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Mark Lynch

I am a first year PhD Student at the Mathematics for Real World Systems (MathSys II) CDT. My project revolves around applications of machine learning and neural networks to epidemiological models. In particular, the use of Physics Informed Neural Networks to predict hidden utility functions that are being optimised by disease dynamics. Some of my current research includes epidemiological models that incorporate human behaviour dependent on infection status. More specifically, how would optimal individuals behave if they acted more selfishly vs acting for the social good.

I am a Fellow of the JSPS Summer ProgrammeLink opens in a new window 2023, which provides opportunities for young pre- and post-doctoral researchers from North America and Europe to receive an orientation on Japanese culture and research systems and to pursue research under the guidance of host researchers at a Japanese university or research institute over a period of two months during the summer.

Projects

  • Nash Neural Networks (PhD Project, 2022 - current)

Supervised by: Matthew TurnerLink opens in a new window (University of Warwick); Ryoichi YamamotoLink opens in a new window, John MolinaLink opens in a new window (Kyoto University); Simon SchnyderLink opens in a new window (University of Tokyo)

External Partners: Ryoichi YamamotoLink opens in a new window, Department of Chemical Engineering, Kyoto University.

  • Inferring the Utility from Optimal Behaviour in an Epidemic using Neural Networks (MSc Individual Project, Summer 2022)

Supervised by: Matthew TurnerLink opens in a new window (University of Warwick); Ryoichi YamamotoLink opens in a new window, John MolinaLink opens in a new window (Kyoto University); Simon SchnyderLink opens in a new window (University of Tokyo)

External Partners: Ryoichi YamamotoLink opens in a new window, Department of Chemical Engineering, Kyoto University.

  • Graph Based Anomaly Detection in Healthcare Data (MSc Group Project, Spring 2022)

Group Members: Mark Lynch, Yueting HanLink opens in a new window, Obed NwachukwuLink opens in a new window

Supervised by: Marya BazziLink opens in a new window (University of Warwick)

External Partners: KirontechLink opens in a new window

Presentations and Conferences

Upcoming
Previous
  • From preferences to endogenous behaviour in disease & vice-versa | SBIDER SeminarLink opens in a new window | Jan 2024
  • God, the Golden Rule and the Game Theory of Social Distancing | CPS Network Warwick | Nov 2023 | Video
  • Nash Neural Networks: Inferring Utilities from Optimal Behaviours in Epidemics | SPAAM Seminar Oral Presentation | Oct 2023
  • Inferring the Utility from Optimal Behaviour in an Epidemic using Neural Networks | ICIAM 2023 Tokyo Poster Presentation | Aug 2023
  • Inferring the Utility from Optimal Behaviour in an Epidemic using Neural Networks | STATPHYS28 Oral Presentation | Aug 2023
  • Nash Neural Networks | MathSys Annual Retreat 'Three Minute Thesis' Talk | April 2023
  • Graph Based Anomaly Detection in Healthcare Data | MathSys Annual Retreat Poster Presentation | April 2022

Education

  • PhD, Mathematics of Systems, University of Warwick MathSys II CDT (Oct 2022 - present)
  • MSc, Mathematics of Systems, University of Warwick MathSys II CDT (Sep 2021 - Sep 2022)
  • BSc (Hons), Mathematics, University of Warwick Mathematics Institute (2018-2021)

Other Responsibilities