Sedar Olmez is a multidisciplinary computer scientist and research leader with 11 years of experience building data-driven software, agent-based simulations, and reinforcement learning systems for academia, industry, and government. Currently a Senior Researcher on Fujitsu’s digital twins team and founder of PhDAdvice, he translates cutting-edge research into practical simulation solutions for councils, ministries and private-sector clients. His PhD work at the Alan Turing Institute focused on emergent behaviours in multi-agent systems using deep RL, a thread he has continued through consultancy projects like an agent-based digital twin of the Lloyd’s insurance market. He combines hands-on software engineering for researcher-facing tools with teaching and mentoring roles across universities and industry, often supervising student research and reviewing ML-for-ABM papers. Based in London, he bridges academic rigor and applied impact, and quietly balances deep technical research with client-facing delivery and coaching.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Reinforcement Learning, Pass, Doctor of Philosophy - PhD, Reinforcement Learning, Pass at University of Leeds
Master's degree, Computer Science, Master's degree, Computer Science at King's College London
Summer School, Computer Science, Summer School, Computer Science at Boğaziçi University
This repository contains an updated python version of the UK Housing Market Agent-Based Model originally designed and developed in Netlogo by Nigel Gilbert, John C. Hawksworth and Paul A. Swinney.
Contributions:1 release, 7 PRs, 7 pushes in 1 year 6 months
housing-marketmodel-basedpythonagent-basedagent
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