School of Engineering
Showing 381-400 of 6,719 Results
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Michelle Q. Wang Baldonado
Research Scientist
Current Research and Scholarly InterestsMichelle is currently exploring the space of robotics systems for older adults. Working to bridge the robotics and senior communities, she is especially interested in robots that encourage older adults to develop and maintain healthy habits as they age, with a focus both on reducing social isolation and on encouraging physical activity and time outdoors.
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Jon Ball
Ph.D. Student in Education, admitted Autumn 2020
Ph.D. Minor, Computer ScienceBioHi! I'm a 3rd year PhD Student in Education Data Science dedicated to improving information accessibility.
Recent projects include:
Natural Language Processing: language analytics for Open Journal Systems (OJS)
Graph ML: modeling citation networks of computer science publications (OJS/arXiv)
Social Network Analysis: clustering of philanthropic partnerships for the Jim Joseph Foundation (SF) -
Nicholas Bambos
Richard W. Weiland Professor in the School of Engineering and Professor of Electrical Engineering
BioNick Bambos is R. Weiland Professor in the School of Engineering at Stanford University, having a joint appointment in the Department of Electrical Engineering and the Department of Management Science & Engineering. He has been the Fortinet Founders Department Chair of the Management Science & Engineering Department (2016 – 20).
He heads the Computer Systems Performance Engineering Lab (Perf-Lab) at Stanford, comprised of doctoral students and industry visitors engaged in various research projects, and was the Director (1999 – 2005) of the Stanford Networking Research Center (a research project of about $30M). He has published over 300 peer-reviewed research publications and graduated over 40 doctoral students (including two post-doctoral ones), who have moved on to leadership positions in academia, the Silicon Valley industries and technology startups, finance and venture capital, etc.
His research interests are in architecture and high-performance engineering of computer systems and networks, as well as data analytics with an emphasis on medical and health-care analytics. His research contributions span the areas of networking and the Internet, cloud computing and data centers, multimedia streaming, computer security, digital health, etc. His methodological interests and contributions span the areas of network control, online task scheduling, routing and distributed processing, machine learning and artificial intelligence, etc.
He received his Ph.D. (1989) in Electrical Engineering & Computer Sciences from the University of California at Berkeley. Before joining Stanford in 1996, he served as assistant professor (1989 – 95) and tenured associate professor (1995 – 96) of Electrical Engineering at the University of California at Los Angeles (UCLA).
He has received several best research paper awards and has been the Cisco Systems Faculty Development Chair and the David Morgenthaler Faculty Scholar at Stanford. He has won the IBM Faculty Award, as well as the National Young Investigator Award and the Research Initiation Award from the National Science Foundation. He has been a Berkeley U.C. Regents Fellow, an E. C. Anthony Fellow, and a D. & S. Gale Fellow.
He has served on various editorial boards of research journals, scientific boards of research labs, international technical and scientific committees, and technical review panels for networking and computing technologies. He has also served on corporate technical boards, as consultant and co-founder of technology start-up companies, and as expert witness in high-profile patent litigation and other legal cases involving information technologies. -
Sujay Banerjee
Masters Student in Bioengineering, admitted Autumn 2025
Current Research and Scholarly InterestsI develop deep learning models for genomic and molecular data to advance precision medicine. My work spans deep learning-based methods for structural variant detection in genome sequencing, diabetetes risk prediction, and protein–ligand binding affinities predicion. I’m broadly interested in how AI can accelerate drug discovery, uncover disease mechanisms, and improve individualized healthcare.
