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Dr Andrey Kormilitzin

BSc, MSc, PhD
Status
Affiliate Researcher
+44 1865 613137
Contact form
Research groups
  • Machine Learning and Data Science
  • Stochastic Analysis
Address
Mathematical Institute
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
Major / recent publications

Publications and working papers

Further details

2012 PhD in Physics, Tel Aviv University

Thesis: "Forward physics at the LHC energies"

Supervisor: Prof. Eugene Levin

 

Prizes, awards, and scholarships
  • 2023 The NIHR Applied Research Collaboration 
  • 2021 The Oxford-GlaxoSmithKline Functional Genomics programme
  • 2021 The National Institute for Health and Care AI Award
  • 2018 Alzheimer’s Research UK Network Centre Grant
  • 2012 - 2014 Minerva Fellowship, Max Planck Society
  • 2011 - 2012 Visiting Fellow, Ben-Gurion University
  • 2006 - 2008 Salim and Rachel Benin Foundation, Award
Recent publications
Detecting the clinical features of difficult-to-treat depression using synthetic data from large language models
Lorge, I Joyce, D Taylor, N Nevado-Holgado, A Cipriani, A Kormilitzin, A Computers in Biology and Medicine volume 194 110246 (10 Aug 2025)
Harnessing digital health data for suicide prevention and care: A rapid review
Bennett-Poynter, L Kundurthi, S Besa, R Joyce, D Kormilitzin, A Shen, N Sunwoo, J Szkudlarek, P Sequiera, L Sikstrom, L Digital Health volume 11 (23 Feb 2025)
Changes in iPSC-Astrocyte morphology reflect Alzheimer’s disease patient clinical markers
Rowland, H Miller, G Liu, Q Li, S Sharp, N Ng, B Wei, T Arunasalam, K Koychev, I Hedegaard, A Ribe, E Chan, D Chessell, T Kocagoncu, E Lawson, J Malhotra, P Ridha, B Rowe, J Thomas, A Zamboni, G Zetterberg, H Cader, M Wade-Martins, R Lovestone, S Nevado-Holgado, A Kormilitzin, A Buckley, N Stem Cells sxae085 (20 Dec 2024)
Model development for bespoke large language models for digital triage assistance in mental health care
Taylor, N Kormilitzin, A Lorge, I Nevado-Holgado, A Cipriani, A Joyce, D Artificial Intelligence in Medicine volume 157 102988 (29 Nov 2024)
Efficiency at scale: investigating the performance of diminutive language models in clinical tasks
Taylor, N Ghose, U Rohanian, O Nouriborji, M Kormilitzin, A Clifton, D Nevado-Holgado, A Artificial Intelligence in Medicine volume 157 (23 Oct 2024)
Research interests
  • Statistical machine learning and deep learning
  • Bioinformatics and applications of ML/DL to healthcare
  • Stochastic analysis, sequential data, signatures
  • Particle Physics, quantum field theory, scattering amplitudes
Teaching
  • HT22 - B7.3 Further Quantum Theory
  • HT21 - B7.3 Further Quantum Theory
  • HT20 - B7.3 Further Quantum Theory
  • HT19 - B7.3 Further Quantum Theory
  • HT18 - B7.3 Further Quantum Theory
  • MT17 - C5.5 Perturbation Methods
  • HT17 - B7.3 Further Quantum Theory 
  • MT16 - C6.3 Approximation of Functions  
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London Mathematical Society Good Practice Scheme Athena SWAN Silver Award (ECU Gender Charter) Stonewall Silver Employer 2022

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