ECE Welcomes Muthukumar, Pananjady to Georgia Tech

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Jackie Nemeth

School of Electrical and Computer Engineering

404-894-2906

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Summaries

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The School of Electrical and Computer Engineering (ECE) is pleased to welcome our two newest faculty members, Vidya Muthukumar and Ashwin Pananjady, to Georgia Tech.

Full Summary:

The School of Electrical and Computer Engineering (ECE) is pleased to welcome our two newest faculty members, Vidya Muthukumar and Ashwin Pananjady, to Georgia Tech.

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  • Vidya Muthukumar and Ashwin Pananjady Vidya Muthukumar and Ashwin Pananjady
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The School of Electrical and Computer Engineering (ECE) is pleased to welcome our two newest faculty members, Vidya Muthukumar and Ashwin Pananjady, to Georgia Tech.

Muthukumar is an assistant professor and is a member of the digital signal processing (DSP) technical interest group. Her office is located in the Centergy Building, Room 5213.

Muthukumar’s research interests are in machine learning, statistical signal processing, game theory, and sequential decision-making.

Muthukumar received the B.Tech. (with honors) degree from the Indian Institute of Technology, Madras and the Ph.D. degree in Electrical Engineering from the Department of Electrical Engineering and Computer Science (EECS) at the University of California, Berkeley. She interned at IBM Research in the summer of 2018 as a Science for Social Good fellow. Before joining Georgia Tech, Muthukumar spent a semester at the Simons Institute for the Theory of Computing at UC Berkeley as a research fellow for the program, “Theory of Reinforcement Learning.”

While at Berkeley, Muthukumar received the Simons-Berkeley research fellowship, IBM Science for Social Good Fellowship, and UC Berkeley EECS Outstanding Course Development and Teaching Award. She serves on the senior program committee for COLT 2021.

Pananjady is an assistant professor and holds a joint appointment with ECE with the DSP technical interest group. His primary academic appointment is with the H. Milton Stewart School of Industrial and Systems Engineering. His office is located in the Groseclose Building, Room 443.

Pananjady’s research interests lie broadly in statistics, optimization, and information theory, as well as their applications in data science, machine learning, and reinforcement learning. He is particularly interested in statistical and computational problems arising from high-dimensional data with geometric structure.

Pananjady received his Ph.D. from the Department of EECS at the University of California, Berkeley and the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Madras. During his Ph.D., he spent a couple of summers working in industrial research labs at Amazon and Microsoft. 

While at UC Berkeley, he received the inaugural Lawrence D. Brown Ph.D. student award from the Institute of Mathematical Statistics; the David J. Sakrison Memorial Prize for his dissertation research; a Swiss Re Research Fellowship in Probability, Geometry and Computation in High Dimensions from the Simons Institute for the Theory of Computing; an Outstanding Graduate Student Instructor award from UC Berkeley; and the Governor's Gold Medal from IIT Madras.

“Please check out the faculty profiles for Vidya and Ashwin and send them an email greeting or introduce yourselves as you see them in online meetings or in person on campus,” said Magnus Egerstedt, the Steve W. Chaddick School Chair and ECE professor. “I am excited to have both of them here at Georgia Tech and look forward to them having bright futures and productive, rewarding careers with us.”

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School of Electrical and Computer Engineering

Categories
Student and Faculty, Research, Engineering
Related Core Research Areas
Data Engineering and Science
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Keywords
Vidya Muthukumar, Ashwin Pananjady, School of Electrical and Computer Engineering, H. Milton Stewart School of Industrial and Systems Engineering, machine learning, statistical signal processing, game theory, sequential decision-making, University of California Berkeley, statistics, optimization, information theory, data science, reinforcement learning high-dimensional data with geometric structure
Status
  • Created By: Jackie Nemeth
  • Workflow Status: Published
  • Created On: Jan 20, 2021 - 9:28am
  • Last Updated: Jan 20, 2021 - 10:49am