School of Engineering
Showing 1-50 of 248 Results
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Simone D'Amico
Associate Professor of Aeronautics and Astronautics
BioSimone D’Amico is Associate Professor of Aeronautics and Astronautics (AA), W.M. Keck Faculty Scholar in the School of Engineering, Associate Professor of Geophysics (by Courtesy), Science Fellow at the Hoover Institution and Chief Science Officer at EraDrive Inc. He is the Founding Director of the Stanford Space Rendezvous Laboratory, Founding Co-Director of the Center for AEroSpace Autonomy Research (CAESAR), and Director of the Undergraduate Program in Aerospace Engineering at Stanford. He has 23+ years of experience in research and development of autonomous spacecraft and distributed space systems. He developed and deployed the distributed Guidance, Navigation, and Control (GNC) system of several formation-flying, rendezvous and proximity operations missions such as GRACE (NASA/DLR), PRISMA (OHB/DLR/CNES/DTU), TanDEM-X (DLR), BIROS (DLR) and PROBA-3 (ESA). Currently, he is the institutional PI of four autonomous satellite swarms funded by NASA (STARLING, STARI) and by NSF (VISORS, SWARM-EX). Dr. D'Amico is Fellow of AAS, Associate Fellow of AIAA, Associate Editor of the AIAA's JGCD and he is in the Advisory Board of four space start-ups focusing on distributed space systems for future applications in SAR remote sensing, orbital lifetime prolongation, and space-based solar power. He was the recipient of several awards, most recently the 2024 NASA Ames Honor Award for the Starling mission, Best Paper Awards at IAF (2022), IEEE (2021), AIAA (2021), AAS (2019) conferences, the M. Barry Carlton Award by IEEE (2020), the Leonardo 500 Award by the Leonardo da Vinci Society/ISSNAF (2019), FAI/NAA’s Group Diploma of Honor (2018), DLR’s Sabbatical/Forschungssemester (2012) and Wissenschaft Preis (2006), and NASA’s Group Achievement Award for the GRACE mission (2004). He received the B.S. and M.S. degrees from Politecnico di Milano (2003) and the Ph.D. degree from Delft University of Technology (2010).
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Marta D'Elia
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioI’m a research/computational scientist working on the design and analysis of models and data-driven algorithms for the simulation of complex, multiscale and multiphysics problems. My background and training have foundations in Numerical Analysis, Scientific Computing, Inverse Problems, Control and Optimization, and Uncertainty Quantification. In the past five years I have focused on Scientific Machine Learning (SciML) and Deep Learning. I am an expert in Nonlocal/Fractional Modeling and Simulation (10 years) with application to Continuum Mechanics, Subsurface Transport, Image Processing, and Turbulence. I have a master's degree in Mathematical Engineering from Politecnico di Milano (2007) and a PhD in Applied Mathematics from Emory University (2011).
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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
On Partial Leave from 11/22/2025 To 12/21/2025Current 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.
