Stanford University
Showing 461-480 of 36,306 Results
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So Hee "Naomi" Ahn
Casual, Medicine - Med/Family and Community Medicine
BioNaomi is a fourth-year medical student at Seoul National University, expecting to graduate in February 2024. She earned her bachelor's degree Summa Cum Laude from Washington University in St. Louis in December 2018, majoring in Biology and minoring in Chinese Language & Culture. Although she has quite a long way to go before becoming a compassionate physician-scientist, Naomi has accumulated many years of research and clinical experience in the field of medicine, ranging from the molecular level to the population level. Her research interests lie in genomics, psychosomatic medicine, and global health.
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T. M. Jensen Ahokovi
Graduate, Economics
BioI’m a predoctoral research fellow at the Stanford Institute for Economic Policy Research (SIEPR) and the STAX Lab (Stanford Initiative on Business, Taxation, and Society) at the Graduate School of Business, where I work with Professors Ran Abramitzky and Rebecca Lester.
My interests lie at the intersection of labor and urban economics, public finance, and economic history. I'm particularly interested in how labor markets and cities evolve over time—and how government interventions through taxation, regulation, and social programs shape both individual trajectories and broader economic outcomes.
Previously, I was a research assistant in the Economic Policy Studies department at the American Enterprise Institute (AEI), where I primarily supported the work of PhD economists and Senior Fellows Stan Veuger, Vincent Smith, and Paul Kupiec.
I earned my BA in the Quantitative Economics Concentration from the University of Hawai‘i at Mānoa in summer 2024. Before AEI, I held research roles at the University of Hawai‘i Economic Research Organization (UHERO), the Center for Entrepreneurship and Economic Education at Hawai‘i Pacific University, and the Grassroot Institute of Hawai‘i. I plan to pursue a PhD in economics and/or public policy in the near future. -
Neera Ahuja
Professor of Medicine (Hospital Medicine)
Current Research and Scholarly InterestsClinical inpatient trials, Quality improvement, Assessing interventions with operations on throughput. SDOH/Health equity
Medical education research; Intergenerational teaching/learning; Analysis of effects of duty hour regulations on housestaff training and ways to improve the system -
Changzhi Ai
Postdoctoral Scholar, Photon Science, SLAC
BioChangzhi Ai is a Postdoctoral Researcher at the SUNCAT Center for Interface Science and Catalysis at Stanford University and SLAC National Accelerator Laboratory. He specializes in developing machine learning models for surface and interfacial chemistry, with broader expertise in atomistic modeling for materials science and chemistry. His research also explores agentic AI for scientific discovery, automation of active learning workflows, global optimization algorithms, and high-throughput materials screening. He obtained his PhD from the Technical University of Denmark.
His current research focuses on the development of scalable, physically informed machine learning potentials, particularly equivariant neural network architectures, for accurately modeling complex chemical environments. His work spans heterogeneous catalysis, multi-metallic alloy design, reaction kinetics, and surface and interfacial chemistry, with an emphasis on uncovering structure–property relationships at the atomic scale.
In addition, he has extensive experience integrating machine learning models into simulation pipelines and deploying them in large-scale computational environments. His technical expertise includes deep learning frameworks such as PyTorch, distributed training (DDP and multi-node GPU systems), and scientific computing tools including LAMMPS, ASE, and TorchScript/LibTorch for production-level deployment. He also develops end-to-end automated workflows for data generation, model training, and adaptive sampling in materials discovery.
Keywords:
Machine Learning Potentials (Equivariant GNNs), Atomistic Simulations, Molecular Dynamics, Active Learning & Workflow Automation, High-Throughput Screening, Global Optimization Algorithms, Scientific Machine Learning, Distributed GPU Computing, PyTorch & TorchScript, LAMMPS Integration, ASE, HPC Systems, Data-Driven Materials Discovery
Code & Projects:
GitHub: https://github.com/changzhiai -
Meghali Aich
Postdoctoral Scholar, Neonatal and Developmental Medicine
BioMy research interest lies in understanding how environmental factors contribute to neurodevelopmental disorders and translating those insights into therapies. Aligned with this, my current research in Dr. Anca Pasca’s lab at Stanford focuses on how reductive stress associated with maternal metabolic syndrome affects fetal brain development.
