Dr. Aditya Thakur, a computer science professor at U.C. Davis, walks us through his work on developing analysis tools that he wished he had while working in industry at places like Google. Aside from program analysis, we talk about making a research group successful by exposing them to industry. Towards the end, he shares his work on techniques and tools for repairing a trained deep neural network once a mistake has been discovered. Along the way, we learn about things like abstract interpretation, non-determinism, the trickiness of parallelism, and other concepts pertinent to analysis in an approachable way.

You can watch this episode on our Youtube Channel:  https://youtube.com/c/BuildingBetterSystemsPodcast

Joey Dodds: https://galois.com/team/joey-dodds/ 

Shpat Morina: https://galois.com/team/shpat-morina/  

Aditya Thakur: http://thakur.cs.ucdavis.edu/

Galois, Inc.: https://galois.com/ 

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