Outline

00:00 - Intro

00:42 - “Research should be fun”

02:02 - Early steps in research

09:00 - Book writing and meeting C. Desoer

18:33 - Control synthesis via the factorization approach

25:46 - The graph metric

29:27 - Robotics and CAIR

36:00 - Randomized algorithms

40:41 - On learning

44:05 - Neural networks

48:40 - Tata, hidden Markov models, and large deviations theory

55:48 - Picking problems and role of luck

58:07 - Compressed sensing and non-convex optimization

01:02:17 - Interplay between control and machine learning

01:09:10 - Advice to future students

01:13:29 - Future of control

Links

Sagar’s website: https://tinyurl.com/4hwruajs

How to Write Mathematics: https://tinyurl.com/35794bv9

C. Desoer: https://tinyurl.com/svhknren

Control Systems Synthesis — A Factorization Approach: https://tinyurl.com/59wdc4sv

A Brief History of the Graph Topology: https://tinyurl.com/49uftzdk

Randomized algorithms for robust controller synthesis using statistical learning theory: https://tinyurl.com/wanpyeuc

Learning and Generalisation: https://tinyurl.com/2s3mzh8h

Are Analog Neural Networks Better Than Binary Neural Networks? https://tinyurl.com/3fnk27xc

An Introduction to Compressed Sensing: https://tinyurl.com/fc6a8eer

ep33 - Mathukumalli Vidyasagar: control synthesis, robotics, randomized algorithms, learning, compressed sensing, non-convex optimization

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