Stanford University
Showing 20,781-20,790 of 36,322 Results
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Anay Mehrotra
Postdoctoral Scholar, Management Science and Engineering
BioI am a Postdoctoral Scholar at Stanford, where I am excited to work with Amin Saberi. I completed my Ph.D. at Yale University where I was fortunate to be advised by Amin Karbasi and Manolis Zampetakis.
My research focuses on machine learning under complex conditions where traditional assumptions break down. My work has two parts. First, I develop foundations for machine learning with missing and selectively observed data (spanning causal inference, limited-dependence, truncated statistics, and omissions shaped by societal biases). Second, I study why generative AI systems (including language models) are effective and design methods to evaluate and improve their safety.
My work has received the Best Paper Award at COLT, been featured in WIRED, and received the Sir Binay Kumar Sinha award from IIT Kanpur. As an undergraduate, I represented IIT Kanpur at the ICPC World Final. While at Yale, I also taught at the Yale ICPC Club. -
Apurva Mehta
Senior Scientist, SLAC National Accelerator Laboratory
BioI am a materials scientist with three decades of experience unraveling the molecular-scale processes that govern the functionality, aging, and failure of complex materials and devices. Over this time, advanced characterization methods have undergone a revolutionary transformation, driven by the emergence of brighter sources—from synchrotrons and X-ray free-electron lasers to MeV accelerator-based electron sources—paired with faster and larger-area detectors. While the depth and precision of measurements have vastly improved, the explosion of raw data now poses a significant challenge, making it increasingly difficult to extract meaningful insights them.
Recognizing this growing challenge, I have devoted the last decade to harnessing the power of emerging machine learning and artificial intelligence techniques to find breakthroughs. My focus has been on not only accelerating the extraction of knowledge from intricate, multi-dimensional, and often noisy measurements but also on making data collection smarter. By integrating these cutting-edge technologies, I aim to transform how we approach material science and deepen our understanding of material behavior and device performance.
