Dr. Amir Sadovnik Gives CURENT Power and Energy Seminar on Feb. 21st
Dr. Amir Sadovnik will gives the CURENT Power and Energy Seminar on Feb. 21st in MHK 404 from 12:20pm to 1:10pm. This seminar will be available through ZOOM (see info near bottom of this email).
Presenter: Dr. Amir Sadovnik, University of Tennessee
Time: Friday, February 21st, 12:20 PM - 1:10 PM EST
Location: Min H. Kao Building, Room 404
Title: An Introduction to Reinforcement Learning
Abstract: With the resurgence of AI in past years, due mostly to deep learning methods, there has also been revived interest in the field of reinforcement learning. By combining these two techniques, deep reinforcement learning algorithms have been able to achieve results that were not possible just a few years ago, such as beating the world champion in the game of Go or building a single system that can play multiple Atari games at human level. In this talk, I will give an introduction to the field of reinforcement learning by describing how it differs from other machine learning techniques, by explaining the mathematical principals it relies on, and finally by going through an example to show how it can be implemented.
Bio: Amir Sadovnik is an assistant professor in the EECS department at the University of Tennessee. He received his PhD from the School of Electrical and Computer Engineering at Cornell University and was advised by Prof. Tsuhan Chen as member of the Advanced Multimedia Processing Lab. Prior to arriving at Cornell he received his Bachelors in Electrical and Computer Engineering from The Cooper Union.
Prior to arriving at UT, Amir was an assistant professor at Lafayette College in Easton, PA. He spent four years mostly teaching undergraduate level courses in addition to working on undergraduate research. During his time at Lafayette he taught a variety of both introductory and advanced computer science courses. In addition, he helped redesign the introductory computer science course to make it more inclusive and was an active advocate for women in the field.
His research in the field of computer vision has been mostly driven by the way humans understand and interact with images. This human centered view has led him to work on new and exciting projects, which utilize tools from different fields (such as computer vision, signal processing, natural language processing, machine learning, etc.) and apply them in new ways.
His current research is mostly centered on using deep neural networks for tasks which tend to be more subjective such as evoked emotions, face similarity, and fashion compatibility. The subjective nature of these problems presents many interesting obstacles and opportunities which he explores in his research.
Zoom Information:
Join from PC, Mac, Linux, iOS or Android: https://tennessee.zoom.us/j/711256283
Or iPhone one-tap (US Toll): +16468769923,711256283# or +16699006833,711256283#
Or Telephone: +1 646 876 9923 (US Toll) +1 669 900 6833 (US Toll) Meeting ID: 711 256 283
International numbers available: https://zoom.us/u/aFK5Bq5SR
Or an H.323/SIP room system: H.323: 162.255.37.11 (US West) or 162.255.36.11 (US East) Meeting ID: 711 256 283
Upcoming Seminars
Friday, February 28th – TBD
Friday, March 6th – Industry Seminar with Cecil Brown of TVA, TVA Inclusion Program
Friday, March 13th – TBD
Friday, March 20th – No Seminar Spring Break
Friday, March 27th - Industry Seminar with Betsey McCall of Seven States
Friday, April 3rd - Xin Xu
Friday, April 10th - No Seminar Spring Recess
Friday, April 17th - Liyan Zhu, University of Tennessee
Friday, April 24th - Industry Seminar with Srijib Mukherjee with ORNL
See the CURENT calendar for more news and seminars
