Dr Efstratios Palias PhD

School of Computer Science
Teaching Fellow

Contact details

Email
e.palias@bham.ac.uk
View my research portal
Address
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Efstratios Palias is a Teaching Fellow in the School of Computer Science. He obtained his PhD from the same school in 2024. His taught modules focus on the mathematical foundations of AI and Machine Learning. He is also conducting research in the field Quantum Machine Learning.

Qualifications

  • PhD in Computer Science, University of Birmingham, 2024
  • MSc in Statistics, University of Athens, 2017
  • BSc in Statistics, University of Athens, 2015

Biography

Efstratios Palias received his BSc and MSc in Statistics from the university of Athens. After working in industry for a couple of years, he embarked on his PhD journey at University of Birmingham, under the supervision of Ata Kaban. His PhD thesis was titled "Exploiting Intrinsic Dimension using Compressed Quadratic Models” and explored some conditions under which learning from high-dimensional data can be done efficiently by randomly removing some variables. He worked extensively with tools from high-dimensional probability, including concentration of measure and random matrices. After submitting his PhD thesis in 2024, he was hired as a Teaching Fellow at the same school to teach mathematical- and AI-related courses. He has been involved in research in Quantum Machine Learning since 2025, in collaboration with colleagues.

Teaching

  • Computer Systems, MSc Computer Science, Summer 2026 (Module lead)
  • Artificial Intelligence and Machine Learning, MSc Computer Science, Summer 2026 (Module lead)

Research

  • Statistical Learning Theory
  • Quantum Machine Learning
  • Information Theory
  • Measure Concentration

Publications

Recent publications

Article

Kaban, A & Palias, E 2024, 'A Bhattacharyya-type conditional error bound for quadratic discriminant analysis', Methodology and Computing in Applied Probability, vol. 26, no. 4, 38. https://doi.org/10.1007/s11009-024-10105-x

Palias, E & Kabán, A 2023, 'The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification', Statistics and Computing, vol. 33, no. 4, 87. https://doi.org/10.1007/s11222-023-10251-1

Conference contribution

Simpson, JP, Palias, E & Jose, S 2026, Optimal Error Exponents for Composite Sequential Quantum Hypothesis Testing. in 2026 IEEE Information Theory Workshop (ITW). IEEE International Information Theory Workshop, Institute of Electrical and Electronics Engineers (IEEE), 2026 IEEE Information Theory Workshop (ITW), Tempe, Arizona, United States, 10/11/26. https://doi.org/10.48550/arXiv.2605.04915

Simpson, JP, Palias, E & Jose, ST 2026, Sample Complexity of Composite Quantum Hypothesis Testing. in 2026 IEEE International Symposium on Information Theory (ISIT). IEEE International Symposium on Information Theory proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2026 IEEE International Symposium on Information Theory, Guangzhou, China, 28/06/26. https://doi.org/10.48550/arXiv.2601.08588, https://doi.org/10.1109/ISIT62367.2026.11654009

Palias, E & Kaban, A 2024, Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension. in 2024 International Joint Conference on Neural Networks (IJCNN)., 10649958, Proceedings of International Joint Conference on Neural Networks, Institute of Electrical and Electronics Engineers (IEEE), 2024 IEEE World Congress on Computational Intelligence, Yokohama, Japan, 30/06/24. https://doi.org/10.1109/IJCNN60899.2024.10649958

View all publications in research portal