I obtained my PhD in Computer Science at Stanford University. I was co-advised by Virginia Williams and Ashish Goel; previously, I had been advised by Yoav Shoham before he retired. My research interests [still] lie in investigating complexity of real-life problems that are often motivated by applications in AI -- in particular, group scheduling and assignment problems are of my primary interests. I was fortunated to have been supported by the Kwanjeong Educational Foundation for my graduate studies.

I defended by dissertation in July, 2016, and submitted my dissertation in December, 2016. I now work at Moloco as research scientist.
[ Thesis ]     [ CV ]

Before joining Stanford, I worked at the Cornell Database Group as a research assistant in 2010-2011. I worked with Professor Johannes Gehrke and Professor Noah Snavely on large-scale image processing. I also worked with Professor Robert Kleinberg on approximation algorithms for low-dimensional coverage problems.

I graduated from Cornell University (summa cum laude) in 2010 with a B.S. in Computer Science and a minor in Applied Mathematics.

Publications

DBLP      Google Scholar

Parameterized Complexity of Group Activity Selection [ Forthcoming ]

Hooyeon Lee and Virginia V. Williams
16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017.

Complexity of the Stable Invitations Problem [PDF]

Hooyeon Lee and Virginia V. Williams
31st AAAI Conference on Artificial Intelligence (AAAI), 2017.

Probabilistic Matrix Inspection and Group Scheduling [PDF]

Hooyeon Lee and Ashish Goel.
25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.

Stable Invitations [PDF]

Hooyeon Lee and Yoav Shoham.
29th AAAI Conference on Artificial Intelligence (AAAI), 2015.

Stable Invitations (Non-archived proceedings) [PDF]

Hooyeon Lee and Yoav Shoham.
Fifth Workshop on Computational Social Choice (COMSOC), 2014.

Algorithmic and Game-Theoretic Approaches to Group Scheduling (Extended Abstract) [PDF]

Hooyeon Lee.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014.

Optimizing Time and Convenience in Group Scheduling (Extended Abstract) [PDF]

Hooyeon Lee and Yoav Shoham.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014.

Stable Group Scheduling (Extended Abstract) [PDF]

Hooyeon Lee and Yoav Shoham.
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014.

Approximating Low-dimensional Coverage Problems [PDF]

Ashwinkumar Badanidiyuru, Robert Kleinberg, and Hooyeon Lee.
Symposium on Computational Geometry (SoCG), 2012.

SGL: A Scalable Language for Data-driven Games (Demo Paper) [PDF]

Robert Albright, Alan J. Demers, Johannes Gehrke, Nitin Gupta, Hooyeon Lee, Rick Keilty, Gregory Sadowski, Ben Sowell, Walker M. White.
ACM Special Interest Group on Management of Data (SIGMOD), 2008.

Presentations

Oral Presentation on Complexity of the Stable Invitations Problem at AAAI'17 [ SLIDES ]

Guest Lecture (90-min) on Stable Invitations at MGTECON608 (by Prof. Robert Wilson). [ SLIDES ]

Oral Presentation on Stable Invitations at AAAI'15 [ SLIDES ]

Oral Presentation on Stable Invitations at COMSOC'14 [ SLIDES ]

Poster Presentation on Algorithmic and Game-theoretic Approaches to Group Scheduling at Doctoral Symposium of AAMAS'14 [ Poster ]

Poster Presentation on Optimizing Time and Convenience in Group Scheduling at AAMAS'14 [ Poster ]

Poster Presentation on Stable Group Scheduling at AAMAS'14 [ Poster ]

Poster Presentation on Mechanism Design for Scheduling Groups of Sociable Agents at ACM-EC'13 [ Poster ]

Poster Presentation on Group Scheduling at Stanford Computer Forum Annual Meeting'13 [ Poster ]

Guest Lecture on Game Theory (title: A Beautiful Strategy) at SEED Stanford [ VIDEO #1 #2 ] (language: Korean)

Community

Honors


Teaching Experience


Internships


Competition



I recently moved from the left column to the right as my first child was born in August 2015.

Title: Group Scheduling and Assignment: Complexity and Algorithms

Abstract:

Scheduling an event for a group of agents is a challenging problem. It tends to be tedious and time-consuming for everyone involved. In practice, procrastination and strategic behavior of agents are often a problem, but even if we assume that agents are truthful, prompt, and indifferent among the possible outcomes, the group scheduling problem exhibits an interesting algorithmic problem. Assuming truthful and prompt behavior of agents, we consider settings where the event organizer has probabilistic estimates on availability of agents and is allowed to query agents for their actual availability. Naturally, it is desirable to minimize the (expected) number of queries so as to optimize the time and inconvenience caused by the scheduling process. We consider two models that are motivated by an existing tool that is widely used in practice today, and offer intuitive and computationally efficient algorithms that are applicable to group scheduling settings. Furthermore, we also discuss how our algorithms can be used in different domains than group scheduling.
Another set of issues arise in group assignment problems. Imagine that an event organizer wishes to assign agents to social activities. Agents may have preferences over activities as well as the number of participants in the activity they are assigned to. The organizer would like to assign as many agents to activities as possible, but not at the cost of upsetting some agents by disregarding their preferences. Finding a Nash stable solution is an interesting algorithmic question of its own in this setting, and it has been studied in the literature that many variants of the problem are computationally difficult (i.e., NP-hard). In this thesis, we take an extra step to investigate some of these problems by analyzing their parameterized complexity when the size of a solution is parameterized. Parameterized complexity offers a finer scale than classical complexity, and we classify many variants of the group assignment problem into different complexity classes in the W-hierarchy. Motivated by this problem, we also consider another class of group assignment problems in which agents have friends and enemies. Friend and enemy relationships introduce combinatoric complications into the setting, and we show that the number of friends and/or enemies each agent has plays an important role in complexity of these problems. In addition, we also show that symmetric relationship reduces the complexity of these problems to a great extent.
Lastly, we consider strategic agents in the group assignment problems. We show that in general it is impossible to obtain a strategy-proof mechanism that can also find a Nash stable solution in these settings, even if we restrict the preferences of agents. The only positive result we show is when there is only one activity and all agents prefer more participants than fewer participants -- in this case, there exists a strategy-proof mechanism that is socially optimal and computationally efficient.

[ Link to PDF ]