Christian Janos Lebeda, PhD candidate
Basic Algorithms Research Copenhagen
Algorithms Group, IT University of Copenhagen
Jason Hartford, Postdoctoral researcher
Mila, Quebec
Causal inference provides a powerful suite of tools through which economists, epidemiologists, and the social sciences understand the world. But textbook causal inference methods limit the questions that scientists can ask because they rely on classical statistical estimation techniques.
Johann Wentzel, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Daniel Vogel
Sunoo Park
Postdoctoral Fellow, Columbia University
Visiting Fellow, Columbia Law School
My research focuses on the security, privacy, and transparency of technologies in societal and legal context. My talk will focus on three of my recent works in this space, relating to (1) preventing exploitation of stolen email data, (2) enhancing accountability in electronic surveillance, and (3) legal risks faced by security researchers.
Hsin-Yuan (Robert) Huang, PhD candidate
Computing and Mathematical Sciences, California Institute of Technology
Khaled Ammar, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Tamer Özsu, Semih Salihoglu
Pengyu Nie, PhD candidate
Department of Electrical and Computer Engineering
University of Texas at Austin
Yen-Ting (Allen) Yeh, PhD candidate
David R. Cheriton School of Computer Science
Wenhan (Cosmos) Zhu, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Michael Godfrey
Tanvir Ahmed Khan, PhD candidate
Computer Science and Engineering, University of Michigan
Billions of people rely on web services powered by data centers, where critical applications run 24/7. Unfortunately, data center applications are extremely inefficient, wasting more than 60% of all processor cycles, and causing millions of dollars in operational expenses and energy costs.