Stanford University
Showing 551-600 of 762 Results
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Krishna Saraswat
Rickey/Nielsen Professor in the School of Engineering and Professor, by courtesy, of Materials Science and Engineering
Current Research and Scholarly InterestsNew and innovative materials, structures, and process technology of semiconductor devices, interconnects for nanoelectronics and solar cells.
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Tracy Schloemer
Postdoctoral Scholar, Electrical Engineering
BioTracy H. Schloemer earned her B.S. in chemistry and M.A. in educational studies from the University of Michigan. She taught high school chemistry in Denver, Colorado as a Knowles Teaching Initiative fellow and served as a lead contributor to ChemEdX. She earned her Ph.D. in applied chemistry from the Colorado School of Mines in 2019 where she focused on organic semiconductor design for improved operational durability of perovskite solar cells under professor Alan Sellinger and in collaboration with the National Renewable Energy Lab. Her current research focuses on the control and application of excitons in the Congreve Lab. Her interests outside the lab include hiking and cheering on University of Michigan “sportsball”.
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Dustin Schroeder
Associate Professor of Geophysics, of Electrical Engineering and Senior Fellow at the Woods Institute for the Environment
BioMy research focuses on advancing the scientific and technical foundations of geophysical ice penetrating radar and its use in observing and understanding the interaction of ice and water in the solar system. I am primarily interested in the subglacial and englacial conditions of rapidly changing ice sheets and their contribution to global sea level rise. However, a growing secondary focus of my work is the exploration of icy moons. I am also interested in the development and application of science-optimized geophysical radar systems. I consider myself a radio glaciologist and strive to approach problems from both an earth system science and a radar system engineering perspective. I am actively engaged with the flow of information through each step of the observational science process; from instrument and experiment design, through data processing and analysis, to modeling and inference. This allows me to draw from a multidisciplinary set of tools to test system-scale and process-level hypotheses. For me, this deliberate integration of science and engineering is the most powerful and satisfying way to approach questions in Earth and planetary science.
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Debbie Senesky
Associate Professor of Aeronautics and Astronautics, of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy
BioDebbie G. Senesky is an Associate Professor at Stanford University in the Aeronautics and Astronautics Department and the Electrical Engineering Department. In addition, she is the Principal Investigator of the EXtreme Environment Microsystems Laboratory (XLab). Her research interests include the development of nanomaterials for extreme harsh environments, high-temperature electronics for Venus exploration, and microgravity synthesis of nanomaterials. In the past, she has held positions at GE Sensing (formerly known as NovaSensor), GE Global Research Center, and Hewlett Packard. She received the B.S. degree (2001) in mechanical engineering from the University of Southern California. She received the M.S. degree (2004) and Ph.D. degree (2007) in mechanical engineering from the University of California, Berkeley. Prof. Senesky is the Site Director of nano@stanford. She is currently the co-editor of two technical journals: IEEE Journal of Microelectromechanical Systems and Sensors. In recognition of her research, she received the Emerging Leader Abie Award from AnitaB.org in 2018, Early Faculty Career Award from the National Aeronautics and Space Administration (NASA) in 2012, Gabilan Faculty Fellowship Award in 2012, and Sloan Ph.D. Fellowship from the Alfred P. Sloan Foundation in 2004.
Prof. Senesky's career path and research has been featured by Scientific American, Seeker, People Behind the Science podcast, The Future of Everything radio show, Space.com, and NPR's Tell Me More program. More information about Prof. Senesky can be found at https://xlab.stanford.edu and on Instagram (@astrodebs). -
Karan P. Singh
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioI am an incoming electrical engineering Ph.D. student and full-time post-baccalaureate researcher, currently advised by Dr. Kim Butts Pauly in the Department of Radiology. My research will be funded by the NSF Graduate Research Fellowship.
My lab works primarily in transcranial ultrasound neuromodulation, a non-invasive therapeutic modality with the potential to cure neurological diseases such as epilepsy, Alzheimer's, and even addiction. My primary focus at the moment is using machine learning, particularly sequence models, to improve therapy outcomes and efficiency.
Previously, I studied electrical engineering at Cal Poly SLO and was the youngest engineering graduate in the school's history. There, I worked with Dr. Benjamin Hawkins on microfluidics research examining the electrowetting effect.
Outside of academia, I enjoy playing the piano, badminton, working out, and cooking! I am also the co-founder and co-president of the Stanford Piano Society. -
Hyongsok Tom Soh
Professor of Radiology (Early Detection), of Electrical Engineering, of Bioengineering and, by courtesy, of Chemical Engineering
BioDr. Soh received his B.S. with a double major in Mechanical Engineering and Materials Science with Distinction from Cornell University and his Ph.D. in Electrical Engineering from Stanford University. From 1999 to 2003, Dr. Soh served as the technical manager of MEMS Device Research Group at Bell Laboratories and Agere Systems. He was a faculty member at UCSB before joining Stanford in 2015. His current research interests are in analytical biotechnology, especially in high-throughput screening, directed evolution, and integrated biosensors.
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Olav Solgaard
Director, Edward L. Ginzton Laboratory and Robert L. and Audrey S. Hancock Professor in the School of Engineering
BioThe Solgaard group focus on design and fabrication of nano-photonics and micro-optical systems. We combine photonic crystals, optical meta-materials, silicon photonics, and MEMS, to create efficient and reliable systems for communication, sensing, imaging, and optical manipulation.
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Shuran Song
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioShuran Song is an Assistant Professor of Electrical Engineering at Stanford University. Before joining Stanford, she was faculty at Columbia University. Shuran received her Ph.D. in Computer Science at Princeton University, BEng. at HKUST. Her research interests lie at the intersection of computer vision and robotics. Song’s research has been recognized through several awards, including the Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21, RSS’19, and finalists at RSS, ICRA, CVPR, and IROS. She is also a recipient of the NSF Career Award, Sloan Foundation fellowship as well as research awards from Microsoft, Toyota Research, Google, Amazon, and JP Morgan.
To learn more about Shuran’s work, please visit: https://shurans.github.io/ -
Daniel Spielman
Professor of Radiology (Radiological Sciences Lab) and, by courtesy, of Electrical Engineering
On Partial Leave from 05/15/2024 To 08/14/2024Current Research and Scholarly InterestsMy research interests are in the field of medical imaging, particularly magnetic resonance imaging and in vivo spectroscopy. Current projects include MRI and MRS at high magnetic fields and metabolic imaging using hyperpolarized 13C-labeled MRS.
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Kavya Sreedhar
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
BioKavya Sreedhar is an electrical engineering PhD candidate advised by Mark Horowitz. Her research interests include architecture design and developing hardware accelerators for cryptography and machine learning applications. On the cryptography side, she has worked on designing a fast extended GCD accelerator for constant-time modular inversion and verifiable delay functions. On the deep learning side, she is working on dynamically adapting the execution of state-of-the-art models for use in real-time systems and accelerating dynamic transformer models for computer vision in an ongoing collaboration with NVIDIA. She previously worked with the Agile Hardware (AHA) Project in developing Lake, a parameterizable memory generator that can be configured at runtime to support different image processing and machine learning applications. As part of her research, she has worked on taping out three chips in SKY130nm, GF12nm, and TSMC16nm. Kavya is supported by the Quad Fellowship (2023 to 2024) and Stanford's Knight-Hennessy Graduate Fellowship (2019 to 2022). She received a B.S. in Electrical Engineering and BEM (Business, Economics, & Management) from Caltech in 2019 and a M.S. in Electrical Engineering from Stanford in 2021.
