Stanford University
Showing 21-30 of 2,733 Results
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Salaar Ahmed
Postdoctoral Scholar, Neurosurgery
BioSalaar Ahmed, MD, is a Postdoctoral Research Scholar in the Ramayya Lab within the Department of Neurological Surgery at Stanford University School of Medicine. His research focuses on the mechanisms and novel treatments of chronic and cancer-related pain, neuromodulation, disorders of consciousness, and global neurosurgery.
Dr. Ahmed earned his MD from Aga Khan University in January 2026, graduating summa cum laude, with a record 18 university awards and 15 honors. His early research focused on Diffuse Intrinsic Pontine Glioma (DIPG), pediatric neuro-oncology, and global neurosurgical outcomes under the mentorship of Dr. Ather Enam and Dr. Naureen Mushtaq. He also collaborated on research projects with investigators from the University of Minnesota, the University of Wisconsin–Madison, and Mayo Clinic Rochester.
Beyond his academic work, Dr. Ahmed served as President of the student wing of Child Protection Services (CPS) at Aga Khan University Hospital. As a high school student, he founded Masoom Jaan, a community initiative that positively impacted the lives of more than 1,000 children in Rahim Yar Khan, his hometown in Pakistan. He later co-founded the Student Neurosurgery and Oncology Research Consortium (SNORC), an international mentorship and research initiative that has connected medical students with neurosurgical faculty mentors and expanded access to research opportunities across multiple countries. In addition, Salaar has worked extensively on HIV stigma and public health research, focusing on the MSM and transgender communities, and continues to collaborate with investigators at Aga Khan University.
Dr. Ahmed has presented his work at numerous international scientific meetings, including the Congress of Neurological Surgeons (CNS), the American Association of Neurological Surgeons (AANS), the Society for Neuro-Oncology (SNO), and the International AIDS Conference. -
Tazbir Ahmed
Postdoctoral Scholar, Ophthalmology
BioDr. Tazbir Ahmed is a clinician-scientist with a focus on neuro-ophthalmology and vision science, bringing expertise in translational research, clinical trials, and medical education. He obtained his medical degree and licensure through the Bangladesh Medical and Dental Council and achieved board certification in Ophthalmology from the Bangladesh College of Physicians and Surgeons.
Motivated by a deep interest in ocular neurodegeneration, inflammation, and metabolic eye disorders, Dr. Ahmed pursued a PhD in Ophthalmology at the University of Tokyo School of Medicine. His doctoral research explored the use of biologics, ocular devices, and experimental models of inflammation to investigate retinal and optic nerve changes in glaucoma, optic neuropathies, and age-related visual decline.
Dr. Ahmed’s multidisciplinary research integrates preclinical disease models, neuroimaging, ocular histochemistry, omics technologies, and electrophysiological methods to elucidate mechanisms of visual pathway dysfunction. He also leverages data science tools to address key issues in ocular public health. -
Jeesung Ahn
Postdoctoral Scholar, Psychiatry
Current Research and Scholarly InterestsMy research focuses on translating neuroscience into real-world solutions by leveraging brain function as a biomarker to advance precision in depression treatment and develop personalized approaches to mental and behavioral health care.
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Changzhi Ai
Postdoctoral Scholar, Photon Science, SLAC
BioChangzhi Ai is a Postdoctoral Researcher 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 (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 -
Agnideep “Agni” Aich, PhD
Postdoctoral Scholar, Emergency Medicine
Current Research and Scholarly InterestsAgni's research develops interpretable statistical machine learning methods for clinical, biomedical, and population health data, with interests spanning dependence-aware learning and copula-based methods, extreme-event modeling, predictive modeling, supervised feature selection, and AI in healthcare. At the HEAL Lab, he analyzes clinical workflows and AI implementation to advance understanding of the human experience in healthcare, emphasizing practical, interpretable, human-centered outcomes.
