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Computer Engineering and Systems Group

Texas A&M University College of Engineering

CESG Seminar – Alan Kuhnle

Posted on October 28, 2022 by Vickie Winston

Friday, November 4, 2022
10:20 – 11:10 a.m. (CST)
ETB 1020 – **In-person** (Zoom option; Links and PW in syllabus or email)

Dr. Alan Kuhnle
Assistant Professor, Computer Science and Engineering
Texas A&M University

Title: “Scalable and Learned Algorithms for Discrete Optimization”

Talking Points

  • Linear-time algorithms for subset selection problems
  • RL for learning local search algorithm

Abstract
In this talk, I present the work of the Optimization and Learning Systems Lab on the design of scalable algorithms for optimization problems on big data. In particular, I describe our work on linear-time, parallelizable algorithms for combinatorial optimization problems arising from online social networks. Finally, I give an overview of future directions of the lab, which include augmenting algorithms with learned components to improve practical performance; optimization with incomplete information; and submodular planning.

Biography
Dr. Alan Kuhnle is an Assistant Professor of Computer Science & Engineering at Texas A&M University, where he directs the Optimization and Learning Systems Lab. His work focuses on the design and analysis of scalable algorithms for ubiquitous combinatorial optimization problems arising in data science applications, such as vehicle routing and marketing on social networks. He is the recipient of the First Year Assistant Professor Award at Florida State University in 2020 and his work has led to 34 publications in leading academic journals and conferences. He has served on the program committee of machine learning conferences and is Associate Editor of Journal of Combinatorial Optimization.

Recent TAMU article on Dr. Kuhnle: HERE

More on CESG Seminars: HERE

Please join on Friday, 11/4/22 at 10:20 a.m. in ETB 1020.

Filed Under: Uncategorized

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