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Centre for AI Fundamentals

People

Key Centre of AI Fundamentals staff are:

Mauricio Alvarez Lopez

Mauricio received his a PhD in Computer Science from The University of Manchester, UK, in 2011. He then joined the Department of Electrical Engineering at Universidad Tecnológica de Pereira, Colombia, where he was appointed as an Associate Professor until Dec 2016.

From January 2017 to April 2022, he was Lecturer in Machine Learning at The University of Sheffield before joining The University of Manchester as a Senior Lecturer.

Read Mauricio's research profile
Michele Caprio

Michele is Lecturer (Assistant Professor) in Machine Learning and Artificial Intelligence at The University of Manchester. He obtained his PhD in Statistics from Duke University, and worked as a postdoctoral researcher in the Department of Computer and Information Science of the University of Pennsylvania.

His general interest is probabilistic machine learning, and in particular the use of imprecise probabilistic techniques to investigate the theory and methodology of uncertainty quantification in Machine Learning and Artificial Intelligence. Recently, he won the IJAR Young Researcher and the IMS New Researcher Awards, and he was elected member of the London Mathematical Society.
Jason Hartford

Jason Hartford is a Dame Kathleen Ollerenshaw Fellow at the University of Manchester. He also jointly holds an industry research scientist role at Valence Labs, where he leads the causality focused research unit. Previously, he was a post-doc with Yoshua Bengio at Université de Montréal. Before joining Mila, he completed his PhD at the University of British Columbia with Kevin Leyton-Brown. He works on developing new techniques for causal representation learning and causal inference.
Samuel Kaski

Samuel is Professor of Artificial Intelligence at The University of Manchester and at Aalto University, Helsinki where he leads the Finnish Center for Artificial Intelligence Research FCAI and ELLIS Unit Helsinki.

In July 2021, Samuel was appointed among the first Turing Artificial Intelligence (AI) World-Leading Research Fellows. The fellowships, named after AI pioneer Alan Turing, are part of the UK’s commitment to further strengthen its position as a global leader in the field.

Read Samuel's research profile
Tingting Mu

Tingting Mu is a Senior Lecturer in Machine Learning. She obtained her Bachelor degree from the University of Science and Technology of China (USTC) in 2004 and a PhD from The University of Liverpool in 2008. She was a Lecturer in University of Liverpool, before joining The University of Manchester in 2016.

Tingting has a general interest on developing advanced mathematical modelling and large-scale optimisation techniques to simulate human intelligence and analyse real-world complex data. Within the fundamental side of machine learning, she is specialised at representation learning.

Read Tingting's research profile
Anirbit Mukherjee

Before joining The University of Manchester in November 2021, Anirbit worked as a postdoctoral researcher at Wharton, the Department of Statistics at the University of Pennsylvania.

Most recently, his research interests include solving differential equations using neural nets, particularly in the direction of building theoretical foundations for Deep Operator Networks.

Read Anirbit's research profile
Wei Pan

Wei Pan is a senior lecturer in Computer Science. After completing degrees in Harbin Institute of Technology and University of Science and Technology of China, Wei Pan gained industry experience in China and then in London whilst completing a PhD in Bioengineering at Imperial College London.

Wei Pan moved to Manchester from TU Delft, where he was Assistant Professor in the Department of Cognitive Robotics, Faculty of Mechanical, Maritime and Materials Engineering and was also co-director of Delft SELF AI Lab.

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Omar Rivasplata

Omar is a Senior Lecturer (Associate Professor) in Machine Learning. Omar's top-level topics of interest are statistical learning theory, risk bounds, PAC-Bayes bounds, and probabilistic machine learning theory; and has a broad interest in artificial intelligence fundamentals (AI-Fun) in general. In the limit of tending to praxis, Omar works on designing strategies to train and certify machine learning models.

Before joining The University of Manchester (July 2024), Omar had positions at University College London and DeepMind. Omar has a PhD in Mathematics (University of Alberta, 2012) and a PhD in Statistical Learning Theory (University College London, 2022).
Mingfei Sun

Mingfei is a lecturer in Computer Science. He obtained his bachelors degree from the University of Science and Technology of China (USTC) and his PhD from the Hong Kong University of Science and Technology (HKUST).

Mingfei has a broad interest in AI with a particular focus on machine learning techniques such as deep reinforcement learning and learning from demonstrations. His research covers large-scale deep reinforcement learning, policy gradient methods, and optimisation theory. He is applying these methods to problems in video games, robotics and multi-agent systems.

Read Mingfei's research profile