Georgios Exarchakis

Staff

Department of Computer Science

Dr Georgios Exarchakis

Georgios finds great satisfaction in seeing well-defined theories validated through real-world observations. With a background in mathematics, he became fascinated with developing models to understand brain function. Over the past decade, machine learning has grown rapidly, driven by breakthroughs in deep learning that solved problems once thought unsolvable. This raises the critical question: Why were our expectations so misaligned? In machine learning, complex models often mimic human processes, but their function cannot be fully specified. Georgios’ research focuses on uncovering the underlying conditions that make these algorithms work—particularly why neural networks generalize so effectively across diverse domains. His work centers on representation learning and probabilistic modelling, and it has found application in diverse areas such as astronomy, medical imaging, and quantum chemistry, with an emphasis on understanding the mathematical principles behind these models’ success.

Research Topics:

Learning Invariant Representations of High Dimensional Data
Efficient Inference and Learning in Probabilistic Models
Deep Learning

University of Bath Research Portal:

Georgios Exarchakis — the University of Bath’s research portal

Second Supervisors

Wenbin Li

Department of Computer Science

Research interests:

Reinforcement learning and its inverse problems;
Graph and network optimisation;
Continuous state approximation.

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Rohit Babbar

Department of Computer Science

Research interests:

supervised learning problems with large label spaces,
learning with long-tailed data, and under label/input noise,
sparse neural networks for energy & memory efficient training/fine-tuning with LLMs, and
generalisation/robustness in deep learning.

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Michael Yang

Department of Computer Science

Research interests:

3D scene synthesis
Scene graph generation
Multimodal learning

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Ali Uncu

Department of Computer Science

Research interests:

Applications of Computer Algebra
Combinatorics and q-series
Developing new algorithms for mathematics

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Alessandro Leronni

Department of Mechanical Engineering

Research interests

Continuum modelling of electrochemo-mechanical systems
Finite element implementation of multiphysics frameworks
Smart materials, energy storage, and developmental biology

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Da Chen

Department of Computer Science

Research interests:

Computer vision, deep learning, multimodal learning: general CV/ML tasks in practical scenarios.
Learning with limited data: Learning with imbalanced data, long-tailed data, open-set data, out-of-distribution data, etc; incremental learning, few-shot learning, etc.
Video processing: multimodal learning with video with visual, textual, and audio information.