Center for Signal and Information Processing Hosts Weekly Seminars

The Center for Signal and Information Processing (CSIP) in the School of Electrical and Computer Engineering (ECE) supports research that involves the representation, processing, modeling, and analysis of signals, information, and physical phenomena. At the core of this research is the interpretation of the captured data and its visualization, analysis, manipulation, and control. Research at CSIP lies at the core of modern artificial intelligence and machine learning algorithms. Some of the current projects within CSIP include, but are not limited to:  Digital Signal Processing (DSP) and Machine Learning Theory; High-dimensional Statistics; Conversational Systems; Robust and Explainable AI; Active and Reinforcement Learning; Image, Speech, Audio & Video Processing and Learning; and Radar & Array Processing. 

Hosting CSIP Seminars on current topics has been part of the ECE tradition of extended learning for more than two decades. It is a celebration of the students and faculty innovation and academic excellence. The seminars are an opportunity for our students to share and learn about current and state-of-the-art research happening in ECE at Georgia Tech and beyond. Past speakers include graduate students, academia and industry leaders, current and new faculty, guests, and alumni. 

The tradition has included pizza for every taste. In 2020, we pivoted to a virtual experience (no pizza). For Fall 2021, we continue CSIP Seminars on Fridays at 3:00 p.m. (Eastern Time) held virtually at https://bluejeans.com/4658604304. Some of these seminars will be hybrid experiences (possibly with pizza!). Look out for upcoming e-mail notifications. 

To get CSIP/DSP related emails, please sign up here.  For more information about CSIP Seminars, contact huckiyang@gatech.edu or alregib@gatech.edu. 

Upcoming Seminars

October 29: Advances in end-to-end automatic speech recognition, Dr. Jinyu Li, Microsoft

November 5: Multi-Speaker Conversation Recognition based on End-to-End Neural Networks, by Prof. Shinji Watanabe, Carnegie Mellon University

November 19: Foundations and Applications of Deep Learning over Graphs, by Prof. Pan Li, Purdue University

Writers: Raquel Plaskett, Ghassan Al Regib, and Huck Yang