School of Engineering
Showing 1-50 of 112 Results
-
Cynthia Bailey
Senior Lecturer of Computer Science
Current Research and Scholarly InterestsI have a PhD in Computer Science from the University of California, San Diego, in the area of High-Performance Computing (HPC), specifically market-based scheduling algorithms. My graduate research was done as part of San Diego Supercomputer Center (SDSC)'s Performance Modeling and Characterization Lab (PMaC), where I investigated economic models of scheduling on high performance computing systems. My adviser was Allan Snavely of SDSC.
My dissertation abstract is as follows: Effective management of Grid and HPC resources is essential to maximizing return on the substantial infrastructure investment these resources entail. An important prerequisite to effective resource management is productive interaction between the user and scheduler. My work analyzes several aspects of the user-scheduler relationship and develops solutions to three of the most vexing barriers between the two. First, users' monetary valuation of compute time and schedule turnaround time is examined in terms of a utility function. Second, responsiveness of the scheduler to users' varied valuations is optimized via a genetic algorithm heuristic, creating a controlled market for computation. Finally, the chronic problem of inaccurate user runtime requests, and its implications for scheduler performance, is examined, along with mitigation techniques.
My current research projects are in the area of Computer Science Education, with an emphasis on assessment and the use of Peer Instruction pedagogy in lecture. With colleagues Mark Guzdial, Leo Porter, and Beth Simon, I run the New CS Faculty Teaching Workshop, an annual "bootcamp" on how to teach effectively that draws attendees from dozens of the top CS programs in the country. The short-term goal is to give newly-hired faculty entering their first year of teaching the skills they need to succeed for themselves and their students. The long-term goal is to transform undergraduate education in CS by seeding our best rising stars with best practices so they can create communities of practice as their institutions and mentor their students in active learning strategies, creating a culture where these are the new norm. -
Jon Ball
Ph.D. Student in Education, admitted Autumn 2020
Ph.D. Minor, Computer Science
Other Tech - Graduate, SAL Digital LearningCurrent Role at StanfordResearch Assistant (GSE)
Teaching Assistant (STS) -
Clark Barrett
Professor (Research) of Computer Science
Current Research and Scholarly InterestsAutomated reasoning; satisfiability modulo theories (SMT); formal methods;
formal verification; verification of smart contracts; verification of neural
networks; AI safety; security; hardware design productivity and verification. -
Gill Bejerano
Professor of Developmental Biology, of Computer Science, of Pediatrics (Genetics) and of Biomedical Data Science
Current Research and Scholarly Interests1. Automating monogenic patient diagnosis.
2. The genomic signatures of independent divergent and convergent trait evolution in mammals.
3. The logic of human gene regulation.
4. The reasons for sequence ultraconservation.
5. Cryptogenomics to bridge medical silos.
6. Cryptogenetics to debate social injustice.
7. Managing patient risk using machine learning.
8. Understanding the flow of money in the US healthcare system. -
Michael Bernstein
Associate Professor of Computer Science
BioMichael Bernstein is an Associate Professor of Computer Science at Stanford University, where he is a Bass University Fellow and Interim Director of the Symbolic Systems program. His research focuses on designing social, societal, and interactive technologies. This research has been reported in venues such as The New York Times, Wired, Science, and Nature. Michael has been recognized with an Alfred P. Sloan Fellowship, the UIST Lasting Impact Award, and the Computer History Museum's Patrick J. McGovern Tech for Humanity Prize. He holds a bachelor's degree in Symbolic Systems from Stanford University, as well as a master's degree and a Ph.D. in Computer Science from MIT.