Feb. 15, 2023
Eshan Chattopadhyay, assistant professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science is one of five Cornell faculty who won 2023 Sloan Research Fellowships from the Alfred P. Sloan Foundation. Chenhao Tan, Ph.D. ’16, assistant professor of computer science and data science at the University of Chicago, also received the honor.
The fellowships, established in 1955, support early-career faculty members’ original research and education related to science, technology, mathematics and economics.
The two are among 126 researchers in the United States and Canada who this year have received two-year, $75,000 fellowships to advance their work.
“Sloan Research Fellows are shining examples of innovative and impactful research,” said Adam F. Falk, president of the Alfred P. Sloan Foundation. “We are thrilled to support their groundbreaking work and we look forward to following their continued success.”
Chattopadhyay’s main research area is computational complexity theory, a discipline within theoretical computer science that tries to understand the intrinsic hardness – or ease – of problems with respect to computational resources. A particular focus has been understanding the role of random bits in computation, a resource that is as valuable as compute time or memory.
His research has made advances in finding efficient ways to generate truly random bits that are crucial for real-world applications – such as secure transactions over the internet – and understanding how to come up with generic ways of reducing the amount of randomness required in algorithms. Future work will explore the intrinsic need of randomness for efficient algorithm design.
Tan, who joined UChicago CS and the Data Science Institute in January 2021, studies human-centered artificial intelligence – AI systems that work with humans on important decision-making tasks in medicine, law, and other fields. His research in the Chicago Human+AI (CHAI) Lab blends data science, natural language processing, machine learning, human-computer interaction, and computational social science to develop and evaluate tools for human-AI collaboration.