Congratulations to Alex Psomas for accepting a faculty position at Purdue University! He will join the Department of Computer Science at Purdue as Assistant Professor in fall 2020. Alex received his PhD in computer science from UC Berkeley (where he was advised by Christos Papadimitriou) in 2017, and subsequently joined my group as a postdoc.
Congratulations to Tom Yan for winning a 2019-2022 National Science Foundation Graduate Research Fellowship.
Together with Michael Ostrovsky, I’m serving as co-chair of the program committee of the 21st ACM Conference on Economics and Computation (EC-20).
Congratulations to Gerdus Benade for accepting a faculty position at Boston University! He will join the Questrom School of Business at BU as Assistant Professor of Information Systems in fall 2019. Gerdus has been a PhD student in operations research since 2014. His thesis committee is co-chaired by John Hooker and myself.
I was elected to a 3-year term on the Executive Council of the Association for the Advancement of Artificial Intelligence (AAAI).
Our paper “The Provable Virtue of Laziness in Motion Planning” has been selected to receive the best paper award at the 28th International Conference on Automated Planning and Scheduling, out of 209 submissions. The paper is joint work with Nika Haghtalab (CMU), Simon Mackenzie (CMU), Oren Salzman (CMU), and Sidd Srinivasa (UW).
Abstract: The Lazy Shortest Path (LazySP) class consists of motion-planning algorithms that only evaluate edges along shortest paths between the source and target. These algorithms were designed to minimize the number of edge evaluations in settings where edge evaluation dominates the running time of the algorithm; but how close to optimal are LazySP algorithms in terms of this objective? Our main result is an analytical upper bound, in a probabilistic model, on the number of edge evaluations required by LazySP algorithms; a matching lower bound shows that these algorithms are asymptotically optimal in the worst case.
In a new paper with Wes Pegden and Dingli Yu, we propose a political redistricting protocol with provable guarantees. This work was covered by the Pittsburgh Post-Gazette, New Scientist, Axios, and the Wisconsin Public Radio.
Update: New story in Slate.
Our new paper, A Voting-Based System for Ethical Decision Making, is the topic of a nice story by Jon Christian in The Outline (which led to an especially lively discussion on Reddit). Pradeep Ravikumar also gave a great interview about this project on the radio show AirTalk.
New Scientist just published a nice story about our IJCAI’17 paper with the catchy title “Why You Should Charge Your Friends for Borrowing Your Stuff” (short answer: because in a game where non-rivalrous goods are bought and shared on a network, equilibria are more efficient, in theory and experiments, when access costs are imposed).
Here are some other random topics I’ve weighed in on recently (not covered by other news):
* AI and online dating, in the Boston Globe.
My former PhD student Nisarg Shah won the Victor Lesser Distinguished Dissertation Award, given annually for the best thesis in the area of autonomous agents and multiagent systems. His thesis is entitled “Optimal Social Decision Making.” He will present his thesis research in a plenary talk at AAMAS-17 in Brazil.
An opinion piece that I wrote was published today in Wired. It’s about computational social choice (although I don’t call it that) and a bit of politics.
RoboVote (http://robovote.org), a not-for-profit voting website that provides optimization-driven methods for making collective decisions, has launched today! Check out RoboVote’s about page for (somewhat AI-centric) information about the website, its algorithms, and the theory underlying them, as well as info about the amazing team.
Our paper “Which Is the Fairest (Rent Division) of Them All” has been selected to receive the best paper award at the 17th ACM Conference on Economics and Computation, out of 242 submissions. The paper is joint work with Kobi Gal and Moshik Mash of Ben Gurion University, and my postdoc Yair Zick.
Abstract: What is a fair way to assign rooms to several housemates, and divide the rent between them? This is not just a theoretical question: many people have used the Spliddit website to obtain envy-free solutions to rent division instances. But envy freeness, in and of itself, is insufficient to guarantee outcomes that people view as intuitive and acceptable. We therefore focus on solutions that optimize a criterion of social justice, subject to the envy freeness constraint, in order to pinpoint the “fairest” solutions. We develop a general algorithmic framework that enables the computation of such solutions in polynomial time. We then study the relations between natural optimization objectives, and identify the maximin solution, which maximizes the minimum utility subject to envy freeness, as the most attractive. We demonstrate, in theory and using experiments on real data from Spliddit, that the maximin solution gives rise to significant gains in terms of our optimization objectives. Finally, a user study with Spliddit users as subjects demonstrates that people find the maximin solution to be significantly fairer than arbitrary envy-free solutions; this user study is unprecedented in that it asks people about their real-world rent division instances. Based on these results, the maximin solution has been deployed on Spliddit since April 2015.
Congratulations to Nisarg Shah, who has accepted a tenure-track faculty position in the Department of Computer Science at the University of Toronto! He will join U of T in fall 2017, after spending a year as a postdoc at Harvard’s Center for Research in Computation and Society. I have had the privilege of advising Nisarg since he joined our PhD program in fall 2011 (which is the same time I myself joined CMU); he is defending on June 28.
The Handbook of Computational Social Choice, which I have co-edited together with Felix Brandt, Vince Conitzer, Ulle Endriss, and Jerome Lang, has been officially published.
Description: The rapidly growing field of computational social choice, at the intersection of computer science and economics, deals with the computational aspects of collective decision making. This handbook, written by thirty-six prominent members of the computational social choice community, covers the field comprehensively. Chapters devoted to each of the field’s major themes offer detailed introductions. Topics include voting theory (such as the computational complexity of winner determination and manipulation in elections), fair allocation (such as algorithms for dividing divisible and indivisible goods), coalition formation (such as matching and hedonic games), and many more. Graduate students, researchers, and professionals in computer science, economics, mathematics, political science, and philosophy will benefit from this accessible and self-contained book.
A PDF of the book is freely available online. To open the document, please enter the password cam1CSC (strangely enough, this password can be disseminated legally, so you are encouraged to shout it from the rooftops). The link is here:
Alternatively, the book can be purchased through the Cambridge University Press website (http://www.cambridge.org/
Congratulations to Yair Zick for accepting a faculty position at the National University of Singapore! He will join NUS as Assistant Professor of Computer Science in the summer. Yair has been a postdoc at CMU since April 2014, jointly hosted by Anupam Datta and me. Before that he completed his PhD at Nanyang Technological University, Singapore, where he worked with Edith Elkind.
A new version of Spliddit, featuring two new apps and improvements to the old ones, has officially launched!
Press coverage (newest to oldest): Metro, New Scientist #2, Quanta Magazine, The New York Times #2, New Scientist #1, Pittsburgh Magazine, GeekWire, NSF podcast, Fast Company, Pittsburgh Post-Gazette, Lifehacker, Slashdot, Gizmodo, Nautilus Magazine, The New York Times #1.
I was named a Sloan Research Fellow, together with 125 other young researchers in chemistry, computer science, economics, mathematics, computational and evolutionary molecular biology, neuroscience, ocean sciences, and physics.
Congratulations to Junxing Wang for winning the best student paper award at EC-14, for our joint paper “Fair Enough: Guaranteeing Approximate Maximin Shares”.
Please check back later for more fascinating news!