NISHEETH K. VISHNOI
RESEARCH
My work spans various areas of Mathematics, Theoretical Computer Science, Optimization, and Artificial Intelligence. I aim to tackle some of the most pressing and complex problems at the intersection of computation and society.
At Yale, I co-founded the Computation and Society Initiative.
AFFILIATIONS CURRENT A. Bartlett Giamatti Professor of Computer Science, Yale ADJUNCT IIT Kanpur PAST IIT Bombay Georgia Tech IBM Research UC Berkeley OPEN POSITIONS
Several open positions Ph.D./Postdoc positions in theoretical computer science, machine learning, optimization, and algorithmic fairness are available. Please get in touch directly if you would be interested.
PUBLICATIONS RESEARCH ON ALGORITHMIC BIAS BOOKS and SURVEYS Algorithms for Convex Optimization BLOGS Algorithms, Nature, and Society RECENT SERVICE and HONORS Elected Fellow of AMS, 2025 PC Chair, FOCS 2021 Co-organizer of Simons Semester on Geometric Methods for Optimization and Sampling, Fall 2021 PC of India Science Festival, 2020-2021 Elected Fellow of ACM, 2019 Best Technical Paper Award at ACM FAT*, 2019 MEDIA and OUTREACH Times of India interview on AI and bias. PBS Nova article on our work on reducing polarization Panelist in ICRC/IIT Delhi Initiative on Humanitarian Policy and Technology, 2019 Round Table on the Governance of Decision Making Algorithms, IRGC, 2018 Round Table on AI and Global Health at Wilton Park, 2018 Our voting framework to be used in Valais elections, 2018 Panelist in the Responsible Finance and Investment Summit, 2018 Philanthropy Impact Roundtable on AI, 2018 A demo of our algorithms to control bias in AI (work in progress) On our work on controlling polarization [video] On our algorithms to control bias An interview on Artificial Intelligence An interview on Algorithmic Bias A journalist's report of the workshop Computation, Science and Society that I co-organized CONTACT EMAIL nisheeth (dot) vishnoi (@) gmail (dot) com TWITTER Follow @NisheethVishnoi
I devise methods aimed at mitigating biases and ensuring privacy within algorithms (broadly interpreted), with a particular focus on understanding the complex interactions between algorithms, human behavior, and societal norms. I am developing techniques to enhance the capabilities of diffusion models, enabling them to learn probability distributions over data that is constrained to geometric spaces. I am interested in developing frameworks to understand and assess the impact of generative AI tools such as Large Language Models on jobs and work.
I am co-PI of an NSF funded AI Institute: The Institute for Learning-enabled Optimization at Scale
At Yale, I am affiliated to the Cowles Foundation for Research in Economics, the Institution for Social and Policy Studies, and the Thurman Arnold Project at the Yale School of Management.
I served on the Yale AI Task Force.
My Curriculum Vitae
CNRS Microsoft Research Simons Inst. EPFL IIT Delhi
ICTS Bangalore IIT Goa Google Research
Lx=b
Optimization, Sampling, Lie Theory
Hamiltonian Monte Carlo
Geodesic Convex Optimization
Faster Algorithms via Approximation Theory
Real Stable Polynomials and their Applications to TCS
Evolution