School of Humanities and Sciences
Showing 961-980 of 2,017 Results
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Xing Liang
Basic Life Res Scientist
Current Research and Scholarly InterestsMechanism of MT polarity establishment during PVD neuron dendrite outgrowing in C. elegans.
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Jared Duker Lichtman
Szego Assistant Professor of Mathematics
BioJared Duker Lichtman is a Szegő Assistant Professor in the Department of Mathematics. Jared earned his doctorate in 2023 at the University of Oxford, supervised by Prof. James Maynard.
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Andrei Linde
Humanities and Sciences Professor, Emeritus
BioWhat is the origin and the global structure of the universe?
For a long time, scientists believed that our universe was born in the big bang, as an expanding ball of fire. This scenario dramatically changed during the last 35 years. Now we think that initially the universe was rapidly inflating, being in an unstable energetic vacuum-like state. It became hot only later, when this vacuum-like state decayed. Quantum fluctuations produced during inflation are responsible for galaxy formation. In some places, these quantum fluctuations are so large that they can produce new rapidly expanding parts of the universe. This process makes the universe immortal and transforms it into a multiverse, a huge fractal consisting of many exponentially large parts with different laws of low-energy physics operating in each of them.
Professor Linde is one of the authors of inflationary theory and of the theory of an eternal inflationary multiverse. His work emphasizes the cosmological implications of string theory and supergravity.
Current areas of focus:
- Construction of realistic models of inflation based on supergravity and string theory
- Investigation of conceptual issues related to the theory of inflationary multiverse -
Scott W Linderman
Assistant Professor of Statistics
BioScott Linderman, PhD, is an Assistant Professor at Stanford University in the Statistics Department and the Wu Tsai Neurosciences Institute, as well as the Co-Director of the Stanford Center for Neural Data Science. His research focuses on machine learning, computational neuroscience, and the general question of how computational and statistical methods can help to decipher neural computation. His work combines novel methodological development in the areas of state space models, deep generative models, point processes, and approximate Bayesian inference with applied statistical analyses of large-scale neural and behavioral data. Previously, he was a postdoctoral fellow at Columbia University and a graduate student at Harvard University. His work has been recognized with a Savage Award from the International Society for Bayesian Analysis, an AISTATS Best Paper Award, an NSF CAREER Award, and fellowships from the McKnight, Sloan, and Simons Foundations.
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John Lipa
Professor (Research) of Physics, Emeritus
BioJohn Lipa received his PhD at the University of Western Austrailia. He has acted as an assistant professor, senior research associate, and professor at Stanford University. Research interests include testing of various aspects of the renormalization group theory of cooperative phase transitions.
