School of Engineering
Showing 3,451-3,500 of 6,016 Results
-
Teresa Meng
Reid Weaver Dennis Professor in Electrical Engineering and Professor of Computer Science, Emerita
BioTeresa H. Meng is the Reid Weaver Dennis Professor of Electrical Engineering, Emerita, at Stanford University. Her research activities in the first 10 years focused on low-power circuit and system design, video signal processing, and wireless communications. In 1998, Prof. Meng took leave from Stanford and founded Atheros Communications, Inc., which developed semiconductor system solutions for wireless network communications products. After returning to Stanford in 2000 to continue her teaching and research, Prof. Meng turned her research interest to applying signal processing and IC design to bio-medical engineering. She collaborated with Prof. Krishna Shenoy on neural signal processing and neural prosthetic systems. She also directed a research group exploring wireless power transfer and implantable bio-medical devices. Prof. Meng retired from Stanford in 2013.
-
Jeannie Meyer
Associate Director of Events, School of Engineering - External Relations
Current Role at StanfordPlan and coordinate donor relations, alumni relations and student outreach activities for the Dean's office in the School of Engineering.
-
Bennet Meyers
Adjunct Professor, Electrical Engineering
BioI am a Staff Scientist with SLAC National Accelerator Laboratory, in the Grid Integration Systems and Mobility (GISMo) Lab in the Applied Energy Division. I completed my PhD in Electrical Engineering at Stanford University in Winter 2023, advised by Prof. Stephen Boyd. We recently wrote a book on signal decomposition, which can be found under my publications tab. More info available on my personal website.
-
David Miller
W.M. Keck Foundation Professor of Electrical Engineering, Emeritus
Current Research and Scholarly InterestsDavid Miller’s research interests include the use of optics in switching, interconnection, communications, computing, and sensing systems, physics and applications of quantum well optics and optoelectronics, and fundamental features and limits for optics and nanophotonics in communications and information processing.
-
Kyle Iman Miller
Undergraduate, Materials Science and Engineering
BioI'm a 2024 graduate of South Eugene High School in Oregon, passionate about triathlons, wilderness exploration, and environmental sustainability.
-
Marek Miltner
Affiliate, Program-Rajagopal, R.
BioMarek is a researcher and postgraduate student in the fields of Artificial Intellignence for Energy Sustainability, and Technology Policy connected to it. He has also been teaching Computer Science courses at university level since 2018, and at Stanford since 2020.
He has received an MPhil in Technology Policy from the University of Cambridge (UK), and an MEng in Innovation Management and Artificial Intelligence from Czech Technical University (EU). In the past, he has led a research team that built the first autonomous electric vehicle in the Czech Republic. -
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.
-
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
-
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.
