School of Engineering
Showing 1-27 of 27 Results
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Zherui Han
Postdoctoral Scholar, Electrical Engineering
BioZherui Han received his Ph.D. (2024) in Mechanical Engineering from Purdue University, and B.S. (2019) in Energy and Power Engineering from Huazhong University of Science and Technology in China. He is a recipient of Purdue's Ross Fellowship and Bilsland Dissertation Fellowship. He is now a postdoc at Stanford developing theory for thermal and electronic transport in 2D systems and devices. His prior works include first-principles modeling of phonon dynamics.
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Nicos Haralabidis
Postdoctoral Scholar, Bioengineering
BioMy research interests lie within both sports and clinical biomechanics applications. I rely upon merging conventional biomechanical in vivo measurements together with state-of-the-art musculoskeletal modeling and optimal control simulation approaches. The integrative approach I take enables me to understand how an individual may run faster, jump further, walk following surgery or intervention, and simultaneously estimate internal body dynamics noninvasively. As a Postdoctoral Research Scholar within the Wu Tsai Human Performance Alliance I aim to explore how stochastic optimal control and reinforcement learning methods can be applied to further our understanding of sporting performance.
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Aoife Henry
Postdoctoral Scholar, Mechanical Engineering
BioAoife Henry earned her doctorate in Electrical, Computer & Energy Engineering at the University of Colorado, Boulder, funded by and in collaboration with the wind energy control systems team at the National Renewable Energy Laboratory (NREL). During her doctorate, she applied her joint specializations of machine learning and control systems to implement and validate forecast-enabled wind energy controllers using state-of-the-art time-series forecasting models. She is now working to commercialize and scale this technology under the wing of the Stanford Sustainability Accelerator Fellowship at the Doerr School of Sustainability.
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Anh Tuan Hoang
Postdoctoral Scholar, Materials Science and Engineering
BioAnh Tuan Hoang is a postdoctoral scholar at Stanford University, where he is working with Prof. Eric Pop and Prof. Andrew Mannix. Hoang received his Ph.D. (2022) in Electrical and Electronic Engineering from Yonsei University and his M.S. (2016) in Bionano Engineering from Hanyang University, supported by the BK21+ Fellowship. Before that, he earned his B.S. degree (2014) in Chemical Engineering from Hanoi University of Science and Technology. Hoang's research interests span various fields, including colorimetric sensors, chemical analysis, displays, flexible and wearable devices, crystallography, and semiconductor physics. During his time at Stanford, he focused primarily on the wafer-scale synthesis and characterization of 2D semiconductors.
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Xuandi Hou
Postdoctoral Scholar, Materials Science and Engineering
BioXuandi Hou's research focuses on integrating nanotools and physical stimuli to gain insights into neural circuits and achieve precise remote manipulation of neural activity. His ultimate aspiration is to develop comprehensive toolkits that facilitate the exploration of the biophysical mechanisms underlying non-invasive transcranial ultrasound brain stimulation, offering applications in both neuroscience and neurology.
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Yifan Hou
Postdoctoral Scholar, Electrical Engineering
BioI am a Post Doctoral researcher working with Prof. Shuran Song at Stanford Electric Engineering. Prior to joining Stanford, I spent three years as an Applied Scientist at Amazon Robotics working on the Stow project. I obtained my PhD and MS degrees from the Robotics Institute at Carnegie Mellon University, obtained BoE from the department of Automation at Tsinghua University. I had also spent time interning at Toyota Research Institute and MIT.
I work on robotic manipulation. I am currently interested in the intersection of data-driven visual motor policies and model based compliance control. -
Pei Huang (黄 沛)
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsAutomated Reasoning, Trustworthy AI, Neural Symbolic Methods, Constraint Solving
