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

PhD positions are available at the Theory and Foundations group in the Department of Computer Science, University of Warwick, UK. The group works on various aspects of theoretical computer science, including:

* automata and formal languages,
* logic and games,
* algorithmic game theory,
* online and dynamic algorithms,
* sublinear and streaming algorithms,
* parameterized complexity and structural graph theory,
* string algorithms,
* parallel algorithms,
* approximation algorithms,
* combinatorial and graph algorithms,
* random structures and randomized algorithms,
* computational complexity.

The group has strong ties with the Centre for Discrete Mathematics and its Applications (DIMAP), established in 2007 jointly with Warwick Mathematics Institute and Warwick Business School. Together with DIMAP, the group is one of the leading theory groups in Europe, with regular publications in top international conferences and journals in theoretical computer science.

The Department of Computer Science at Warwick offers an excellent research environment. It was ranked 4th in the latest UK research assessment in Research Excellence Framework (REF) in 2021. The University of Warwick is one of the founding members of the Alan Turing Institute.

The university campus is located on the border of two counties, West Midlands and Warwickshire, is about one hour train ride from London, and 15 minutes from Birmingham International Airport.

The applicants are expected to have a strong background in discrete mathematics, algorithms, or related topics with undergraduate and/or Master's degrees in Computer Science, Mathematics, or related disciplines. The position(s) will be fully funded, and the successful applicant(s) will be receiving a stipend at rate in line with current Research Councils UK rates.

If you are interested in this opening, please send an email to Dr Ramanujan Sridharan (r.maadapuzhi-sridharan@warwick.ac.uk) with a SINGLE .pdf file containing your CV and the names and email addresses of two references, by 24 November 2023. You are strongly encouraged to informally contact faculty members in the group you might want to work with prior to submitting your application.

Shortlisted candidates will be interviewed informally during the week of 4 December - 8 December, 2023.

List of faculty members in the group:

https://warwick.ac.uk/focs/people/<https://warwick.ac.uk/fac/sci/dcs/research/focs/people/>

Centre for Discrete Mathematics and its Applications:
https://warwick.ac.uk/dimap/<https://warwick.ac.uk/fac/cross_fac/dimap/>

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

We are happy to announce that Dr Ayse Saliha Sunar has joined the Department of Computer Science as a Teaching Fellow. She completed her Master's degree on Intelligent Tutoring Systems at Nagoya University and her PhD on Big Educational Data Analysis and Recommender Systems at the University of Southampton.

She then gained experience in teaching in Turkey and in research collaboration, including European project proposals in Slovenia on integrating cutting-edge technologies into educational and other social contexts. Her current research interests include technology-enhanced learning to improve teachers' and faculties' pedagogical skills, as well as applications of natural language processing in classrooms and hybrid teaching models.

We welcome her to the department!

We are delighted to announce that Peter Kiss, a PhD student in the Theory and Foundations Research Division, has received the best student paper award at European Symposium on Algorithms (ESA) 2023, for his joint work with Joakim Bilkstad for the paper: "Incremental (1-eps)-approximate dynamic matching in O(poly(1/eps)) update time". The paper considers the problem of maintaining a large matching in a graph that is undergoing a sequence of edge insertions. They present an algorithm for this fundamental problem in dynamic graph algorithms, which has near-optimal approximation ratio and an update time that does not grow at all with the size of the input and is also polynomial in 1/\eps (the error parameter). In addition, their approach is simpler than previous algorithms on the same problem that achieved weaker guarantees.

Mustafa Yasir, a former Warwick Department of Computer Science student who graduated in Summer 2023, wrote up and presented an academic paper on the work carried out as part of his third year project. The paper was accepted to the 3rd Annual Workshop on Graph Learning Benchmarks at KDD 2023, and was presented in California by Mustafa.

Mustafa's third year project idea, supervised by Dr Long Tran-Thanh and titled 'Extending the Graph Generation Models of GraphWorld', started whilst he was interning at Google last summer. Mustafa contacted some researchers at the company working in the Graph ML space, to ask for any relevant project ideas. He bumped into a team who had just published GraphWorld: a tool to change the way Graph Neural Networks are benchmarked, by creating synthetic graph datasets through graph generation models – as opposed to using real-world datasets that are limited in their generalisability and present a major issue facing the field of Graph Learning.

However, since GraphWorld only used a single graph generation model in this process, Mustafa integrated two additional models with the system, ran large-scale GNN benchmarking experiments with these models and published his code to Google’s official GraphWorld repository. The project provides a significant advancement to researchers across the field looking to benchmark models and guide the development of new architectures.

Dr Long Tran-Thanh commented:

What Mustafa and the GraphWorld team has been working on is very important for the machine learning and AI research communities. In particular, there has been a vocal criticism against the whole field that most models are trained on the same public datasets (e.g., ImageNet, MNIST, etc), therefore are not diverse enough. One way to mitigate this issue is to generate realistically looking synthetic data. This need is especially of importance in within the graph learning community. GraphWorld’s aim is to address this exact problem by creating a powerful and convenient tool that can generate a diverse set of graphs, ranging from large social network-style graphs to molecule-inspired ones. Joining this project with the Google researchers is a huge opportunity for Warwick students to participate in a very impactful project.