Avrim Blum
Professor and Chief Academic Officer
Toyota Technological Institute at Chicago (TTIC)
6045 S. Kenwood Ave.
Chicago, IL 60637
email: [firstname] at ttic.edu. Administrative Assistant: Mary Marre (773)834-1757.

The Toyota Technological Institute at Chicago (TTIC or TTI-Chicago) 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 a bit like a self-contained, free-standing department of machine learning, algorithms, AI, and data science. We have tenure-track faculty (currently 11), limited-term research faculty (currently 12) and PhD students (currently 35). See also our colloquium, distinguished lectures, and young researcher seminar.

Register for the workshops in our 2019 Summer Workshop Program (registration is free). [2018 Summer Workshop Program]


My main research interests are in machine learning theory, approximation algorithms, on-line algorithms, algorithmic game theory / mechanism design, the theory of database privacy, and non-worst-case analysis of algorithms. Some time ago I also did work in AI Planning. Before joining TTIC, I spent 25 wonderful years on the CS faculty at Carnegie Mellon University.

I am currently (Winter 2019) teaching TTIC 31010 / CMSC 37000 Algorithms.

I am Program Chair for the 2019 Innovations in Theoretical Computer Science (ITCS) Conference and also on the FOCS Steering Committee. I was recently on the Organizing Committee and Workshop Co-Chair for the STOC 2018 Theory Fest, the Program Committee for COLT 2018, the SafeToC committee, the organizing committee for the STOC 2017 Theory Fest and Program Committees for STOC 2016 and COLT 2014. I also co-organized the STOC 2013 Workshop on New (Theoretical) Challenges in Machine Learning. For more information on my research, see the publications and research interests links below.

Publications Research Interests
Survey Talks Courses Taught
My SODA 2015 talk on New Directions in Learning Theory and a short essay.
Blum, Hopcroft, & Kannan, Foundations of Data Science (as of March 2019).

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:

[Last updated November 2018]