Roles and subjects

Stipendiary Lecturer in Applied Mathematics, Data Science, & Physics

Contact

Emre.esenturk@ndm.ox.ac.uk

Academic Background 

• BSc, Physics, Middle East Technical University
• PhD, Applied Mathematics, University of Pittsburgh

Undergraduate Teaching Areas 

• Statistics & Data Analysis,
• Introduction to Probability
• Probability
• Mathematical Statistics
• Introduction to Graph Theory
• CP2 (Electricity and Magnetism, Circuits, Optics)
• CP1 (Mechanics, Special Relativity)

Research Interests 

My research concerns topics from applied analysis (differential equations and their applications) and data science (machine learning, etc.). Over the years, I have investigated a number of key areas related to statistical physics, materials science, and machine learning.

Applied Areas (Computational/Statistical modelling and code development)

• Prostate cancer research
• Machine learning for traffic accident analysis (scenario development for smart vehicles)
• Code improvement for atmospheric science research (incorporated into Met Office UM)
• Modelling colloidal inks for 3D printing (developed models for ink transport, stain patterns)

Theoretical Areas (Analysis of DEs, PDEs)

• Kinetic theory of growth processes (analysis of exchange-driven growth systems)
• Kinetic theory of plasmas (analysis of systems with complex boundary conditions)
• Phase transitions and interface motion (dynamics with anisotropic surface tension)

Hobbies

Travelling & E-sports.

Recent Publications 

• Esenturk E., Wallace A., Khastgir S., Jennings P., Identification of Traffic Accident Patterns via Cluster Analysis and Test Scenario Development for Autonomous Vehicles, IEEE Access, 10, 660-675, 2022
• Esenturk E., Velazquez J., Large time asymptotics of exchange-driven growth, Discrete and Continuous Dynamical Systems A, Disc. Cont. Dyn. Sys. A, 41, 747, (2021)

• Esenturk E., Connaughton C., Role of zero clusters in exchange-drive growth, Physical Review E, (101), 052134, (2020)
• Esenturk E., Mathematical theory of exchange-driven growth, Nonlinearity, (31), 3460-3483, (2018).
• Esenturk E., Abraham L., Nicholls S., Matsouki C., Griffiths P., Archibald A., Pyle J., Quasi-Newton methods for atmospheric chemistry simulations: Implementation in UKCA vn10.8, Geoscientific Model Development, (11), 3089-3108, (2018)