Cornell Bowers College of Computing and Information Science
Color photo collage of new faculty members joining Bowers CIS


Cornell Bowers CIS welcomes 6 new faculty

August 30, 2022

Six new faculty members have joined the Cornell Ann S. Bowers College of Computing and Information Science community this fall.

The incoming faculty are experts in a broad range of areas, including robotics, artificial intelligence, digital fabrication, public health, and population genetics. Their research efforts will advance the goal of Cornell Bowers CIS to improve the world by creating an equitable, sustainable future for all.

Cornell Bowers CIS is investing heavily in expanding its faculty to meet the growing demand for computer and information science education, with a goal to increase by 50% in the next few years. The scale of this growth will enable the college to foster research excellence, develop core and emerging fields, and bring about new opportunities for cross-disciplinary and universitywide collaboration.

The following faculty have joined the college community:

Sanjiban Choudhury, Assistant Professor, Computer Science

Choudhury’s research aims to enable robots to work seamlessly alongside human partners to accomplish everyday tasks. He thinks that for robots to acquire skills to work with people, they must solve the problem of interaction and imitation. Interactive imitation learning provides a scalable way to implicitly program robots through human demonstrations, interventions, or preferences. To this end, his work focuses on imitation learning, decision making, and human-robot interaction. Much of his previous research has been deployed on real-world robot systems — full-scale helicopters, self-driving cars, and mobile manipulators. He is currently a part-time researcher at Aurora, a self-driving technology company. He received his Ph.D. in robotics at Carnegie Mellon University and was a postdoctoral fellow at the University of Washington CSE.

Jaehee Kim, Assistant Professor, Computational Biology

Kim’s lab focuses on the general fields of population genetics and evolutionary biology. Her lab is interested in computational problems relevant to understanding evolutionary processes and population dynamics, and in development and application of statistical methods for inference from genetic data. In addition to answering fundamental questions in evolution, she applies these approaches to solve questions with biomedical, legal, and social implications in the areas of genetic epidemiology, conservation genomics, and forensic genetics. Kim received her Ph.D. in physics at Stanford University and was a postdoctoral research fellow in biology, also at Stanford.

Allison Koenecke, Assistant Professor, Information Science

Koenecke’s research interests lie broadly at the intersection of economics and computer science. She uses computational tools, such as machine learning and causal inference, to study inequity in algorithmic systems, spanning domains from automated speech-to-text systems to online advertisements for welfare benefits. She received her Ph.D. from the Stanford Institute for Computational & Mathematical Engineering and was a postdoctoral researcher at Microsoft Research New England in the Machine Learning and Statistics group.

Ian Lundberg, Assistant Professor, Information Science

Lundberg’s research explores how computational tools can change the way we study inequality. Trained as a sociologist, Lundberg enjoys collaborating, not only with other social scientists but also with computer scientists and data scientists. He aims to help social scientists ask questions about economic inequality in new ways, using precise language that can point toward algorithmic tools for estimation. His research also helps scientists who develop algorithms to translate them back to well-defined research questions. He received a Ph.D. in sociology and social policy at Princeton University and was recently a postdoctoral scholar in the Department of Sociology and the California Center for Population Research at UCLA.

Thijs Roumen, Assistant Professor, Information Science, Cornell Tech

Roumen conducts research on human-computer interaction with a focus on digital fabrication: using computers to control physical matter. As director of the Matter of Tech lab, he believes that manipulating physical matter is the next big paradigm in personal computing. He aims to develop this future of personal fabrication, which began within industry and the “maker scene,” by rethinking the shape and use context of fabrication machines, the process of creating and modifying models for fabrication, and education around digital fabrication. Previously, Roumen conducted his doctoral studies in human-computer interaction at the Hasso Plattner Institute (HPI) and was a research assistant at the National University of Singapore (NUS).  

Angelique Taylor, Assistant Professor, Information Science, Cornell Tech

Taylor directs the Artificial Intelligence & Robotics Lab (AIR Lab), which focuses on research in the field of human-robot interaction. Her research lies at the intersection of robotics, computer vision, and artificial intelligence. Specifically, she develops intelligent systems that enable robots to interact and work with groups of people in safety-critical environments. These systems are realized through community engagement with stakeholders to design multi-robot, robot vision, and AR/VR systems. Prior to joining Cornell Tech, Taylor was a Visiting Research Scientist at Meta Reality Labs Research. Taylor earned her Ph.D. in computer science and engineering from the University of California, San Diego, where she focused on building perception and decision-making systems for mobile robots that support teams in healthcare.