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- Avrim Blum
(avrim at ttic.edu)
- Professor and Chief Academic Officer
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Toyota Technological Institute at Chicago (TTIC)
- 6045 S. Kenwood Ave,
Chicago, IL 60637
- [Admin Assistant: Mary Marre 773-834-1757]
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The Toyota Technological Institute at Chicago
(TTIC)
is a PhD-granting computer science
institute focusing in the areas of machine learning, algorithms, AI
(robotics, natural language, speech, and vision) and computational biology,
located on the University of Chicago campus.
We are essentially a self-contained, free-standing department of machine learning, algorithms, AI, and data science.
We have tenure-track faculty, limited-term research faculty, PhD students, and postdocs.
We are hiring Tenure-Track Faculty and Research Assistant Professors and recruiting new PhD students.
See also our colloquium and
distinguished lectures.
Here is a slide deck with more information!
I am also site-director for the multi-institution NSF TRIPODS Institute for Data, Econometrics, Algorithms, and Learning (IDEAL), a joint effort of Northwestern, UIC, TTIC, UChicago, and Illinois Tech.
I am currently (Spring 2023) teaching TTIC 31150/CMSC 31150 - Mathematical Toolkit (MW 1:30-2:50)
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My main research interests are in machine learning theory, approximation
algorithms, on-line algorithms, algorithmic game theory /
mechanism design, algorithmic fairness, and non-worst-case
analysis of algorithms. Many years ago I also did work in AI Planning. I am a member of the Simons Collaboration on the Theory of Algorithmic Fairness.
Before joining TTIC, I spent 25 wonderful years on the CS faculty at Carnegie Mellon University.
I am on the Steering Committees for FOCS, ITCS, and FORC, and on the editorial board for JACM. I am also on the Advisory Board of a new open access journal TheoretiCS. I was recently Program Chair
for the 2019
Innovations in Theoretical Computer Science (ITCS) Conference,
on the Organizing Committee for the STOC 2018 and STOC 2017 Theory Fest, and a member of the SafeToC
committee.
For more information on my research, see the publications and research
interests links below.
Blum, Hopcroft, &
Kannan, Foundations
of Data Science. (This pre-publication version is free to view and download
for personal use only. Not for re-distribution, re-sale or use in derivative works. Please do not re-post
or mirror.)
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Current PhD advisees:
Kevin Stangl,
Han Shao,
Naren Manoj (jointly advised with Yury Makarychev),
Keziah Naggita (jointly advised with Matt Walter),
Kavya Ravichandran (jointly advised with Nati Srebro),
Melissa Dutz.
Former PhD advisees:
Prasad
Chalasani,
Santosh
Vempala,
Carl Burch,
Adam Kalai,
John Langford,
Nikhil Bansal,
Martin Zinkevich,
Shuchi Chawla,
Brendan McMahan,
Maria-Florina (Nina) Balcan,
Shobha Venkataraman,
Mugizi Robert Rwebangira,
Katrina Ligett,
Aaron Roth,
Or Sheffet,
Pranjal Awasthi,
Liu Yang,
Ankit Sharma,
Jamie Morgenstern,
Nika Haghtalab.
Though I am no longer at CMU, I endorse the CMU SCS Reasonable Person Principle which basically asks to be reasonable and assume everyone else is doing likewise.
