Elias Bareinboim, Brian Smith, and Shuran Song join the department.
Elias Bareinboim Associate Professor, Computer Science Director, Causal Artificial Intelligence Lab Member, Data Science Institute PhD, Computer Science, University of California, Los Angeles (UCLA), 2014 BS & MS, Computer Science, Federal University of Rio de Janeiro (UFRJ), 2007
Elias Bareinboim’s research focuses on causal and counterfactual inference and its application to data-driven fields in the health and social sciences as well as artificial intelligence and machine learning. His work was the first to propose a general solution to the problem of “causal data fusion,” providing practical methods for combining datasets generated under heterogeneous experimental conditions and plagued with various biases. This theory and methods constitute an integral part of the discipline called “causal data science,” which is a principled and systematic way of performing data analysis with the goal of inferring cause and effect relationships.
More recently, Bareinboim has been investigating how causal inference can help to improve decision-making in complex systems (including classic reinforcement learning settings), and also how to construct human-friendly explanations for large-scale societal problems, including fairness analysis in automated systems.
Bareinboim is the recipient of the NSF Faculty Early Career Development (CAREER) Award, IEEE AI’s 10 to Watch, and a number of best paper awards. Later this year, he will be teaching a causal inference class intended to train the next generation of causal inference researchers and data scientists. Bareinboim directs the Causal Artificial Intelligence Lab, which currently has open positions for Ph.D. students and Postdoctoral scholars.
Brian Smith Assistant Professor PhD, Computer Science, Columbia University, 2018 MPhil, Computer Science, Columbia University, 2015 MS, Computer Science, Columbia University, 2011 BS, Computer Science, Columbia University, 2009
Brian Smith’s interests lie in human-computer interaction (HCI) and creating computers that can help people better experience the world. His past research on video games for the visually impaired was featured in Quartz, TechCrunch, the Huffington Post, among others.
Smith has spent the last year at Snap Research (Snap is best known for Snapchat) developing new concepts in human–computer interaction (HCI), games, social computing, and augmented reality. He will continue to work on projects with Snap while at Columbia.
He comes back to the department as an assistant professor and is set to teach a class on user interface design this fall. That class had a waitlist of 235 students hoping to be part of the class. Smith shared that back when he was a student, there were only 35 students in the class he was enrolled in. “There is definitely more interest in computer science now compared to even five years ago,” he said.
Smith hopes to start a HCI group and is looking for PhD students. He encourages students from underrepresented groups to apply.
Shuran Song Assistant Professor PhD, Computer Science, Princeton University, 2018 MS, Computer Science, Princeton University, 2015 BEng, Computer Engineering, Hong Kong University of Science and Technology, 2013
Shuran Song is interested in artificial intelligence with an emphasis on computer vision and robotics. The goal of her research is to enable machines to perceive and understand their environment in a way that allows them to intelligently operate and assist people in the physical world.
Previously, Song worked at Google Brain Robotics as a researcher and developed TossingBot, a robot that learns to how to accurately throw arbitrary objects through self-supervised learning.
This fall, she is teaching a seminar class on robot learning. Song currently has one PhD student who is working on active perception — enabling robots to learn from their interactions with the physical world, and autonomously acquire the perception and manipulation skills necessary to execute complex tasks. She is looking for more students who are interested in machine learning for vision and robotics.
The ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining.
FREP awards grants to faculty members in support of research to enhance people’s lives by improving the internet. FREP was founded in 2012 to foster cutting-edge collaborations between scientists in academic settings and those at Yahoo Research.
Researchers from around the country gathered at Columbia Engineering this past weekend for a three-day event honoring four decades of ground-breaking research by Prof. Christos Papadimitriou. The conference, which organizers dubbed “PapaFest,” included individual speakers, panel discussions, social events, and even a rock band.
The diverse cohort come from the various groups within the department. They are a mix of those new to Columbia and students who have received fellowships for the year.
J.P. Morgan 2019 AI Research PhD Fellowship Awards The inaugural award supports researchers who have the skills and imagination to potentially transform the way we live and work.
Ana-Andreaa Stoica A third-year PhD student, Ana-Andreaa Stoica works with Augustin Chaintreau on social networks and algorithmic fairness. Her work focuses on mathematical models, data analysis, and policy implications for algorithm design in social networks. Stoica graduated from Princeton in 2016 with a bachelor’s degree in Mathematics and certificates in Computing and Applied Mathematics.
2019 Google PhD Fellowship in Algorithms, Optimizations, and Markets The program recognizes outstanding graduate students doing exceptional work in computer science and related research areas.
Peilin Zhong A member of the Theory Group, Peilin Zhong is a third-year PhD student who is particularly interested in parallel graph algorithms, generative models, and large-scale data computational models. His goal is to design new algorithms for large-scale computational models that have more impact in machine learning, data mining, and can be used in practice. Zhong was part of the Yao Class at Tsinghua University and graduated in 2016 with a bachelor’s degree in engineering.
National Defense Science and Engineering Graduate (NDSEG) Fellowship The NDSEG is a highly competitive, portable fellowship that is awarded to U.S. citizens and nationals who intend to pursue a doctoral degree in one of fifteen supported disciplines.
Gabriel Ryan Gabriel Ryan is a second-year PhD student whose current research involves using deep learning to construct logical formulas for program verification and synthesis. Prior to joining Columbia for graduate studies, he worked as a software engineer developing systems for data security, robotic 3D mapping and localization, and ballistic missile defense. Ryan graduated from Swarthmore College with a B.S. Engineering and B.A. Computer Science dual degree in 2013.
Ministry of Education of Taiwan – Government Scholarship to Study Abroad The scholarship is awarded to Taiwanese students studying abroad with exceptional academic record and potential in their research areas.
Jen-Shuo Liu Working in professor Steven Feiner’s Computer Graphics and User Interfaces Laboratory, third-year PhD student Jen-Shuo Liu’s research focus is user interface design for augmented reality and virtual reality. Liu has gained recognition for his work including an NYC Media Lab award for an augmented reality project. He graduated from National Taiwan University with an M.S. degree in Communication Engineering in 2016 .
The Belgian American Educational Foundation (BAEF) The BAEF fosters the higher education of deserving Belgians and Americans through its exchange fellowship program.
Basile Van Hoorick As an MS student, Basile Van Hoorick’s interests include computer vision, machine learning, and software engineering. While at Columbia, he hopes to work as a research and/or teaching assistant. Van Hoorick was a finalist in the Flemish Mathematics Olympiad (a national mathematics competition) in 2014 and studied electrical engineering at Ghent University in Belgium where he graduated summa cum laude in July 2019.
SEAS Fellowships Columbia School of Engineering and Applied Sciences established the Presidential and SEAS fellowships to recruit outstanding students from around the world to pursue graduate studies at the school.
Xi Chen As part of her research project, Xi Chen is trying to predict depression based on human mobility trajectory. Her interests lie in social networks and machine learning and she is a second-year PhD student working with Augustin Chaintreau. Chen graduated in 2018 with a degree in computer science and mathematics from Carleton College.
Shunhua Jiang Shunhua Jiang is a first-year PhD student with the Theory Group, under the guidance of Omri Weinstein and Alex Andoni. Her research interests range from data structures, lower bounds, to algorithms. An alum of Tsinghua University, Jiang graduated in 2015 with a degree in computer science.
Eric Neyman Eric Neyman is a first-year PhD student with the Theory Group under the supervision of professors Tim Roughgarden and Rocco Servedio. He looks forward to exploring the various disciplines of theoretical computer science. Neyman has earned three honorable mentions in the Putnam mathematical competition and graduated summa cum laude from Princeton University in 2019 with a degree in mathematics.
Chang Xiao Chang Xiao is a fourth-year PhD student in computer science who works with professor Changxi Zheng. His research focuses on building human-computer interaction systems using computational methods. He has developed methods in a range of applications and his research has attracted public interest, including media coverage from CNN, IEEE Spectrum, etc. Chang received a BS degree in computer science from Zhejiang University in 2016 and is a recipient of the Snap Fellowship in 2019.
Hengjie Zhang Hengjie Zhang’s research interests are graph theory, algorithms, and data structure. He will join the theory group as a first-year PhD student working with Alexandr Andoni and Omri Weinstein. He won a gold medal in the International Olympiad in Informatics and a Yao Award Recognition Prize from Tsinghua University where he graduated with a degree in engineering in 2019.
Joseph Zuckerman With the system-level design group, Joseph Zuckerman will work on heterogeneous system-on-chip architectures. He is a first-year PhD student interested in application-specific architectures, the integration of accelerators, and hardware design methodologies. Zuckerman completed a B.S. in Electrical Engineering from Harvard University in 2019, with a focus on hardware architectures for machine learning applications.
The AI4All 2019 class with program organizers on a field trip to Princeton University.
They could have been at the beach enjoying the summer. Instead, high school students gathered from across New York City and New Jersey for the AI4All program hosted by the Columbia community. The students came to learn about artificial intelligence (AI) but this program had a special twist – computer science (CS) and social work concepts were combined for a deeper, more meaningful look at AI.
“We created a space for young people to think critically about the social implications of artificial intelligence for the communities that they live in,” said Desmond Patton, the program co-director and associate professor of the School of Social Work. “We wanted them to understand how things like race, power, privilege and oppression can be baked into algorithms and their adverse effects on communities.”
The AI4All 2019 class with program organizers on a field trip to LinkedIn.
The program participants, composed of 9th, 10th and 11th graders, are from racial and ethnic groups underrepresented in AI: Black, Hispanic, and Asian. Girls as well as youth from lower-income backgrounds were particularly encouraged to apply. For three weeks the students attended lectures, went on field trips to visit local companies (LinkedIn and Samsung) involved in the program, and visited other AI4All programs, like at Princeton University. Their work culminated in a final project which they presented to their classmates, mentors, and industry professionals.
“I believe that it is important to bring more ethics to AI,” said Augustin Chaintreau, the program co-director and a CS assistant professor. He sees ethics integrated into technical concepts and taught at the same time. Instead of learning about the social consequences and fixing it after, to solve an issue. Shared Chaintreau, “It shouldn’t be thought about just in passing but as a central part of why this is a tool and its implications.”
An interdisciplinary approach to AI was even part of how the classes were structured. Technical CS concepts, such as machine learning and Python, were taught in the morning by professors and student volunteers. While in the afternoon, guest speakers came to talk about their perspective to the day’s lesson. So, on the same day, students learned about supervised and unsupervised learning, and in the afternoon, someone who was formerly incarcerated described how the criminal policing that survey people on social media had a role in making a case against them.
Genesis Lopez (center, in black) in class.
“We were learning college courses meant to be taught in a month but for us it was just a couple of weeks and that was really impressive,” said Genesis Lopez, who is part of the robotics team at her school. Lopez loves robotics but works more on the mechanical side. She goes back to the team knowing how to use Python and is confident she can step up and code if needed. Continued Lopez, “I learned a lot but my favorite part was the people, we became a family.”
Text IQ started as co-founder Apoorv Agarwal’s (PhD ’14) Columbia thesis project titled “Social Network Extraction From Text.” The algorithm he built was able to read a novel, like Jane Austen’s “Emma,” for example, and understand the social hierarchy and interactions between characters.
Dean Boyce's statement on amicus brief filed by President Bollinger
President Bollinger announced that Columbia University along with many other academic institutions (sixteen, including all Ivy League universities) filed an amicus brief in the U.S. District Court for the Eastern District of New York challenging the Executive Order regarding immigrants from seven designated countries and refugees. Among other things, the brief asserts that “safety and security concerns can be addressed in a manner that is consistent with the values America has always stood for, including the free flow of ideas and people across borders and the welcoming of immigrants to our universities.”
This recent action provides a moment for us to collectively reflect on our community within Columbia Engineering and the importance of our commitment to maintaining an open and welcoming community for all students, faculty, researchers and administrative staff. As a School of Engineering and Applied Science, we are fortunate to attract students and faculty from diverse backgrounds, from across the country, and from around the world. It is a great benefit to be able to gather engineers and scientists of so many different perspectives and talents – all with a commitment to learning, a focus on pushing the frontiers of knowledge and discovery, and with a passion for translating our work to impact humanity.
I am proud of our community, and wish to take this opportunity to reinforce our collective commitment to maintaining an open and collegial environment. We are fortunate to have the privilege to learn from one another, and to study, work, and live together in such a dynamic and vibrant place as Columbia.
Sincerely,
Mary C. Boyce
Dean of Engineering
Morris A. and Alma Schapiro Professor
Add to GMail