Independent Labs, Institutes, and Centers (Dean of Research)
Showing 31-40 of 126 Results
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Rachel Manber, PhD
Professor of Psychiatry and Behavioral Sciences (General Psychiatry and Psychology-Adult)
On Partial Leave from 11/16/2024 To 11/15/2025Current Research and Scholarly InterestsRecent and current projects include
Treatment of insomnia during pregnancy
Treatment of insomnia comorbid with sleep apnea
Use of digital interventions for insomnia among middle age and older adults
Mobile intervention for insomnia among those with alcohol use -
Edward Manche, MD
Professor of Ophthalmology
BioEdward E. Manche, MD is Professor of Ophthalmology and Director of the Cornea and Refractive Surgery Service at Stanford University School of Medicine. He received his medical degree from Albert Einstein College of Medicine and completed residency training at the University of Medicine and Dentistry at New Jersey where he served as Chief Resident. He completed a two-year fellowship in Cornea and Refractive Surgery at the Jules Stein Eye Institute at UCLA.
Dr. Manche is a fellow of the American Academy of Ophthalmology and received its Achievement Award in 2003 and its Senior Achievement Award in 2014. He was elected to active membership in the American Ophthalmological Society in 2011, and is recognized in Best Doctors in America and Guide to America's Top Physicians. He serves on the editorial boards of the American Journal of Ophthalmology, Journal of Ophthalmology, Clinical and Experimental Ophthalmology and Journal of Refractive Surgery.
He lectures widely on topics in cornea and refractive surgery and has published over 130 peer-reviewed articles and 30 book chapters. -
Christopher Manning
Thomas M. Siebel Professor of Machine Learning, Professor of Linguistics, of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
On Leave from 01/01/2025 To 06/30/2025BioChristopher Manning is the inaugural Thomas M. Siebel Professor in Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). From 2010, Manning pioneered Natural Language Understanding and Inference using Deep Learning, with impactful research on sentiment analysis, paraphrase detection, the GloVe model of word vectors, attention, neural machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, and summarization, work for which he has received two ACL Test of Time Awards and the IEEE John von Neumann Medal (2024). He earlier led the development of empirical, probabilistic approaches to NLP, computational linguistics, and language understanding, defining and building theories and systems for Natural Language Inference, syntactic parsing, machine translation, and multilingual language processing, work for which he won ACL, Coling, EMNLP, and CHI Best Paper Awards. In NLP education, Manning coauthored foundational textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), and his online CS224N Natural Language Processing with Deep Learning course videos have been watched by hundreds of thousands. In linguistics, Manning is a principal developer of Stanford Dependencies and Universal Dependencies, and has authored monographs on ergativity and complex predicates. He is the founder of the Stanford NLP group (@stanfordnlp) and was an early proponent of open source software in NLP with Stanford CoreNLP and Stanza. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). Manning has a B.A. (Hons) from The Australian National University, a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023. He held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford.
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Andrew J. Mannix
Assistant Professor of Materials Science and Engineering
Current Research and Scholarly InterestsAtomically thin 2D materials incorporated into van der Waals heterostructures are a promising platform to deterministically engineer quantum materials with atomically resolved thickness and abrupt interfaces across macroscopic length scales while retaining excellent material properties. Because 2D materials exhibit a wide range of electronic characteristics with properties that often rival conventional electronic materials — e.g., metals, semiconductors, insulators, and superconductors — it is possible to combine them in virtually infinite variety to achieve diverse heterostructures. Furthermore, the van der Waals interface enables interlayer twist engineering to modify the interlayer symmetry, periodic potential (moiré superlattice), and hybridization, which has resulted in novel quantum states of matter. Many of these heterostructures, especially those involving specific interlayer twist angles, would be otherwise infeasible through direct growth.
The Mannix Group is developing a unique set of in-house capabilities to systematically elucidate the fundamental structure-property relationships underpinning the growth of 2D materials and their inclusion into van der Waals heterostructures. Greater understanding will allow us to provide a platform for engineering the properties of matter at the atomic scale and offer guidance for emerging applications in novel electronics and in quantum information science.
To accomplish this, we employ: precise growth techniques such as chemical vapor deposition and molecular beam epitaxy; automated van der Waals assembly; and atomically-resolved microscopy including cryo-STM/AFM. -
Wendy Mao
Professor of Earth and Planetary Sciences and of Photon Science
Current Research and Scholarly InterestsUnderstanding the formation and evolution of planetary interiors; experimental mineral physics; materials in extreme environments.
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Ivana Maric
Assistant Professor (Research) of Pediatrics (Neonatology)
BioIvana Maric is an Assistant Professor in the Pediatrics Department at the Stanford University School of Medicine. Her research focuses on applying machine learning to improving maternal and neonatal health. Her main focus has been on developing machine learning models for early prediction of adverse outcomes of pregnancy from omics and electronic health records data, that could guide development of low-cost, point of care diagnostic tools. Her main interest is in solutions that are applicable worldwide and especially in low-resource settings. Previously, her research focused on information theory, a mathematical discipline tightly related to statistics and machine learning. She is a recipient of the 2021 Rosenkranz Prize awarded for innovative work to improve health in low- or middle-income countries. She is also a co-recipient of the 2013 IEEE Communications Society Best Tutorial Paper Award.
She received BS degree from the University of Novi Sad, Serbia, MS and PhD at Rutgers University and postdoctoral training at Stanford University. She served as an Associate Editor for the IEEE Communications Letters from 2009 to 2012 and for the Trans. on Emerging Telecommunications Technologies from 2016 to 2018. -
Agostino Marinelli
Assistant Professor of Photon Science and of Particle Physics and Astrophysics
Current Research and Scholarly InterestsMy main research interests are the physics and applications of x-ray free-electron lasers. I lead the free-electron laser R&D program at the Linac Coherent Light Source at SLAC, where I employ new accelerator and FEL physics concepts to advance ultrafast X-ray science. Some highlights of my research are the development of attosecond x-ray free-electron lasers, and the use of advanced plasma accelerators for the generation of ultrafast radiation pulses.
