School of Engineering
Showing 221-240 of 455 Results
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Michael LoCascio
Postdoctoral Scholar, Civil and Environmental Engineering
BioMichael's work focuses on wind energy at the intersection of computational fluid dynamics, controls, and optimization. He is interested in wake modeling, wind farm layout optimization, and large eddy simulations of wind farm flows. He is currently working on a low-cost model for the annual energy production of wind farms. Michael is also a graduate researcher at the National Wind Technology Center, a research facility of the National Renewable Energy Laboratory. He received his Master of Science in Mechanical Engineering from Stanford in 2023 and his Bachelor of Science in Mechanical Engineering from UCLA in 2020.
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Lu Lu
Postdoctoral Scholar, Mechanical Engineering
BioDr. Lu Lu is currently a postdoctoral researcher at Stanford University. He received his B.S. and Ph.D. degrees from Ningbo University and Shanghai University in China in 2014 and 2019, respectively. He then worked as a postdoctoral researcher at Peking University from 2020 to 2022 before joining Stanford. His research interests focus on solid mechanics, with emphasis on mechanical instabilities, deployable structures, mechanics of intelligent soft materials, plate and shell theories, and nonlocal elasticity. He has published nearly 30 peer-reviewed papers in journals such as PNAS, JMPS, IJSS, AMR, IJMS, JAM, and PRSA, and received the ASME Melville Medal in 2024.
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Viviana Macarelli
Postdoctoral Scholar, Bioengineering
BioViviana earned her PhD in Clinical Biochemistry from the University of Cambridge (UK) in 2024, where she focused on the role of primary cilia in metabolic sensing by the hypothalamus. She then joined the Lundberg lab as a postdoc for a project in collaboration with the Chan Zuckerberg Imaging Institute. She will focus on characterizing primary cilia in the adult brain using human induced pluripotent stem cells (hIPSC).
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Anders Gjølbye Madsen
Graduate Visiting Researcher Student, Computer Science
BioAnders Gjølbye Madsen is a PhD fellow at the Technical University of Denmark. His research focuses on trustworthy machine learning for healthcare, with an emphasis on explainability, interpretability, and reliable evaluation of models in high-stakes settings. He works broadly with modern deep learning methods, including self-supervised learning, and is interested in questions of robustness and alignment. He is the author of PatternLocal, a NeurIPS 2025 paper on reducing false-positive attributions in explanations of non-linear models by refining local explanation approaches. He earned a BSc in Artificial Intelligence and Data from DTU and completed an MSc in Engineering in Applied Mathematics at DTU, including a study exchange in Computational Science and Engineering at ETH Zürich. Anders will spend 2026 as a visiting researcher at Stanford University’s Trustworthy AI Research (STAIR) Lab, working with Professor Sanmi Koyejo.
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Alam Mahmud
Postdoctoral Scholar, Chemical Engineering
BioA curious individual, seeking truth and exploring wonders, as ever
