Seminar

Please note: This seminar will be given online.

Krikamol Muandet
Research Group Leader, Empirical Inference Department
Max Planck Institute for Intelligent Systems

Society is made up of a set of diverse individuals, demographic groups, and institutions. Learning and deploying algorithmic models across these heterogeneous environments face a set of various trade-offs. In order to develop reliable machine learning algorithms that can interact successfully with the real world, it is necessary to deal with such heterogeneity.

Please note: This seminar will be given online.

Sihang Liu
Department of Computer Science, University of Virginia

Please note: This seminar will be given online.

Ningning Xie, Research Associate
Department of Computer Science and Technology
University of Cambridge

Please note: This seminar will be given online.

Amirali Aghazadeh, Postdoctoral researcher
Department of Electrical Engineering and Computer Sciences
University of California, Berkeley

Please note: This seminar will be given online.

Hong Zhang, Postdoctoral Scholar
Department of Electrical Engineering and Computer Sciences
University of California, Berkeley

Please note: This seminar will be given online.

Eugene Ndiaye, Tennenbaum President’s Postdoctoral Fellow
H. Milton Stewart School of Industrial and Systems Engineering
Georgia Institute of Technology

Please note: This seminar will be given online.

Octavian Ganea, Postdoctoral researcher
Computer Science & Artificial Intelligence Laboratory, MIT

Please note: This seminar will be given online.

Xuehai Qian
Department of Electrical and Computer Engineering, University of Southern California

Please note: This PhD seminar will be given online.

Sangho Suh, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Edith Law

Please note: This PhD seminar will be given online.

Daniel Gabric, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jeffrey Shallit