School of Engineering
Showing 1,201-1,250 of 6,554 Results
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Onat Dalmaz
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
Current Research and Scholarly InterestsMy current research centers on developing mathematical tools to enhance the explainability of image reconstruction algorithms in computational magnetic resonance imaging (MRI). By integrating principles from machine learning, signal processing, and generative models, I aim to improve the transparency and reliability of AI applications in medical imaging.
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Bruce Daniel
Professor of Radiology (Body Imaging) and, by courtesy, of Bioengineering
Current Research and Scholarly Interests1. MRI of Breast Cancer, particularly new techniques. Currently being explored are techniques including ultra high spatial resolution MRI and contrast-agent-free detection of breast tumors.
2. MRI-guided interventions, especially MRI-compatible remote manipulation and haptics
3. Medical Mixed Reality. Currently being explored are methods of fusing patients and their images to potentially improve breast conserving surgery, and other conditions. -
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. -
Eric Darve
Director, Institute for Computational and Mathematical Engineering (ICME) and Professor of Mechanical Engineering
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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Reinhold Dauskardt
Ruth G. and William K. Bowes Professor in the School of Engineering
BioDauskardt and his group have worked extensively on integrating new materials into emerging technologies including thin-film structures for nanoscience and energy technologies, high-performance composite and laminates for aerospace, and on biomaterials and soft tissues in bioengineering. His group has pioneered methods for characterizing adhesion and cohesion of thin films used extensively in device technologies. His research on wound healing has concentrated on establishing a biomechanics framework to quantify the mechanical stresses and biologic responses in healing wounds and define how the mechanical environment affects scar formation. Experimental studies are complimented with a range of multiscale computational capabilities. His research includes interaction with researchers nationally and internationally in academia, industry, and clinical practice.
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David Davidson
Sr Research Engineer, Mechanical Engineering
BioEducation
University of Toronto Physics B.S (1978)
University of Toronto Aerospace Sciences M.Sc. (1980)
York University Physics Ph.D. (1986)
Appointment:
1986-present Senior Research Engineer, Mechanical Engineering Department
Research Activities:
Dr. Davidson’s research interests span the fields of gas dynamics and combustion kinetics. During his tenure at Stanford University he investigated the chemical kinetics of combustion using a wide array of optical and laser-based diagnostic methods and advanced the use of these diagnostics in shock tubes. He co-authored over 350 research publications with his students and Professor Ronald Hanson. He continues to advise and mentor the graduate students who use shock tubes in the High Temperature Gasdynamics Laboratories. An overview of the shock tube studies performed at Stanford under Prof. Hanson’s and Dr. Davidson’s supervision can be found in the report entitled “Fundamental Kinetics Database Utilizing Shock Tube Measurements” available at http://purl.stanford.edu/kb621cw6967.
He claims he is now retired, but apparently, he is still working. -
Beverly Davis
Administrative Associate, Electrical Engineering
Current Role at StanfordFaculty Administrative Assistant for Professors
Daniel Congreve, Eric Pop, Nick McKeown and the Shenoy Lab -
Caden Davis
Masters Student in Electrical Engineering, admitted Autumn 2025
Current Research and Scholarly InterestsPreviously, I developed a platform for joint communications and sensing (JCAS) with mmWave beamforming systems as part of the UCLA Wireless Lab under Professor Ian Roberts. Then, as a DSP engineer intern at Anduril, I worked to enhance detectors for frequency-hopping OFDM and chirp-spread-spectrum signals. From these experiences, I found a strong interest in optimization methods and statistical inference techniques for signal processing systems, mainly wireless communications and radar.
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Jenna Davis
Professor of Civil and Environmental Engineering, of Environmental Social Sciences and Higgins-Magid Senior Fellow at the Woods Institute
Current Research and Scholarly InterestsProfessor Davis’ research and teaching deals broadly with the role that water plays in promoting public health and economic development, with particular emphasis on low- and middle-income countries. Her group conducts applied research that utilizes theory and analytical methods from public and environmental health, engineering, microeconomics, and planning. They have conducted field research in more than 20 countries, most recently including Zambia, Bangladesh, and Kenya.
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Kristen Davis
Associate Professor of Oceans and, by courtesy, of Civil and Environmental Engineering
BioI am an engineer and oceanographer who is interested in studying how physical processes shape coastal waters – combining principles of fluid mechanics, oceanography, and ecology. I use both field observations and numerical tools to examine circulation in the ocean, its natural variability, and influence on marine ecosystems and human-nature interactions. I joined Stanford department of Oceans in 2024. Before that, I was an Associate Professor in the Department of Civil & Environmental Engineering at the University of California, Irvine.
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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.
