PhD Seminar • Bioinformatics — Modeling Transitions of Protein Elastic Network Models and the Rank 3 Positive Semidefinite Matrix Manifold
Xiao-Bo Li, PhD candidate
David R. Cheriton School of Computer Science
Xiao-Bo Li, PhD candidate
David R. Cheriton School of Computer Science
Marijn Heule, Research Assistant Professor
University of Texas at Austin
Progress in satisfiability (SAT) solving has enabled answering long-standing open questions in mathematics completely automatically, resulting in clever though potentially gigantic proofs. We illustrate the success of this approach by presenting the solution of the Boolean Pythagorean triples problem. We also produced and validated a proof of the solution, which has been called the "largest math proof ever."
Michael Cormier, PhD candidate
David R. Cheriton School of Computer Science
Edward Zulkoski, PhD candidate
David R. Cheriton School of Computer Science

Saman Barghi, PhD candidate
David R. Cheriton School of Computer Science
Yifan Zhang, Master’s candidate
David R. Cheriton School of Computer Science
| Dates | Times |
|---|---|
| Friday, June 22, 2018 | 5:30 p.m. to 8:30 p.m. |
| Saturday, June 23, 2018 | 10:00 a.m. to 5:00 p.m. |
| Sunday, June 24, 2018 | 10:00 a.m. |
Babar Naveed Memon, Master’s candidate
David R. Cheriton School of Computer Science
Remote Direct Memory Access (RDMA) can be used to implement a shared storage abstraction or a shared nothing abstraction for distributed applications. We argue that the shared storage abstraction is an overkill for loosely coupled applications and that the shared nothing abstraction does not leverage all the benefits of RDMA.
Junnan Chen, Master’s candidate
David R. Cheriton School of Computer Science
Conversations depend on information from the context. To go beyond one-round conversation, a chatbot must resolve contextual information such as: 1) co-reference resolution, 2) ellipsis resolution, and 3) conjunctive relationship resolution.
There are simply not enough data to avoid these problems by trying to train a sequence-to-sequence model for multi-round conversation similar to that of one-round conversation.