Computer Science
Showing 401-450 of 2,209 Results
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Srivatsava Daruru
Affiliate, Program-Koyejo, O.
BioSrivatsava Daruru is a researcher and machine learning leader whose work spans natural language processing, neuro-symbolic AI, and large-scale learning systems. He is currently Chief AI Officer at Exlens AI and was formerly Senior Manager of Machine Learning at ServiceNow, where he led research in retrieval-augmented generation (RAG), question answering, post-training optimization of large language models, and agentic workflows for conversational AI. His contributions shaped ServiceNow’s generative AI strategy, including the company’s first production-grade generative application, Genius Q&A.
Daruru’s research interests focus on self-improving large language models, reasoning, and mathematical verification. He is currently workin on VeriBench, an end-to-end benchmark for translating Python into Lean 4, and VeriCI, a continuous verification framework for CI/CD pipelines, as part of neuro-symbolic software reliability.
He has published at leading venues such as ACM SIGKDD and IEEE ICDM, with research spanning scalable clustering for terascale astronomy, parallel data mining, and large-scale telecom analytics. His Google Scholar profile reflects a consistent track record of contributions to data mining, NLP, and applied machine learning. In addition, he is the inventor on multiple patents in NLP, fact validation, and semi-automated data labeling.
Daruru holds an M.S. in Computer Science from the University of Texas at Austin and a B.Tech. (Hons) in Computer Science from IIIT Hyderabad.
About Me (Informal)
I am a scientist and engineer working at the intersection of large language models, reasoning, and verification. My long-term vision is to build AI systems that are not only powerful but also trustworthy, capable of explaining themselves and proving their correctness. I’m especially excited about self-improving LLMs, agentic workflows, and neuro-symbolic methods that combine data-driven learning with formal verification. Currently, I’m working on VeriBench and VeriCI, projects that push AI systems toward rigorous mathematical guarantees while remaining practical for real-world development pipelines. -
Mateus Gheorghe De Castro Ribeiro
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2022
Ph.D. Minor, Computer ScienceBioMateus Gheorghe de Castro Ribeiro is a PhD candidate in the Stanford Sustainable Systems Lab. He has worked on various topics at the intersection of engineering applications and artificial intelligence (AI). His main area of research focuses on AI applied to sustainable energy systems, specifically using data-driven methods to accelerate the electrification of bus fleets, ensure reliable operations with minimal costs, and achieve 24/7 carbon-free operations. Mateus obtained his bachelor's and master's degrees in mechanical engineering from the Federal University of Juiz de Fora and the Pontifical Catholic University of Rio de Janeiro, respectively. In 2022, he was awarded the CAPES/Fulbright Scholarship to pursue his PhD in the Department of Civil and Environmental Engineering at Stanford University.
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Gabriela de Sá
Undergraduate, Computer Science
Research Assistant, SIEPR OperationsBioweb.stanford.edu/~gabisa/
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Nurullah Demir
Visiting Postdoc, Computer Science
Affiliate, Program-Durumeric, Z.BioMy research focuses on building automated, agentic systems to identify and mitigate structural security and privacy risks at internet scale.
I hold a PhD from KIT. Previously, I was a Visiting Scholar at UC Davis. I also work closely with the if(is) and Intellisec research groups and I am a core maintainer of the open-source project HTTP Archive and the Editor-in-Chief of the Web Almanac.
I actively translate my research into operational tools. I am the founder of the global threat intelligence platform SecuSeek. -
Yegor Denisov-Blanch
Research Scientist, Program-Koyejo, O.
BioResearch Scientist
Stanford Artificial Intelligence Laboratory (SAIL)
Department of Computer Science, Stanford School of Engineering
Yegor Denisov-Blanch studies how artificial intelligence is changing software engineering. His research focuses on measuring real-world engineering productivity, AI adoption, code quality, and organizational outcomes across large populations of repositories and teams. He designs empirical methods and metrics that move beyond simple proxies to accurately quantify software output, rework, and AI-assisted development at scale.
His work has been covered by the World Bank, the United Nations, and The Washington Post, and has been reshared by Elon Musk.
Yegor graduated with highest honors from Indiana University, where he studied operations research. He also earned an MBA from Stanford Graduate School of Business on full-tuition scholarships. He left school after the eighth grade, founded a company, and later entered university skipping 5 grades. He is a Master of Sport of Russia in Olympic weightlifting, a national champion-equivalent distinction awarded in 2013. -
Abhijit Devalapura
Masters Student in Computer Science, admitted Autumn 2021
Student/Hourly, Law Instructional SupportBioSIEPR Undergraduate Research Fellow 2022-2023
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David Dill
Donald E. Knuth Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsSecure and reliable blockchain technology at Facebook.
