We are seeking PhD candidates in the topic of Multiagent Systems and related areas, with particular emphasis on one or more of: computational social choice, algorithmic game theory, multiagent learning, and social and economic networks. The multiagent systems researchers at University of Warwick include Markus BrillLink opens in a new windowLink opens in a new window, Ramanujan SridharanLink opens in a new windowLink opens in a new window, Long Tran-ThanhLink opens in a new windowLink opens in a new window, Debmalya Mandal and Paolo TurriniLink opens in a new window

We are happy to announce that Dr Fanghui Liu and Dr Debmalya Mandal have joined the Department of Computer Science as Assistant Professors.

Fanghui finished his PhD degree at Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University in 2019. Then he gained the research experience in Europe as a postdoc researcher, at ESAT-STADIUS, KU Leuven from 2019 to 2021 and Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland from 2021 to 2023, respectively. His research interests include machine learning, statistical learning theory as well as applications in trustworthy machine learning systems.

Debmalya completed his Master’s degree in Computer Science and Automation from Indian Institute of Science, and his PhD in Computer Science from Harvard University, where he was also part of the EconCS group. He then gained experience as a postdoctoral researcher at the Data Science Institute of Columbia University, and at the Max Planck Institute of Software Systems. He is broadly interested in the theoretical foundations of AI/ML systems and often incorporate tools from computational social choice, game theory, and machine learning theory in his research. He is currently working on fairness in machine learning, reinforcement learning, and the exciting problem of AI alignment.

We welcome them both to the department!

Seven papers authored by Computer Science researchers from Warwick have been accepted for publication at the 37th Conference on Neural Information Processing Systems, the leading international venue for machine learning research, which will be held on 10-16 December 2023 in New Orleans, Louisiana, USA:

• EV-Eye: Rethinking High-frequency Eye Tracking through the Lenses of Event Cameras, by Guangrong Zhao, Yurun Yang, Jingwei Liu, Ning Chen, Yiran Shen, Hongkai Wen, and Guohao Lan
• Fully Dynamic k-Clustering in Õ(k) Update Time, by Sayan Bhattacharya, Martin Costa, Silvio Lattanzi, and Nikos Parotsidis
• Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks, by Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, and Volkan Cevher
• Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs, by Dmitry Chistikov, Matthias Englert, and Ranko Lazic
• On the Convergence of Shallow Transformers, by Yongtao Wu, Fanghui Liu, Grigorios Chrysos, and Volkan Cevher
• Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? by Hoang Pham, The Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, Hongkai Wen, and Long Tran-Thanh
• Towards Unbounded Machine Unlearning, by Meghdad Kurmanji, Peter Triantafillou, and Eleni Triantafillou