Complementary to the nine new faculty added this year to the University of Chicago Department of Computer Science, the Data Science Institute is pleased to announce 6 additional new faculty members joining us for the 2023 fall.
Five of the six new faculty members share joint appointments with the Department of Computer Science and share their interdisciplinary knowledge across these highly related domains. As experts in areas like machine learning, human-computer interaction, and privacy and security, the new faculty will contribute to the rapid expansion of research here at the University of Chicago.
Ari Holtzman is an incoming Assistant Professor for the Summer of 2024. His research interests have spanned everything from dialogue, including winning the first Amazon Alexa Prize in 2017, to fundamental research on text generation, such as proposing Nucleus Sampling, a decoding algorithm used broadly in deployed systems such as the OpenAI API as well as in academic research. Ari completed an interdisciplinary degree at NYU combining Computer Science and the Philosophy of Language. He will receive his PhD from the University of Washington.
Frederic Koehler was previously a fellow at Stanford University where he worked on computational learning theory and related topics, such as optimization and probability theory. He was previously a research fellow for UC Berkeley’s Simons Institute in the Program on Computational Complexity of Statistical Inference. He received his PhD in Mathematics and Statistics from MIT, and before that completed his undergraduate degree in Mathematics at Princeton University. Frederic’s current research interests include statistical physics, high-dimensional statistics, and learning and inference in graphical models.
Mina Lee is an incoming Assistant Professor for the Summer of 2024. Her research goal is to design and evaluate language models to enhance our productivity and creativity and understand how these models change the way we write. She has built various writing assistants, including an autocomplete system, a contextual thesaurus system, and a creative story-writing system. In addition, she has developed a new framework to evaluate language models based on their ability to interact with humans and augment human capabilities. She was named one of MIT Technology Review’s Korean Innovators under 35 in 2022, and her work has been published in top-tier venues in natural language processing (e.g., ACL and NAACL), machine learning (e.g., NeurIPS), and human-computer interaction (e.g., CHI). Her recent work on human-AI collaborative writing received an Honorable Mention Award at CHI 2022 and was featured in various media outlets, including The Economist. Mina received her PhD from Stanford University in 2023.
Bo Li shares a dual appointment as an Associate Professor in the Computer Science Department. She is also on the advisory board of the Center for Artificial Intelligence Innovation at Illinois, and a member of the Information Trust Institute. She is affiliated with several research centers aiming to broaden the research collaboration and bridge different communities, such as the Advanced Digital Science Center, the Center for Cognitive Computing Systems Research, and the Quantum Information Science and Technology Center. Her research focuses on trustworthy machine learning, with an emphasis on robustness, privacy, generalization, and their interconnections. Bo believes that closing today’s trustworthiness gap in ML requires us to tackle these grappled problems in a holistic framework, driven by fundamental research focusing on not only each problem but also their underlying interactions.
Tian Li will be joining the Department as an Assistant Professor in the Summer of 2024. Her research interests are in distributed optimization, federated learning, and trustworthy ML. Tian is receiving her PhD from Carnegie Mellon University. Prior to CMU, she received her undergraduate degrees in Computer Science and Economics from Peking University. She received the Best Paper Award at the ICLR Workshop on Security and Safety in Machine Learning Systems, was invited to participate in the EECS Rising Stars Workshop, and was recognized as a Rising Star in Machine Learning/Data Science by multiple institutions.
Ce Zhang is an incoming Associate Professor for the Summer of 2024. He is currently an Associate Professor of Computer Science at ETH Zurich. Before joining the department he will spend his time as the CTO of Together, building a decentralized cloud for artificial intelligence. His research looks at the fundamental tension between data, model, computation and infrastructure, with the final goal of democratizing machine learning and artificial intelligence. His current research focuses on building next-generation machine learning platforms and systems that are data-centric, human-centric, and declaratively scalable. Before joining ETH, Ce finished his PhD at the University of Wisconsin-Madison and spent another year as a postdoctoral researcher at Stanford, both advised by Christopher Ré. His work has received recognitions such as the SIGMOD Best Paper Award, SIGMOD Research Highlight Award, Google Focused Research Award, an ERC grant, and has been featured and reported by Science, Nature, the Communications of the ACM, and various media outlets such as Atlantic, WIRED, Quanta Magazine, etc. He also currently serves as the co-Editors-in-Chief of DMLR, a new member of the JMLR family focusing on data-centric machine learning research.