Arun Jambulapati, Postdoctoral Researcher
Computer Science and Engineering, University of Michigan
Alex Zhang, GFW Report
Ruixue Zhang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ming Li
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.
Nandan Thakur, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jimmy Lin
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.
Ajay Singh, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Trevor Brown
In this presentation, we introduce Neutralization Based Reclamation (NBR), a novel technique that helps concurrent data structures with non-synchronized traversals to safely free objects. Additionally, we explore optimization possibilities, examining the efficiency of the technique.
Connor Stewart, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Krzysztof Czarnecki
Siddhartha Sahu, PhD candidate
David. R. Cheriton School of Computer Science
Supervisor: Professor Semih Salihoğlu
Andrew Ilyas, PhD candidate
Department of Electrical Engineering and Computer Science, MIT