School of Engineering
Showing 1,201-1,300 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.
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Adam de la Zerda
Associate Professor of Structural Biology and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsMolecular imaging technologies for studying cancer biology in vivo
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Gregory Deierlein
John A. Blume Professor in the School of Engineering
BioDeierlein's research focuses on improving limit states design of constructed facilities through the development and application of nonlinear structural analysis methods and performance-based design criteria. Recent projects include the development and application of strength and stiffness degrading models to simulate steel and reinforced concrete structures, seismic design and behavior of composite steel-concrete buildings, analysis of inelastic torsional-flexural instability of steel members, and a fracture mechanics investigation of seismically designed welded steel connections.
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Karl Deisseroth
D. H. Chen Professor, Professor of Bioengineering and of Psychiatry and Behavioral Sciences
Current Research and Scholarly InterestsKarl Deisseroth's laboratory created and developed optogenetics, hydrogel-tissue chemistry (beginning with CLARITY), and a broad range of enabling methods. He also has employed his technologies to discover the neural cell types and connections that cause adaptive and maladaptive behaviors.
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Scott L. Delp, Ph.D.
Director, Wu Tsai Human Performance Alliance at Stanford, James H. Clark Professor in the School of Engineering, Professor of Bioengineering and of Mechanical Engineering
Current Research and Scholarly InterestsExperimental and computational approaches to study human movement. Development of biomechanical models to analyze muscle function, study movement abnormalities, design medical products, and guide surgery. Imaging and health technology development. Discovering the principles of peak performance to advance human health. Human performance research. Wearable technologies, video motion capture, and machine learning to enable large-scale analysis.
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Nurullah Demir
Visiting Postdoc, Computer Science
Affiliate, Program-Durumeric, Z.BioI hold a PhD from KIT and am currently a Visiting Postdoctoral Scholar at Stanford University. Previously, I was a Visiting Scholar at UC Davis. My research focuses on Web Security and Privacy Measurements, Robust ML models, and Metascience. I work with the if(is) and Intellisec research groups. I am also a core maintainer of the open-source project HTTP Archive and currently lead the Web Almanac.
Beyond academia, I am the founder of the web agency webpen, which specialises in web development and digital solutions, and the project SecuSeek, focused on innovative web security solutions. -
Utkan Demirci
Professor of Radiology (Diagnostic Sciences Laboratory) and, by courtesy, of Electrical Engineering
BioDr. Utkan Demirci, UofM’99, Stanford’01’05’05, is a Professor of Radiology (with tenure) and of Electrical Engineering (by courtesy) at the Canary Center at Stanford for Cancer Early Detection, Stanford University School of Medicine, where he leads a productive researcher group. Utkan is a tenured professor at Stanford University School of Medicine. Prior to joining Stanford in 2014, he held the position of Associate Professor at the Brigham and Women’s Hospital-Harvard Medical School and also served at the Harvard-MIT Health Sciences and Technology division. Over the past decade, his research group has focused on the early detection of cancer and has made significant contributions to the development of microfluidic platforms for sorting rare cells and exosomes and point-of-care bio-sensing technologies.
Dr. Demirci leads a productive and impactful research group focused on addressing problems from the clinic with innovations including cell sorter for IVF, optical technologies for detecting viruses, portable point of care technologies for diagnostics in global health, smart robots in vivo, extracellular vesicle based early detection approaches for cancer. He is an elected fellow of the American Institute of Medical and Biological Engineering and The Academy for Radiology & Biomedical Imaging Research Distinguished Investigator.
He has published over 250 peer-reviewed articles, 300 abstracts and proceedings, 24 book chapters and editorials, and 7 edited books. He also serves on the editorial board of various journals. He is a serial academic entrepreneur and co-founded multiple successful companies. His patents are translated into broadly used biomedical products. Dr. Demirci's pioneering work in microfluidics and cell sorting has resulted in CE certified and FDA approved devices used in over 500,000 clinical cases serving patients globally. -
Dora Demszky
Assistant Professor of Education and, by courtesy, of Computer Science
BioDr. Demszky is an Assistant Professor in Education Data Science at the Graduate School of Education at Stanford University. She works on developing natural language processing methods to support equitable and student-centered instruction. She has developed tools to give feedback to teachers on dialogic instructional practices, to analyze representation in textbooks, measure the presence of dialect features in text, among others. Dr Demszky has received her PhD in Linguistics at Stanford University, supervised by Dr Dan Jurafsky. Prior to her PhD, Dr. Demszky received a BA summa cum laude from Princeton University in Linguistics with a minor in Computer Science.
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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. -
Jesse DeRose
Masters Student in Management Science and Engineering, admitted Autumn 2024
Hourly Student Employee- Practitioner Course Program, Ethics In SocietyBioHow can work balance profit and social impact? What if employees were intrinsically motivated to show up every day?
I help leaders answer these questions because we all deserve purposeful work. Whether that’s cultivating emotional intelligence, fostering psychological safety, or removing process friction, healthy work is proven to increase productivity, creativity, and decision-making.
Combining industry research with a decade of experience building digital transformation programs, I help my clients build human-centered solutions that align their people, processes, and technology to make data-driven business decisions. -
Gauri Desai
Postdoctoral Scholar, Bioengineering
BioDr. Gauri Desai is a Postdoctoral Research Associate with the Female Athlete Science and Translational Research Program (FASTR). She is a biomechanist, with a research focus on female-specific biomechanical risk factors for sport-related injuries. She integrates biomechanics principles with physiology to provide an all-round perspective on improving performance and mitigating injury risk in female athletes. Dr. Desai's research complements human subject experiments with insights from computer modeling and simulation, to answer research questions that are challenging to address via human subject research studies alone. Beyond research, she is an active contributor to the sports science community through mentorship and advocacy for women in sport.
