CS Professors Awarded Test of Time Award at ICML’23
Richard Zemel and Toniann Pitassi were recognized for their paper, “Learning Fair Representations,” which established the subfield of machine learning–machine learning and fairness.
Richard Zemel and Toniann Pitassi were recognized for their paper, “Learning Fair Representations,” which established the subfield of machine learning–machine learning and fairness.
Professor Emeritus Alfred Aho and Professor Toniann Pitassi are among the Columbians recognized for their distinguished and continuing achievements in original research.
Josh Alman, Toniann Pitassi, and Richard Zemel join the department. They will facilitate research and learning in CS theory, machine learning, and artificial intelligence.
Josh Alman
Assistant Professor
PhD Computer Science, Massachusetts Institute of Technology 2019
MS Computer Science, Stanford University 2016
BS Mathematics, Massachusetts Institute of Technology 2014
Josh Alman is a theoretical computer scientist who works broadly throughout algorithm design and complexity theory. His current research focuses on algorithms for fundamental algebraic problems. In particular, he is interested in how quickly one can multiply matrices and compute important linear transforms like Fourier transforms, and how to apply algebraic tools like these to new problems throughout computer science.
Alman joins the Theory Group and looks forward to working with students who have a background in theoretical computer science or mathematics on various projects. This Fall, he will teach a graduate class on algebraic techniques in algorithms and complexity.
Toniann Pitassi
Jeffrey L. and Brenda Bleustein Professor of Engineering
PhD Computer Science, University of Toronto 1992
MS Computer Science, Pennsylvania State University 1985
BS Chemistry & Computer Science, Pennsylvania State University 1985
Pitassi’s research area is computational complexity: what are the inherent limitations on the resources (time, space, randomness) required to solve fundamental computational problems? An important direction aimed at resolving the ultimate question of this type, the P versus NP question, is propositional proof complexity, which studies the difficulty of proving tautological statements in standard proof systems. She has also worked extensively in communication complexity which studies how much information must be communicated between two or more players in order to compute a joint function of their inputs. Her other research interests lie in the foundations of machine learning, particularly in the areas of privacy, fairness, and reproducibility.
Previously Pitassi was the Bell Research Chair at the University of Toronto, a Canadian Institute for Advanced Research research chair, and a research lead at the Schwartz-Reisman Institute for Technology and Society. She currently holds a five-year appointment as visiting professor at the Institute for Advanced Study. Pitassi is the 2021 EATCS Award recipient and was an invited speaker at the International Congress of Mathematicians
At Columbia, Pitassi joins the department’s Theory Group and the Machine Learning Group. She is excited to collaborate with new colleagues and graduate students at Columbia and to explore New York. Her hobbies and outside interests are constantly changing with the latest being stained glass.
Richard Zemel
Professor of Computer Science
PhD Computer Science, University of Toronto 1994
MS Computer Science, University of Toronto 1989
BA History and Science, Harvard University 1984
Richard Zemel’s research focuses on machine learning and artificial intelligence. He is also interested in natural intelligence, including neuroscience and cognitive science. His recent research targets learning with few labels and creating robust and controllable machine learning systems, which can transfer to a variety of tasks and domains. He also has a strong interest in algorithmic fairness.
Previously, Zemel was the NSERC Industrial Research Chair in Machine Learning at the University of Toronto, and co-founded and served as the Research Director of the Vector Institute for Artificial Intelligence. He is the recipient of an ONR Young Investigator Award, an NVIDIA Pioneer of AI Award, and is a Fellow of the Canadian Institute for Advanced Research.
This Fall, he will teach a course on Neural Networks and Deep Learning and will teach a seminar class on machine learning in the Spring term. Zemmel is looking for PhD students who are interested in machine learning to join his research group. In his spare time, he likes sports such as hockey, squash and biking, and eating.
The Distinguished Lecture series brings computer scientists to Columbia to discuss current issues and research that are affecting their particular fields. This year, eight experts covered topics from machine learning, cryptography, privacy, algorithms, ethics, and computer vision.
Below are a couple of the lectures from prominent faculty from universities across the country.
Find open faculty positions here.
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