Stanford University
Showing 271-280 of 407 Results
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Lloyd B. Minor, MD
The Carl and Elizabeth Naumann Dean of the School of Medicine, Vice President for Medical Affairs, Stanford University, Professor of Otolaryngology - Head and Neck Surgery and Professor of Neurobiology and of Bioengineering, by courtesy
Current Research and Scholarly InterestsThrough neurophysiological investigations of eye movements and neuronal pathways, Dr. Minor has identified adaptive mechanisms responsible for compensation to vestibular injury in a model system for studies of motor learning. Following his discovery of superior canal dehiscence, he published a description of the disorder’s clinical manifestations and related its cause to an opening in the bone covering of the superior canal. He subsequently developed a surgical procedure to correct the problem.
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Brando Miranda
Ph.D. Student in Computer Science, admitted Autumn 2022
BioBio
Brando Miranda is a current Ph.D. Student at Stanford University under the supervision of Professor Sanmi Koyejo in the department of Computer Science. Previously he has been a graduate student at University of Illinois Urbana-Champaign, Research Assistant at MIT’s Center for Brain Minds and Machines (CBMM), and graduate student at the Massachusetts Institute of Technology (MIT). Miranda’s research interests lie in the field of meta-learning, foundation models for theorem proving, and human & brain inspired Artificial Intelligence (AI). Miranda completed his Master of Engineering in Electrical Engineering and Computer Science under the supervision of Professor Tomaso Poggio – where he did research on Deep Learning Theory. Miranda has been the recipient of several awards, including Most Cited Paper Certificate awarded by International Journal of Automation & Computing (IJAC), two Honorable Mention with the Ford Foundation Fellowship, Computer Science Excellence Saburo Muroga Endowed Fellow, Stanford School of Engineering fellowship, and is currently an EDGE Scholar at Stanford University.
About me (Informal)
I am a scientist and an engineer that is interested in moving forward the powerful and beautiful field of A.I. closer to true Artificial General Intelligence (AGI). I believe an important direction is understanding how to combine cognitive and neuro-inspired models, specially investigating how reasoning and learning work together. In addition, I also believe being able to adapt to new tasks using prior experience and knowledge is crucial for AGI to occur. Consequently, I decided to pursue a Ph.D in AI and machine learning. I currently work on meta-learning and machine learning (ML) for Theorem Proving (TP) at Stanford University. -
Eduardo Miranda
Professor of Civil and Environmental Engineering
Current Research and Scholarly InterestsRegional seismic risk assessment, ground motion directionality
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Azalia Mirhoseini
Assistant Professor of Computer Science
BioAzalia Mirhoseini is an Assistant Professor of Computer Science at Stanford University where she directs Scaling Intelligence, a research lab focused on developing scalable and self-improving AI systems. She is a co-founder of Ricursive Intelligence, a frontier lab dedicated to recursive self-improvement through AI that designs the chips that fuel it. Previously, she spent several years in industry AI labs, including Google Brain, Anthropic, and Google DeepMind, working on Gemini and Claude, among other projects. Her past work includes Mixture-of-Experts (MoE) neural architectures, now predominantly used in leading frontier AI models; AlphaChip, a reinforcement learning approach for layout optimization used in the design of advanced chips like Google AI accelerators (TPUs) and data center CPUs; as well as pioneering research on LLM Test-Time Scaling. Her work has been recognized through the Okawa Research Grant, the Google ML and Systems Junior Faculty Award, MIT Technology Review's 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship venues such as Nature, and coverage by various media outlets, including WSJ, NYT, Forbes, MIT Technology Review, IEEE Spectrum, WIRED, and TechCrunch.
