Four Columbians Elected to the National Academy of Sciences
Computer scientists Alfred Aho and Toniann Pitassi, mathematician Michael Harris, and sociologist Mario Small join this year’s class of new members.
May 04, 2022
Four Columbia professors—Alfred Aho, Michael Harris, Toniann Pitassi, and Mario Small—are among the 120 U.S.-based scholars to be elected as members this year to the National Academy of Sciences for their distinguished and continuing achievements in original research.
Alfred V. Aho, the Lawrence Gussman Professor Emeritus of computer science, is known for his broad and fundamental contributions in algorithm design and analysis, and programming languages and compilers, which translate human-written code into a form that machines can execute. With his longtime collaborator Jeffrey Ullman (SEAS’63), a professor emeritus at Stanford, Aho received computing’s highest honor, the Turing Award, in 2020. Before joining Columbia Engineering in 1995, Aho spent more than three decades at Bell Labs, helping to run the lab that invented UNIX, C, and C++.
Michael Harris, a professor of mathematics, works in number theory, one of the oldest branches of mathematics, which focuses on the often-subtle properties of solutions of equations in whole numbers. His work has centered on the role of geometric structures and properties of symmetry in solving problems in number theory. He is the author of the 2015 book, Mathematics Without Apologies, and the newsletter, Silicon Reckoner, both of which celebrate the humanity embedded in a discipline sometimes viewed as robotic or two-dimensional.
Toniann Pitassi, Jeffrey L. and Brenda Bleustein Professor of Engineering, studies computational complexity, or the limitations that time, space, and randomness impose on computational problems. She is an expert in communication complexity, which explores how much information two or more players must swap to compute a joint function of their inputs, as well as proof complexity, the study of inherent limitations of computation and proofs. Her research also focuses on timely topics in machine learning: privacy, fairness, and reproducibility.
Mario L. Small, Quetelet Professor of Social Science, is an expert on social inequality, social networks, and field research methods. His most recent books, Someone To Talk To and Personal Networks, examine when and how people turn to their networks to meet their needs. He is currently studying the relationship between networks and decision-making, the ability of large-scale data to answer critical questions about urban inequality, and the relation between qualitative and quantitative methods.