Summary
Kashyap Popat is a Machine Learning Engineer with nine years of experience building large-scale content understanding and NLP systems, currently working on content models at Meta in London. He holds a PhD from the Max Planck Institute where his dissertation produced explainable credibility-analysis models that retrieve evidence, model stance, and weigh source trustworthiness—work that bridges research-grade interpretability with practical retrieval. His background spans industry research and product deployments, from launching a personalized learning system at IBM Research to improving search robustness during a Facebook internship. Comfortable moving models from research to production, he combines deep academic rigor with hands-on engineering across cross-lingual IR, claim verification, and curriculum-aligned content analysis. An author on Google Scholar, he brings a rare mix of explainability-focused NLP expertise and operational experience at scale.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Max Planck Institute for Informatics
M.Tech, Computer Science, M.Tech, Computer Science at IIT Bombay
Bachelor of Engineering (B.E.), Computer Engineering, Bachelor of Engineering (B.E.), Computer Engineering at Dharmsinh Desai Institute of Technology
English, Hindi, Gujarati