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Overview

Dr Gokberk Kabacaoglu

Assistant Professor


Affiliations
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Assistant Professor in the Department of Computer Science

Biography

Dr. Gökberk Kabacaoğlu is an Assistant Professor in the Department of Computer Science at Durham University. He develops fast and accurate computational methods for simulating complex fluids, combining numerical algorithms, machine learning and high-performance computing. His work has applications in biological fluid dynamics and the design of microfluidic devices for cell sorting. 

He joined Durham in 2025, having previously held an Assistant Professorship in Mechanical Engineering at Bilkent University. Before this, he was a postdoctoral researcher at the Flatiron Institute’s Center for Computational Biology in New York. He received his PhD in Mechanical Engineering from the University of Texas at Austin in 2019 and his undergraduate degree from Bilkent University in 2014. 

Research

His research explores how cells, droplets and other deformable structures interact with flowing fluids. He develops simulation methods that combine boundary-integral formulations with machine learning and GPU computing to make these problems more computationally tractable. Applications include microfluidic cell sorting, droplet flows in confined channels, microscopic swimmers and fluid motion within cells. He also contributes to open-source scientific software, including Ves-Net, a neural-network-accelerated solver for vesicle suspensions, and SkellySim, a simulation framework for biophysical flows. 

Teaching and academic service

At Durham, he teaches Parallel Scientific Computing and Reinforcement Learning and Game Theory. He received the Department of Computer Science’s Excellence in Teaching Award in 2025. He also chairs the Engineering Domain Panel for EuroHPC Joint Undertaking Regular Access calls and contributes to international conferences and peer review in scientific computing and fluid dynamics.

Research interests

  • Fast numerical algorithms
  • Machine learning for scientific simulations
  • Complex flows
  • Data-driven models for biological applications

Publications

Journal Article

Supervision students