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Latest academic promotions

We are happy to announce four promotions in the department:

Many congratulations to our colleagues for all their achievements!


Paris Giampouras joins the department as an Assistant Professor

We are happy to announce that Dr Paris Giampouras has joined the Department of Computer Science as an Assistant Professor. Originally from Greece, he has relocated to Warwick from Baltimore, where he spent four years working as a Postdoctoral Fellow and later as a Research Faculty member at the Mathematical Institute for Data Science at Johns Hopkins University. His expertise lies in machine learning theory and its applications in image processing and computer vision. More specifically, his research has focused on exploring parsimonious representations to address various inverse problems and adversarial robustness.

Currently, he is focusing on two main areas: a) leveraging structured representation in Generative AI applications, and b) developing algorithms that enable continual learning of various tasks for deep learning systems. His goal is to contribute to the foundational understanding of AI algorithms, with a focus on robustness, applications of AI in medicine, and climate change.

We welcome him to the department!


PhD Studentship in the topic of Multiagent Systems and related areas

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


Two New Assistant Professors

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 accepted to NeurIPS 2023

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

Ayse Saliha Sunar joins the department as a Teaching Fellow

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!


Mustafa Yasir Presents Project Work at the 3rd Annual Workshop on Graph Learning Benchmarks at KDD 2023

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.


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