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Dr Costis Papageorgakis

Costis

Head of Physics and Astronomy | Reader in Theoretical Physics

Email: c.papageorgakis@qmul.ac.uk
Telephone: 020 7882 5806
Room Number: G. O. Jones Building, Room 608

Profile

I am the Head of Physics and Astronomy and a Reader in Theoretical Physics at the Centre for Theoretical Physics. My work has focussed on various aspects of supersymmetric/superconformal field theories, their relation to String/M-theory and how they can be attacked with Machine Learning techniques.

I hold an undergraduate diploma from the University of Patras (Greece), an MSc from Durham University and a PhD from Queen Mary University of London. I previously held postdoctoral positions at the Tata Institute of Fundamental Research, India ('06-'09), King's College London ('09-'11) and Rutgers University, USA ('11-'14) before returning to Queen Mary as staff with a Royal Society University Research Fellowship. 

I am a Fellow of the Institute of Physics. 

Teaching

I currently teach the undergraduate course "Quantum Mechanics and Symmetry" over the second semester of the 2025-2026 academic year.

I am a Fellow of Advance HE.

Research

Research Interests:

See Costis Papageorgakis’ research profile pages including details of research interests, publications, and live grants.

 

 

Publications

(A complete and up to date list of publications with an accurate citation count can also be found at this link)

  • (2025). Deep finite temperature bootstrap. nameOfConference


  • Richmond P, Agarwal P, Chowdhury B et al. (2025). FeynTune: Large Language Models for High-Energy Theory. nameOfConference


  • Niarchos V, Papageorgakis C (2024). Learning S-matrix phases with neural operators. nameOfConference


  • Niarchos V, Papageorgakis C, Richmond P et al. (2023). Bootstrability in line-defect CFTs with improved truncation methods. nameOfConference


  • Kántor G, Niarchos V, Papageorgakis C et al. (2023). 6D (2,0) bootstrap with the soft-actor-critic algorithm. nameOfConference


  • Andriolo E, Niarchos V, Papageorgakis C (2023). Covariantly Constant Anomalies on Conformal Manifolds. nameOfConference


  • Andriolo E, Lambert N, Orchard T (2022). A path integral for the chiral-form partition function. nameOfConference


  • Kántor G, Papageorgakis C, Niarchos V (2022). Solving Conformal Field Theories with Artificial Intelligence. nameOfConference


  • Kántor G, Niarchos V, Papageorgakis C (2022). Conformal bootstrap with reinforcement learning. nameOfConference


  • Agarwal P, Andriolo E, Kántor G et al. (2021). Macdonald indices for four-dimensional N=3 theories. nameOfConference


View profile publication page

Supervision

PhD students:

I am also interested in taking on new students for the following project:

Project Title
Conformal Field Theories and Artificial Intelligence

Conformal Field Theories are mathematical descriptions of natural phenomena that look the same at all length scales. They find fundamental applications over a large spectrum of topics ranging from condensed-matter physics, particle physics, string theory and quantum gravity. They are, however, incredibly hard to solve with the exception of a handful of examples.

This project aims to exploit the tremendous recent progress in Artificial Intelligence to solve arbitrary conformal field theories. This will be achieved by utilising machine-learning techniques similar to those used by Google’s DeepMind Technologies when building the AlphaGo programme, which spectacularly beat professional Go champions.

Requirements:

A very good grasp of graduate Quantum Field Theory and supersymmetry, as well as some basic conformal field theory and string theory. Coding experience is desirable. 

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