Events - February 2024

Please note: This seminar will take place in DC 1304.

Luke Schaeffer, QuICS Hartree Postdoctoral Fellow
Joint Center for Quantum Information and Computer Science, University of Maryland

Please note: This seminar will take place in DC 1304.

Yuanhao Wei, Postdoctoral Researcher
Computer Science and Artificial Intelligence Laboratory, MIT

Concurrent programming is becoming increasingly important as systems are scaling up by increasing the number of processors rather than the speed of a single processor. However, concurrent programming can be very difficult and error-prone.

Please note: This master’s thesis presentaton will take place in DC 1304.

Kerem Akillioglu, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor M. Tamer Özsu

Please note: This master’s thesis presentation will take place online.

Zhenbo Li, Master’s candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Bin Ma, Yang Lu

Please note: This seminar will take place in DC 1304.

Jim Shaw, PhD candidate
Department of Mathematics, University of Toronto

DNA is life’s instruction manual, but mathematically, DNA is simply a string over an alphabet of four letters. DNA can now easily be read into a computer, and the associated string-processing algorithms are being leveraged by biologists for exciting discoveries. However, this has created a flood of data in the petabytes, requiring modern and faster tools.

Please note: This seminar will take place in DC 1304.

Andrew Ilyas, PhD candidate
Department of Electrical Engineering and Computer Science, MIT

Please note: This master’s thesis presentation will take place online.

Connor Stewart, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Krzysztof Czarnecki

Please note: This PhD seminar will take place in DC 3317.

Edward Lee, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Ondřej Lhoták

Reasoning about the use of external resources is an important aspect of many practical applications. Effect systems enable tracking such information in types, but at the cost of complicating signatures of common functions. Capabilities coupled with escape analysis offer safety and natural signatures, but are often overly coarse grained and restrictive.

Please note: This seminar will take place in DC 1304.

Dinghuai Zhang, PhD candidate
Mila

Advancements in scientific discovery have always been at the forefront of human endeavor, particularly in complex domains such as molecule synthesis. The intrinsic challenges in these fields stem from two main factors: the vast and combinatorially complex high-dimensional search spaces, and the costly evaluation of scientific hypotheses. Therefore, leveraging machine learning offers a promising avenue to expedite the scientific discovery process.

Please note: This talk will take place in DC 1304 and online.

Alex Zhang, GFW Report

Please note: This PhD seminar will take place online.

Kira Aveline Selby, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Pascal Poupart