The Computing and Mathematical Sciences PhD
Why start a new PhD program?
We are in the midst of an unprecedented convergence of disciplines
Math
Medicine
Psychology
Biology
Neuroscience
…it’s harder & harder to tell faculty, postdocs, and students apart
Omer Tamuz
Math PhD, CS Postdoc, Joining Caltech as faculty in Economics
Na (Lina) Li
PhD work involved Economics, Control, Energy, and Physiology
…even Nobel prizes are starting to go increasingly to this intersection
2012 Nobel Prize in Economics awarded for “the theory of stable allocations
and the practice of market design”  recipients are very active in
Algorithmic Game Theory, within computer science / electrical engineering
2013 Nobel Prize in Chemistry awarded for “the development of multiscale
models for complex systems”  hailed as an award for computer science
We are in the midst of an unprecedented convergence of disciplines
Math
Medicine
Psychology
Biology
Neuroscience
From this convergence, a new core has emerged
Probability
Optimization
Algorithms
Learning
Math
Medicine
Psychology
Biology
Neuroscience
The core is crucial for progress in traditional areas
Probability
Optimization
Algorithms
Learning
Math
Medicine
Psychology
Biology
Neuroscience
…and is the foundation for many emerging fields
Complex Systems
Probability
Optimization
Algorithms
Learning
Smart Grid/City/*
Network Science
EE / CS / Control / …
⊇
Traditional programs do not teach this core
We need something new
Probability
Optimization
Algorithms
Learning
A key driver for research
and education at Caltech
Probability
Optimization
Algorithms
Learning
A key driver for research
and education at Caltech
Probability
Optimization
Algorithms
Learning
A new PhD program
The core is dominating recent hiring
Adam Wierman
Katrina Ligett
Matt Elliot
Omer Tamuz
Joel Tropp
Venkat Chandrasekaran
Yisong Yue
Thomas Vidick
The Computing & Mathematical Sciences (CMS) PhD
Core: Unique, interdisciplinary courses on
Breadth: Sample a few application areas
Depth: Choose a “focus” application area to study
Probability
Optimization
Algorithms
Learning
Faculty involvement:
James Beck, Shuki Bruck, Oscar Bruno, Joel Burdick, Venkat Chandrasekaran, Mani Chandy, Mathieu
Desbrun, John Doyle, Federico Echenique, Michelle Effros, Matthew Elliott, Ben Gillen, Babak Hassibi, John
Ledyard, Katrina Ligett, Steven Low, Richard Murray, Houman Owhadi, Pietro Perona, Leonard Schulman,
Peter Schroeder, Matt Shum, Omer Tamuz, Joel Tropp, Chris Umans, P. P. Vaidyanathan, Thomas Vidick,
Adam Wierman, Yisong Yue.
...have your best undergrads apply!