Summary
Abhinav Garg is a research engineer specializing in speech recognition and foundation models, currently working at Stanford's Center for Research on Foundation Models after a decade of industry and academic experience. He built ML research teams and applied speech systems at Samsung R&D in Seoul and consulted on production ML problems for companies like Observe.AI and Jumio. A Stanford CS master’s graduate and IIT Kanpur alumnus, he has taught core NLP, speech, and graph/ML courses (CS224N, CS224S, CS224W) to graduate students, bridging classroom rigor with practical system-building. Based in Palo Alto, he combines deep speech-processing expertise with hands-on production ML experience, and has a knack for translating cutting-edge research into deployed features across large-scale consumer and enterprise products.
10 years of coding experience
5 years of employment as a software developer
Indian Institute of Technology Kanpur
Master's degree Computer Science, Master's degree Computer Science at Stanford University