5:00 PM to 6:30 PM
Davis Auditorium (CEPSR 412)
Dean Mary C. Boyce cordially invites you to a conversation with renowned computer scientist, investor, hedge fund manager, and computational biochemist David E. Shaw.
Dr. Shaw serves as chief scientist of D. E. Shaw Research, and as a senior research fellow and adjunct professor at Columbia University. He received his Ph.D. from Stanford University in 1980, served on the faculty of the Computer Science Department at Columbia until 1986, and founded the D. E. Shaw group in 1988. Since 2001, Dr. Shaw has devoted his time to hands-on research in the field of computational biochemistry. His lab is currently involved in the development of new algorithms and machine architectures for high-speed biomolecular simulations, and in the application of such simulations to basic scientific research and computer-aided drug design.
Dr. Shaw was appointed to the President's Council of Advisors on Science and Technology by President Clinton in 1994, and again by President Obama in 2009. He is a two-time winner of the ACM Gordon Bell Prize, and was elected to the American Academy of Arts and Sciences in 2007, to the National Academy of Engineering in 2012, and to the National Academy of Sciences in 2014.
After the talk, we will host a special reception with Dr. Shaw for a limited number of current students. Tickets to the reception will be determined via lottery. Students may register for the lottery when they register for a ticket to the lecture. Winners will be notified of their spot two (2) days prior to the event and will be required to confirm attendance.
Space is limited! Tickets are on a first come, first served basis. A wait list will be available when necessary.
9:00 AM to 5:00 PM
Roone Arledge Auditorium
Alfred Spector, Chief Technology Officer and Head of Engineering at Two Sigma
OPPORTUNITIES AND PERILS IN DATA SCIENCE
Lightning Talk Sessions
Our Connected World
Suman Jana, Assistant Professor of Computer Science
Susan McGregor, Assistant Professor of Journalism; Assistant Director, Tow Center for Digital Journalism
Hollie Russon-Gilman, Lecturer in International and Public Affairs
Applications of Data Science
Stefano Fusi, Associate Professor of Neuroscience
Andrew E. Gelman, Professor of Statistics and Political Science
Andreas Christian Mueller, Lecturer in the Discipline of Data Science
Mingoo Seok, Assistant Professor of Electrical Engineering
Patient Driven Health Care
Kenrick Dwain Cato, Assistant Professor of Nursing
Ying Kuen K. Cheung, Professor of Biostatistics
Noemie Elhadad, Associate Professor of Biomedical Informatics
Xuan Sharon Di, Assistant Professor of Civil Engineering and Engineering Mechanics
Constantinos Maglaras, David and Lyn Silfen Professor of Business
Eric L. Talley, Isidor and Seville Sulzbacher Professor of Law
For more information and tickets, go here.
12:00 PM to 1:00 PM
CS Conference Room
John Brunhaver , Arizona State University
Computer vision, image signal processing, and computational photography are, increasingly, a significant part of the computation in our hand-held devices, automated systems, and multimedia protocols. Given the significant energy constraints of modern computer systems, fixed function image processing hardware plays an important role in enabling these applications. Simultaneously, non-recurring engineering costs make it difficult to explore the design space of these applications in hardware. By abstracting image processing applications as pipelines of stencil kernels (e.g. convolution) in a Domain Specific Language, we have shown how complex algorithms can be quickly translated into efficient hardware. Relative to a GPU in the same process technology, this fixed function hardware is 3 orders of magnitude more energy and area efficient. In fact, at 0.4 pJ energy per operation and 1 TeraOp per square millimeter, fixed function image processing hardware is, on average, is 2x more efficient than the general class of fixed function hardware. However, many products require dynamic reconfigurability to virtually support a large number of applications. To broadly enable application experts, an architecture should be easily programmed, reconfigured many times per frame, and approach the energy efficiency of fixed hardware.
Our recent work has explored how Domain Specific Languages can be used to quickly program hardware customized to the domain of Computer Vision.
Our early results indicate an energy efficiency within 5x of fixed hardware. FPGA's, which can be difficult to program and have long configuration cycles, are at least 25x more energy expensive than fixed hardware. Further, given the relatively significant cost of GPU computation, it is also an alternative for the acceleration of embedded real-time graphics.
John Brunhaver is an Assistant Professor at Arizona State University since 2015. His current research focuses on high performance computer architectures for computer vision and the design automation techniques to quickly implement them. His curricular development, based in constructionism, emphasizes the skills and knowledge required to implement computer hardware or configure FPGAs using hardware design languages.
His thesis, written as a part of his Ph.D. work at Stanford University, was titled "The Design and Optimization of a Stencil Engine" and examines the virtual machine model for an image processing and image understanding domain specific processor.
2:00 PM to 3:00 PM
Davis Auditorium (CEPSR 412)
Jim Kurose, National Science Foundation
Advances in computer and information science and engineering are providing unprecedented opportunities
for research and education. My talk will begin with an overview of CISE activities and programs at the
National Science Foundation and include a discussion of current trends that are shaping the future of our
discipline. I will also discuss the opportunities as well as the challenges that lay ahead for our community
and for CISE.
5:00 PM to 6:00 PM
Davis Auditorium (CEPSR 412)
Michael Winter, Senior Fellow for Advanced Technology at Pratt & Whitney
The lecture will present the motivation, mechanics, and methodologies of model-based systems engineering as applied to product platforms and infrastructures that are often safety or operationally critical. Cyber-physical system-of-systems that combine both physics and controls form the basis of modern society. Application of systems engineering principles in an analytic context with focus on requirements, architecture, model-based development, and design flows will be presented as applied in an industrial context.
Dr. Michael Winter is a seasoned corporate leader who has held numerous responsibilities running technical and multi-national organizations. His current position is Senior Fellow for Advanced Technology at Pratt & Whitney. He is responsible for development and maturation of the Company's technology portfolio, including identification and prioritization of technologies, establishing intellectual property basis, technology licensing, and technology partnership programs. Most recently he served as Director of Systems & Controls Engineering (SCE) at United Technologies Corporation, a world-wide corporation supplying a broad range of high-technology products and services to the fast-growing aerospace and building industries. He led the SCE organization and initiative to provide UTC's business units with the competency, capacity and tools needed to deliver the complex cyber-physical systems that are the core of UTC products.
In more than 25 years with UTC, Dr. Winter has made contributions working with fuel cells, lasers, and combustion & propulsion systems. Previously, Dr. Winter was Chief Engineer for Technology at Pratt & Whitney, responsible for the Company's technology portfolio. He also was responsible for development of the Pratt & Whitney Technical Career Ladder and for leading the Fellows Program, which recognizes the company's top technical experts. Earlier, he served at United Technologies Research Center as Director of the Flight Systems Program, with responsibility for advanced technology for Hamilton Sundstrand and Sikorsky Aircraft.
Dr. Winter holds Doctor of Philosophy, Master of Science and Master of Philosophy degrees from Yale University and a Bachelor of Science degree in Mechanical Engineering from Drexel University. He is the author of more than 30 patents and more than 50 published technical articles.
Dr. Winter is on the advisory board of the Engineering Schools at Embry Riddle Aeronautical University and is an adjunct full professor in Systems Engineering at Columbia University. He has served on the National Research Council Board of Assessment of the National Academies, on several committees of the American Institute of Aeronautics & Astronautics (AIAA), and as chairman of the Aerospace Industry Association (AIA) Technical Operations Council.