School of Engineering
Showing 301-350 of 1,781 Results
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Rachel Cleaveland
Ph.D. Student in Computer Science, admitted Autumn 2021
BioI am a 5th-year PhD student at Stanford University, advised by Clark Barrett. My research focuses on applications of the theory of strings within symbolic execution as well as memory model verification.
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Steve Cousins
SRC Executive Director, Robotics Center
Current Role at StanfordExecutive Director of the Stanford Robotics Center
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Srivatsava Daruru
Affiliate, Computer Science
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. -
Eric Darve
Director, Institute for Computational and Mathematical Engineering (ICME), Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for science and engineering, large-language models, transformer models, surrogate and reduced order modeling, stochastic inversing, anomaly detection, numerical linear algebra, high-performance, parallel, and GPU computing.
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Emma Dauterman
Assistant Professor of Computer Science
BioEmma Dauterman is an assistant professor at Stanford University in the Department of Computer Science. She works at the intersection of systems, security, and applied cryptography to build systems that provide strong security and privacy properties. She was a postdoc at MIT with Henry Corrigan-Gibbs, and before that, she was a PhD student at UC Berkeley advised by Raluca Ada Popa and Ion Stoica. Emma's work has influenced the Signal messaging application, as well as Apple's Enhanced Visual Search. Emma was a runner-up for the ACM SIGSAC Doctoral Dissertation Award and a recipient of the Microsoft Ada Lovelace Research Fellowship and NSF Graduate Research Fellowship.
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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
Bioweb.stanford.edu/~gabisa/
