Stanford University
Showing 101-200 of 259 Results
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Nick Delurgio
Course Asst-Graduate, Aeronautics and Astronautics
BioNick Delurgio is a graduate student in Mechanical Engineering at Stanford University. Nick previously received his B.S. in Aerospace Engineering from the University of Texas at Austin, where he developed in interest in Guidance, Navigation, and Control (GNC) for Aerospace applications. At Stanford, Nick is pursuing his interest in GNC through Distributed Space Systems (DSS) research, advised by Professor Simone D'Amico. Nick's research involves the development of dynamics, guidance, and control strategies for RPOD missions in eccentric orbits, as well as creating reduced order modeling techniques to simplify formation flying mission design.
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Utkan Demirci
Professor of Radiology (Canary Cancer Center) and, by courtesy, of Electrical Engineering
On Partial Leave from 02/26/2024 To 02/25/2025BioUtkan Demirci is a tenured professor in the School of Medicine at Stanford University and serves as the Interim Division Chief and Director of the Canary Center at Stanford for Cancer Early Detection in the Department of Radiology. Prior to Stanford, he was an Associate Professor of Medicine at the Brigham and Women’s Hospital, Harvard Medical School, and a faculty member of the Harvard-MIT Health Sciences and Technology division.
Professor Demirci received his PhD from Stanford University in Electrical Engineering in 2005 and holds M.S. degrees in Electrical Engineering, and in Management Science and Engineering. He has published over 200 peer-reviewed journal articles, 24 book chapters, 7 edited books, and several hundred abstracts and proceedings, as well as having over 25 patents and disclosures pending or granted. He has mentored and trained hundreds of successful scientists, entrepreneurs and academicians and fostered research and industry collaborations around the world. Dr. Demirci was awarded the NSF CAREER Award, and IEEE EMBS Early Career Award. He is currently a fellow of the the American Institute for Medical and Biological Engineering (AIMBE, 2017), and Distinguished Investigator of the Academy for Radiology and Biomedical Imaging Research and serves as an editorial board member for a number of peer-reviewed journals.
The BAMM Lab group focuses on developing innovative extracellular vesicle isolation tools, point-of-care technologies and creating microfluidic platforms for early cancer detection with broad applications to multiple diseases including infertility and HIV. Dr. Demirci’s lab has collaborated with over 50 research groups and industry partners around the world. His seminal work in microfluidics has led to the development of innovative FDA-approved platform technologies in medicine and many of his inventions have been industry licensed. He holds several FDA-approved and CE-marked technologies that have been widely used by fertility clinics with assisted reproductive technologies leading to over thousands of live births globally and in the US.
Dr. Demirci is a serial academic entrepreneur and co-founder of DxNow, Zymot, Levitas Bio, Mercury Biosciences and Koek Biotech and serves as an advisor, consultant and/or board member to some early stage companies and investment groups. -
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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John DeSilva
Systems & Network Manager, Electrical Engineering
Current Role at StanfordSystems & Network Manager, David Packard Electrical Engineering Building
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Joseph M. DeSimone
Sanjiv Sam Gambhir Professor of Translational Medicine, Professor of Chemical Engineering and, by courtesy, of Chemistry, of Materials Science and Engineering, and of Operations, Information and Technology at the Graduate School of Business
BioJoseph M. DeSimone is the Sanjiv Sam Gambhir Professor of Translational Medicine and Chemical Engineering at Stanford University. He holds appointments in the Departments of Radiology and Chemical Engineering with courtesy appointments in the Department of Chemistry and in Stanford’s Graduate School of Business.
The DeSimone laboratory's research efforts are focused on developing innovative, interdisciplinary solutions to complex problems centered around advanced polymer 3D fabrication methods. In Chemical Engineering and Materials Science, the lab is pursuing new capabilities in digital 3D printing, as well as the synthesis of new polymers for use in advanced additive technologies. In Translational Medicine, research is focused on exploiting 3D digital fabrication tools to engineer new vaccine platforms, enhanced drug delivery approaches, and improved medical devices for numerous conditions, with a current major focus in pediatrics. Complementing these research areas, the DeSimone group has a third focus in Entrepreneurship, Digital Transformation, and Manufacturing.
Before joining Stanford in 2020, DeSimone was a professor of chemistry at the University of North Carolina at Chapel Hill and of chemical engineering at North Carolina State University. He is also Co-founder, Board Chair, and former CEO (2014 - 2019) of the additive manufacturing company, Carbon. DeSimone is responsible for numerous breakthroughs in his career in areas including green chemistry, medical devices, nanomedicine, and 3D printing. He has published over 350 scientific articles and is a named inventor on over 200 issued patents. Additionally, he has mentored 80 students through Ph.D. completion in his career, half of whom are women and members of underrepresented groups in STEM.
In 2016 DeSimone was recognized by President Barack Obama with the National Medal of Technology and Innovation, the highest U.S. honor for achievement and leadership in advancing technological progress. He has received numerous other major awards in his career, including the U.S. Presidential Green Chemistry Challenge Award (1997); the American Chemical Society Award for Creative Invention (2005); the Lemelson-MIT Prize (2008); the NIH Director’s Pioneer Award (2009); the AAAS Mentor Award (2010); the Heinz Award for Technology, the Economy and Employment (2017); the Wilhelm Exner Medal (2019); the EY Entrepreneur of the Year Award (2019 U.S. Overall National Winner); and the Harvey Prize in Science and Technology (2020). He is one of only 25 individuals elected to all three branches of the U.S. National Academies (Sciences, Medicine, Engineering). DeSimone received his B.S. in Chemistry in 1986 from Ursinus College and his Ph.D. in Chemistry in 1990 from Virginia Tech. -
Abhijit Devalapura
Masters Student in Computer Science, admitted Autumn 2021
Research Asst., Graduate School of Business - EconomicsBioSIEPR Undergraduate Research Fellow 2022-2023
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Thomas Devereaux
Professor of Photon Science and of Materials Science and Engineering
Current Research and Scholarly InterestsMy main research interests lie in the areas of theoretical condensed matter physics and computational physics. My research effort focuses on using the tools of computational physics to understand quantum materials. Fortunately, we are poised in an excellent position as the speed and cost of computers have allowed us to tackle heretofore unaddressed problems involving interacting systems. The goal of my research is to understand electron dynamics via a combination of analytical theory and numerical simulations to provide insight into materials of relevance to energy science. My group carries out numerical simulations on SIMES’ high-performance supercomputer and US and Canadian computational facilities. The specific focus of my group is the development of numerical methods and theories of photon-based spectroscopies of strongly correlated materials.
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Sahil Dhakla
Masters Student in Civil and Environmental Engineering, admitted Autumn 2023
BioDedicated to advancing technology in construction, I am a results-driven professional with a proven track record in Virtual Design Construction (VDC) and sustainable project execution. As a Master's candidate in Sustainable Design & Construction at Stanford University, my expertise spans the realms of on-site construction, BIM, Augmented/Virtual Reality, and document control.
With a background as a VDC Engineer and Founder/Principal Consultant at BuiltVisor Pvt Ltd, I have led dynamic teams, facilitated cross-functional dialogue, and ensured the successful implementation of technology-driven workflows. My commitment to people-oriented organizations and sustainable practices aligns with my goal of contributing to societal upliftment through innovative technological solutions in the construction industry. -
Gerwin Dijk
Postdoctoral Scholar, Materials Science and Engineering
BioBioelectronics, neurostimulation, biosensors, conducting polymers, microfabrication.
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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.
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Katryna Dillard
Senior Program Manager, Program-Bao Z.
BioKatryna Dillard joined Stanford University in April 2021 as the program manager for the Stanford Wearable Electronics (eWEAR) Initiative. As the program manager Katryna manages the logistics of annual symposiums, monthly seminars/newsletters, tracking and updating current affiliate member companies, and acts as a point of contact with affiliate members while providing administrative support. Prior to joining eWEAR Katryna worked in hotels at the front desk and in events for 5 years. She graduated from Whittier College with a B.A. in Sociology and Theatre Communication Arts with an emphasis in Design and Technology.
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Jennifer Dionne
Professor of Materials Science and Engineering
BioJennifer Dionne is the Senior Associate Vice Provost of Research Platforms/Shared Facilities and an Associate Professor of Materials Science and Engineering and of Radiology (by courtesy) at Stanford. Jen received her Ph.D. in Applied Physics at the California Institute of Technology, advised by Harry Atwater, and B.S. degrees in Physics and Systems & Electrical Engineering from Washington University in St. Louis. Prior to joining Stanford, she served as a postdoctoral researcher in Chemistry at Berkeley, advised by Paul Alivisatos. Jen's research develops nanophotonic methods to observe and control chemical and biological processes as they unfold with nanometer scale resolution, emphasizing critical challenges in global health and sustainability. Her work has been recognized with the Alan T. Waterman Award (2019), an NIH Director's New Innovator Award (2019), a Moore Inventor Fellowship (2017), the Materials Research Society Young Investigator Award (2017), Adolph Lomb Medal (2016), Sloan Foundation Fellowship (2015), and the Presidential Early Career Award for Scientists and Engineers (2014), and was featured on Oprah’s list of “50 Things that will make you say ‘Wow!'"
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Varun Dolia
Ph.D. Student in Materials Science and Engineering, admitted Autumn 2021
BioVarun Dolia is a Benchmark Fellow and a Ph.D. candidate in Prof. Jen Dionne's lab. He is excited about developing nanophotonic platforms for health and environmental monitoring.
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Stefan P. Domino
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioDr. Domino’s research interest rests within low-Mach fluid mechanics methods development for complex systems that drive the coupling of mass, momentum, species and energy transport. His core research resides within the intersection of physics elucidation, numerical methods research, V&V techniques exploration, and high performance computing and coding methods for turbulent flow applications. Stefan also supports the teaching of ME469, Computational Methods in Fluid Mechanics, while continuing his primary career at Sandia National Laboratories as a Distinguished Member of the Technical Staff.
Education:
University of Utah
Ph.D. Department of Chemical Engineering, 1999
"Methods towards improved simulations for the oxides of nitrogen in pulverized-coal furnaces"
Professor Philip J. Smith, Advisor
Select Recent Publications:
* Domino, S. P., "On the subject of large-scale pool fires and turbulent boundary layer interactions", Phys. Fluids, 2024. (Featured)
* Domino, S. P., Wenzel, E. A, "A direct numerical simulation study for confined non-isothermal jet impingement at moderate nozzle-to-plate distances: capturing jet-to-ambient density effects", Int. J. Heat Mass Trans, 2023.
* Benjamin, M., Domino, S. P., Iaccarino, G., "Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges", Eur. Phys. J. E., 2023.
* Hubbard, J., Cheng, M., Domino, S. P., "Mixing in low-Reynolds number reacting impinging jets in crossflow", J. Fluids Engr., 2023.
* Domino, S. P. “Unstructured finite volume approaches for turbulence,” in Numerical Methods in Turbulence Simulation, edited by R. Moser (Elsevier, 2023), Ch. 7, pp. 285–317.
* Scott, S., Domino, S. P., "A computational examination of large-scale pool fires: variations in crosswind velocity and pool shape", Flow, 2022.
* Domino, S. P., Horne, W., "Development and deployment of a credible unstructured, six-DOF, implicit low-Mach overset simulation tool for wave energy applications", Renew. Energy, 2022.
* Hubbard, J., Hansen, M., Kirsch, J., Hewson, J., Domino, S. P., “Medium scale methanol pool fire model validation”, J. Heat Transfer, 2022.
* Barone, M., Ray, J., Domino, S. P., "Feature selection, clustering, and prototype placement for turbulence datasets", AIAA J., 2021,
* Domino, S. P., Hewson, J., Knaus, R., Hansen, M., "Predicting large-scale pool fire dynamics using an unsteady flamelet- and large-eddy simulation-based model suite", Phys. Fluids, 2021. (Editor's pick)
* Domino, S. P., "A case study on pathogen transport, deposition, evaporation and transmission: linking high-fidelity computational fluid dynamics simulations to probability of infection", Int. J. CFD, 2021.
* Domino, S. P., Pierce, F., Hubbard, J., "A multi-physics computational investigation of droplet pathogen transport emanating from synthetic coughs and breathing", Atom. Sprays, 2021.
* Jofre, L., Domino, S. P., Iaacarino, G., "Eigensensitivity analysis of subgrid-scale stresses in large-eddy simulation of a turbulent axisymmetric jet", Int. J. Heat Fluid Flow, 2019.
* Domino, S. P., Sakievich, P., Barone, M., "An assessment of atypical mesh topologies for low-Mach large-eddy simulation", Comp. Fluids, 2019.
* Domino, S. P., "Design-order, non-conformal low-Mach fluid algorithms using a hybrid CVFEM/DG approach ", J. Comput. Physics, 2018.
* Jofre, L., Domino, S. P., Iaacarino, G., "A Framework for Characterizing Structural Uncertainty in Large-Eddy Simulation Closures", Flow Turb. Combust., 2018.
CV: https://github.com/spdomin/Present/blob/master/cv/dominoCV.pdf -
Yiwen Dong
Research Asst - Graduate, Program-Noh, H.
BioYiwen Dong is a Ph.D. student in the Department of Civil and Environmental Engineering at Stanford University, advised by Prof. Hae Young Noh. Her research interest is human behavior characterization and health monitoring through their interactions with the physical structures. Her current work focuses on human and animal health monitoring through footstep/activity-induced structural vibrations.
While structures are traditionally considered as passive and indifferent, her works allow the structures to be both self-aware and user-aware. Yiwen developed systems that utilize ambient structural vibrations to infer human behaviors and health status, which enables many smart building applications such as in-home patient monitoring and elder care, intruder prevention and occupant management, animal health monitoring, and welfare. She strives for the next-generation intelligent infrastructures by exploring the potential of structural monitoring for human-centered purposes.
Yiwen has an interdisciplinary background in structural engineering, electrical engineering, and machine learning. Yiwen received her Master’s degree in Structural Engineering at Stanford University and her Bachelor’s degree in civil engineering at Nanyang Technological University. She won various awards (Best Paper Award, runner-ups in competitions) in ubiquitous computing and cyber-physical system conferences. She is passionate about combining the physical knowledge from structural dynamics, sensing approaches from cyber-physical systems, and data-driven models from machine learning to infer people’s behavior patterns and health status. -
David Donoho
Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences
BioDavid Donoho is a mathematician who has made fundamental contributions to theoretical and computational statistics, as well as to signal processing and harmonic analysis. His algorithms have contributed significantly to our understanding of the maximum entropy principle, of the structure of robust procedures, and of sparse data description.
Research Statement:
My theoretical research interests have focused on the mathematics of statistical inference and on theoretical questions arising in applying harmonic analysis to various applied problems. My applied research interests have ranged from data visualization to various problems in scientific signal processing, image processing, and inverse problems.
