a DAVIC Video on Demand international interoperability test, a video library under Columbia's Health Care Digital Library, and the ADVENT university-industry research consortium with the participation of more than 25 industry sponsors. Many video indexing technologies developed by his group have been licensed to companies. He has received the IEEE Kiyo Tomiyasu technical field award, IBM Faculty Award, NSF CAREER Award, and ONR Young Investigator Award. He and his students have won many best paper awards and best student paper awards from IEEE, ACM, and SPIE. He served as the Editor-in-Chief of the IEEE Signal Processing Magazine (2006-8), Chair of Columbia Electrical Engineering Department (2007-2010), general co-chair of ACM Multimedia Conference in 2000 and 2010, and advisor for several media technology companies and research institutions. His research has been broadly supported by government agencies as well as industry sponsors. He is an IEEE Fellow and a Fellow of the American Association for the Advancement of Science.
Developing Next-Generation Visual Search Engines [PDF]
Machine learning, social networks, graphs, vision, and spatio-temporal modeling
Tony Jebara is Associate Professor of Computer Science at Columbia University and co-founder of Sense Networks. He directs the Columbia Machine Learning Laboratory whose research intersects computer science and statistics to develop new frameworks for learning from data with applications in vision, networks, spatio-temporal data, and text. Jebara has published over 75 peer-reviewed papers in conferences and journals including NIPS, ICML, UAI, COLT, JMLR, CVPR, ICCV, and AISTAT. He is the author of the book Machine Learning: Discriminative and Generative and co-inventor on multiple patents in vision, learning and spatio-temporal modeling. In 2004, Jebara was the recipient of the Career award from the National Science Foundation. His work was recognized with a best paper award at the 26th International Conference on Machine Learning, a best student paper award at the 20th International Conference on Machine Learning as well as an outstanding contribution award from the Pattern Recognition Society in 2001. Jebara's research has been featured on television (ABC, BBC, New York One, TechTV, etc.) as well as in the popular press (New York Times, Slash Dot, Wired, Businessweek, IEEE Spectrum, etc.). He obtained his PhD in 2002 from MIT. Esquire magazine named him one of their Best and Brightest of 2008.
Tony serves as Associate Editor for the Journal of Machine Learning Research and Associate Editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence. He is currently on the steering committee of the NYAS Machine Learning Symposium.
Finding Patterns in a Complex World [PDF]
Computer vision, video understanding, visual user interfaces, medical imaging processing, artificial intelligence
John R. Kender is Professor of Computer Science at Columbia University. His primary research interests are in the use of statistical and semantic methods for navigating through collections of videos. He received his Ph.D. from Carnegie‐Mellon University in 1980, specializing in computer vision and artificial intelligence, and he was the first professor hired in its Robotics Institute. Since 1981, he has been one of the founding faculty of the Department of Computer Science of Columbia University. He was named one of the first National Science Foundation Presidential Young Investigators, and he has served the School of Engineering and Applied Science at Columbia both as Acting Dean of Students and as Vice Dean. He has been awarded the Great Teacher Award of the Society of Columbia Graduates, and the Distinguished Faculty Teaching Award of the Columbia Engineering School Alumni Association. He has graduated 22 PhD students, has published well over 125 refereed articles, and holds multiple patents and patent applications in computer vision.
Indexing Videos Automatically [PDF]
Computer vision, computational imaging, computer graphics, robotics, human-computer interfaces
Shree K. Nayar received his PhD degree in Electrical and Computer Engineering from the Robotics Institute at Carnegie Mellon University in 1990. He is currently the T. C. Chang Professor of Computer Science at Columbia University. He co-directs the Columbia Vision and Graphics Center. He also heads the Columbia Computer Vision Laboratory (CAVE), which is dedicated to the development of advanced computer vision systems. His research is focused on three areas; the creation of novel cameras, the design of physics based models for vision, and the development of algorithms for scene understanding. His work is motivated by applications in the fields of digital imaging, computer graphics, and robotics.
He has received best paper awards at ICCV 1990, ICPR 1994, CVPR 1994, ICCV 1995, CVPR 2000 and CVPR 2004. He is the recipient of the David Marr Prize (1990 and 1995), the David and Lucile Packard Fellowship (1992), the National Young Investigator Award (1993), the NTT Distinguished Scientific Achievement Award (1994), the Keck Foundation Award for Excellence in Teaching (1995), the Columbia Great Teacher Award (2006) and Carnegie Mellon University's Alumni Achievement Award. In February 2008, he was elected to the National Academy of Engineering.
Picturing the World in New Ways [PDF]
