Program: August 5, 2024

Location: 3F: Room 304

9:00 – 9:05 Welcome and Overview

9:05 – 10:30

Session 1

7 Student Presentations (10 min  talk + 2 min Q&A)  

Deep Learning with Requirements in the Real World
(Mihaela  Stoian, University of Oxford)

Parameter Efficient Instruction Tuning of LLMs for Financial Applications
(Subhendu Khatuya, IIT Kharagpur)

Culturally-aware Image Captioning
(Youngsik Yun, Dongguk University)

NeuroSymbolic LLM for Mathematical Reasoning and Software Engineering
(Prithwish Jana, Georgia Institute of Technology))

Implicit Anomaly Subgraph Detection (IASD) in Multi-Domain Attribute Networks
(Ying Sun, Tianjin university)

Causal Graph Modeling with Deep Neural Engines for Strong Abstract Reasoning in Language and Vision
(Gaël Gendron, University of Auckland)

N-Agent Ad Hoc Teamwork
(Caroline L Wang, University of Texas at Austin)

10:30 – 11:00 Coffee Break
11:00 – 12:00 Invited Talk
Writing for ResearchMichael Wooldridge (University of Oxford)
12:00 – 12:40

Session 2

3 Student Presentations (10 min talk + 2 min Q&A)  

Two-Sided Facility Location Games
(Simon Krogmann, Hasso Plattner Institute)

Fair and Efficient Chore Allocation: Existence and Computation
(Aniket Murhekar, University of Illinois at Urbana-Champaign)

Bio-inspired Dynamic and Decentralized Online Learning in Uninformed Heterogeneous Multi-Agent Environments
(Angel A Sylvester, University of Minnesota)

12:40 – 14:00 Lunch Break
14:00 – 15:30 Session 3

7 Student Presentations (10 min talk + 2 min Q&A) 

Optimization Under Epistemic Uncertainty Using Prediction  
(Noah J Schutte, TU Delft)

Fairness and Optimization Tradeoffs in Dynamic Multiagent Allocation Problems
(Yohai Trabelsi, Bar-Ilan University)

Multivariate Analysis and Structural Restrictions in Computational Social Choice
(Šimon Schierreich, Czech Technical University)

Stakeholder-oriented Decision Support for Auction-based Federated Learning
(Xiaoli Tang, Nanyang Technological University)

Towards Revolutionized Smart Grids: An AI-Driven Broker for Improved Operational Efficiency
(Sanjay Chandlekar, Singapore Institute of Technology)

Cooperation and Fairness in Systems of Indirect Reciprocity
(Jacobus M. M. Smit, University of Amsterdam)

Enhancing Policy Gradient Algorithms with Search in Imperfect Information Games
(Ondřej Kubíček,  Czech Technical University)

15:30 – 16:00 Coffee Break
16:00 – 17:00 Career Panel
Professor Ken Forbus (Northwestern University), Professor Caren Han (The University of Melbourne), Professor Kate Larson (University of Waterloo), Professor Peter Stone (University of Texas at Austin)
17:00 – 17:10 Closing Remarks

Poster Session: August 6, 2024

Time: TBD All DC participants will present posters. Details will be shared soon.

 

Invited Talk

Topic: Writing for Research

Michael Wooldridge (University of Oxford)

Abstract
Many PhD students, who have spent years honing their mathematical and other technical skills, imagining that these are the key to success in AI, are taken aback to discover that writing skills are just as important — and the majority of PhD students internationally will spend their professional careers writing in a foreign language. In this talk, I will review the scientific writing process: starting from the mechanics and some key principles to help improve your writing, through to publication strategy, and even (gulp) research grant proposal writing.

About the invited speaker
Michael Wooldridge is a Professor of Computer Science at the University of Oxford, and a programme director for AI at the Alan Turing Institute. He is a Fellow of the ACM, the Association for the Advancement of AI (AAAI), and the European Association for AI (EurAI). From 2014-16, he was President of the European Association for AI, and from 2015-17 he was President of the International Joint Conference on AI (IJCAI). As well as more than 400 technical articles on AI, he has published two popular science introductions to the field: The Ladybird Expert Guide to AI (2018), and The Road to Conscious Machines (Pelican, 2020).

Career Panel

Professor Ken Forbus (Northwestern University)
Bio: Kenneth D. Forbus is the Walter P. Murphy Professor of Computer Science and Professor of Education at Northwestern University.  His research interests include qualitative reasoning, analogical reasoning and learning, spatial reasoning, sketch understanding, natural language understanding, cognitive architecture, reasoning system design, and AI for education and learning.  He is a Fellow of the Association for the Advancement of Artificial Intelligence, the Cognitive Science Society, the Association for Computing Machinery, and the American Association for the Advancement of Science.  He is the inaugural recipient of the Herbert A. Simon Prize, a recipient of the Humboldt Research Award and served as Chair of the Cognitive Science Society.

Professor Caren Han (University of Melbourne)
Bio: Prof. Han is a Senior Lecturer (Associate Professor in U.S. System) at the University of Melbourne and an Honorary Professor at the School of Computer Science, University of Sydney and University of Edinburgh, teaching and researching Natural Language Processing and Artificial Intelligence. Her research expertise lies in Natural Language Processing, encompassing multi-modal (Visual-Linguistic) Learning, Explainable and Refinable NLP, sentiment analysis, abusive language detection, dialogue systems, and language understanding. This research interest has led her to successfully secure multiple international and national research and industry grants, including NASA, Google, Thales, Microsoft, Hyundai, Bank of Korea, the Australian government, the Hong Kong government, and the Korean government. She is the winner of several awards, including Australia Young Achiever 2017, Teacher of the Year 2020, Supervisor of the Year 2021, Early Career Research Award 2023 (Physics, Math, and Computing), and Google Research Award 2023.

Professor Kate Larson (University of Waterloo)
Bio: Prof. Larson is a professor and holds a University Research Chair at the University of Waterloo and is a research scientist at Google DeepMind.   She is interested in algorithmic questions arising in artificial intelligence and multiagent systems with a particular focus on algorithmic game theory, group decision making, preference modelling, and the insights that reinforcement learning can bring to these problems, along with ways of promoting and supporting cooperative AI. Among many things, she is co-editor-in-chief of the Journal of Autonomous Agents and Multiagent System and is serving as program chair for IJCAI 2024.

Professor Peter Stone (University of Texas at Austin)
Bio: Prof. Stone holds the Truchard Foundation Chair in Computer Science at the University of Texas at Austin. He is Associate Chair of the Computer Science Department, as well as Director of Texas Robotics.  Professor Stone’s research interests in Artificial Intelligence include machine learning (especially reinforcement learning), multiagent systems, and robotics. Professor Stone received his Ph.D in Computer Science in 1998 from Carnegie Mellon University. From 1999 to 2002 he was a Senior Technical Staff Member in the Artificial Intelligence Principles Research Department at AT&T Labs – Research. He is a University Distinguished Teaching Professor, an Alfred P. Sloan Research Fellow, Guggenheim Fellow, AAAI Fellow, IEEE Fellow, AAAS Fellow, ACM Fellow, Fulbright Scholar, and 2004 ONR Young Investigator. He is recipient of the University of Texas System Regents’ Outstanding Teaching Award, the prestigious IJCAI Computers and Thought Award and the ACM/SIGAI Autonomous Agents Research Award. Professor Stone co-founded Cogitai, Inc., a startup company focused on continual learning, in 2015, and currently serves as Chief Scientist of Sony AI.

List of mentors

  • Hau Chan (University of Nebraska-Lincoln)
  • Maria Gini (University of Minnesota)
  • Caren Han (University of Melbourne)
  • Laura Hiatt (Naval Research Laboratory)
  • Kate Larson (University of Waterloo)
  • Viliam Lisy (Czech Technical University
  • Jihie Kim (Dongguk University)
  • Tim Miller  (University of Queensland)
  • Parisa Kordjamshidi (Michigan State University)
  • Sarit Kraus (Bar-Ilan University)
  •  Fernando Santos (University of Amsterdam)
  •  Peter Stone (University of Texas at Austin)
  •  Chee Wei Tan (Nanyang Technological University)
  •  Matt Taylor (University of Alberta)
  •  Harko  Verhagen (Stockholm University)
  •  Lirong Xia (Rensselaer Polytechnic Institute)
  •  Da Yan  (Indiana University Bloomington)

List of reviewers

  • Haris Aziz (UNSW Sydney)
  • Dorothea Baumeister (Federal University of Applied Administrative Sciences)
  • Katrien Beuls (Université de Namur)
  • Elizabeth Bondi-Kelly (University of Michigan)
  • Hau Chan (University of Nebraska-Lincoln)
  • Joydeep Chandra (Indian Institute of Technology Patna)
  • Hyung Jin Chang (University of Birmingham)
  • Maria Chang (IBM Research)
  • Muhammad Tayyab Chaudhry (COMSATS University Islamabad (CUI) Lahore Campus)
  • Huanhuan Chen (University of Science and Technology of China)
  • Qiang Cheng (University of Kentucky)
  • Arthur Choi (Kennesaw State University)
  • Edith Elkind (Oxford)
  • Joao Florindo (University of Campinas)
  • Maria Gini (University of Minnesota)
  • Claudia Goldman (General Motors Advanced Technical Center)
  • Caren Han (University of Melbourne)
  • Dirk Heylen (University of Twente)
  • Laura Hiatt (Naval Research Laboratory)
  • Mahdi Jalili (RMIT University)
  • Sundong Kim (Gwangju Institute of Science and Technology)
  • Sven Koenig (University of Southern California)
  • Jérôme Lang (CNRS)
  • Kate Larson (University of Waterloo)
  • Daniel Le Berre (Université d’Artois, CNRS)
  • Seulki Lee (Ulsan National Institute of Science and Technology)
  • Viliam Lisy (Czech Technical University)
  • Jiwen Lu (Tsinghua University)
  • Roger Mailler (Oklahoma State University)
  • Tim Miller (The University of Queensland)
  • Debdeep Mukhopadhyay (IIT KGP)
  • Prajakta Nimbhorkar (Chennai Mathematical Institute)
  • Xia Ning (Ohio State University)
  • David Pynadath (USC Institute for Creative Technologies)
  • Claude-Guy Quimper (Université Laval)
  • Jan Ramon (INRIA, FR)
  • Fenghui Ren (University of Wollongong)
  • Jianfeng Ren (University of Nottingham Ningbo)
  • Francesco Ricci (Free University of Bozen-Bolzano)
  • Yasushi Sakurai (Osaka University)
  • Ansaf Salleb-Aouissi (Columbia University)
  • Fernando Santos (University of Amsterdam)
  • Sebastian Sardina (RMIT University)
  • Silvia Schiaffino (ONICET)
  • Sandip Sen (University of Tulsa)
  • Mohamed Siala (LAAS-CNRS)
  • Mohan Sridharan (University of Edinburgh)
  • Peter Stone (University of Texas at Austin and Sony AI)
  • Samarth Swarup (University of Virginia)
  • Chee Wei Tan (Nanyang Technological University)
  • Quan Tho (Ho Chi Minh City University of Technology)
  • Paolo Torroni (University of Bologna)
  • Long Tran-Thanh (University of Warwick)
  • David Traum (USC Institute for Creative Technologies)
  • Harko Verhagen (Stockholm University)
  • Honghan Wu (University College London)
  • Nannan Wu (Tianjin University)
  • Lirong Xia (Rensselaer Polytechnic Institute)
  • Hongteng Xu (Renmin University of China)
  • Da Yan (Indiana University Bloomington)
  • Seunghyun Yoon (Adobe Research)
  • Neil Yorke-Smith (Delft University of Technology)
  • Han Yu (Nanyang Technological University) 
  • Xiangyu Zhao (City University of Hong Kong)
  • Hai-Tao Zheng (Tsinghua University)

DC Program Chairs

  • Anita Raja (City University of New York, Hunter College)
  • Jihie Kim (Dongguk University)