Krishnaram Kenthapadi

Krishnaram Kenthapadi Photo Dr. Krishnaram Kenthapadi has over a 20-year record of advancing new research areas, identifying early trends in AI/ML & influencing thought leadership in industry, shaping the technical vision, development & launch of new AI products, and steering company-wide initiatives in new domains. As the Chief AI Officer & Chief Scientist of Fiddler AI, he leads initiatives on generative AI (e.g., Fiddler Auditor, an open-source library for evaluating & red-teaming LLMs before deployment; AI safety, observability & feedback mechanisms for LLMs in production), and on AI safety, alignment, observability, and trustworthiness, as well as the technical strategy, customer-driven innovation, and thought leadership for Fiddler. Previously, he was a Principal Scientist at Amazon AWS AI, where he led the fairness, explainability, privacy, and model understanding initiatives in Amazon AWS AI platform, and shaped new initiatives such as Amazon SageMaker Clarify from inception to launch. Prior to joining Amazon, he was part of the LinkedIn AI team, where he led one of the early large-scale responsible AI deployments in industry (fairness-aware LinkedIn Talent Search), incubated responsible AI initiatives across different LinkedIn applications, and served as LinkedIn's representative in Microsoft's AI and Ethics in Engineering and Research (AETHER) Advisory Board. He shaped the technical roadmap and led the privacy/modeling efforts for LinkedIn Salary product, and prior to that, served as the relevance lead for the LinkedIn Careers and Talent Solutions Relevance team, which powers search/recommendation products at the intersection of members, recruiters, and career opportunities. Previously, he was a Researcher at Microsoft Research Silicon Valley, where his work resulted in product impact (and Gold Star / Technology Transfer awards), and several publications/patents. He received his Ph.D. in Computer Science from Stanford University in 2006, advised by Professor Rajeev Motwani. Before joining Stanford, he received his Bachelors degree in Computer Science and Engineering from Indian Institute of Technology-Madras.

Krishnaram has advanced the state-of-the-art in areas such as fairness, explainability, privacy, and robustness in ML, and helped start new research areas (e.g., co-authoring the second paper on Differential Privacy). Leveraging his expertise in research and industry, he has steered company-wide initiatives on responsible AI and AI observability, led the technical roadmap/design/launch of new AI products, and improved business metrics for existing products via technology transfers. He serves regularly on the senior program committees of conferences such as KDD, FAccT, and WWW, and co-chaired the 2014 ACM Symposium on Computing for Development. His work has been recognized through awards at NAACL, WWW, SODA, CIKM, ICML AutoML workshop, and Microsoft's AI/ML conference (MLADS). He has published 60+ papers, with 7500+ citations and filed 150+ patents (71 granted). He has given several invited industry talks, presented tutorials on trustworthy generative AI, privacy, fairness, explainable AI, ML model monitoring, and responsible AI at forums such as ICML, KDD, WSDM, WWW, FAccT, and AAAI, and instructed a course on responsible AI at Stanford, thereby influencing industry thinking, thought leadership, and practice in his areas of work.

Research Trustworthy Generative AI, AI Observability, AI Safety, Fairness/Explainability/Privacy/Robustness in AI/ML Systems, Algorithms for Large Datasets and Graphs, Data Mining, Web Search, Information Retrieval, Search and Recommendation Systems, Social Network Analysis, Computational Education.

Publications   [Google Scholar]   [Patents (71 Granted)]   [Selected Projects]

Contact
Email: kkenthapadi [at] gmail.com   [LinkedIn]   [Twitter]

Selected Initiatives:


Personal: Photos

Krishnaram Kenthapadi