Dr. Emir Demirović

Assistant Professor of Computer Science, TU Delft, The Netherlands

I lead a research group on combinatorial optimisation, where we develop algorithms that can be applied to a wide range of real-world problems. Our techniques are based on Satisfiability solving and constraint programming, with some elements of machine learning. Prior to my appointment at TU Delft, I worked as postdoc at the University of Melbourne (2017-2020), received my PhD from the Vienna University of Technology in 2017, and in between these positions held shorter term posts at a production planning and scheduling company MCP (Vienna, Austria) and the National Institute of Informatics (Toyko, Japan).

My long term vision is to automate decision making that is currently done by humans, referring to scenarios where difficult decisions need to be made under complex constraints. This not only results in more efficient decision making and resource utilisation, but also relieves human experts of the burden of handling difficult and stressful tasks, leaving them more time to deal with creative and meaningful problems that have not (yet) been automatised.

Office: 4.E.400, Building 28
Email: e.demirovic@tudelft.nl
Publications: Google Scholar

  • Would you like to do your master thesis in our group? Get in touch!


We work on both fundamental and applied research, and collaborate with civil engineering, QuTech, and industry.

Data Science

specialised combinatorial optimisation algorithms for trustworthy machine learning, focussing on decision trees

Portfolio 1


general-purpose optimisation techniques based on propositional logic and constraint programming

Portfolio 1


methods that can provide human-understandable explanations in addition to good performance

Portfolio 1


solving real-world problems such as timetabling, scheduling, and production planning

Portfolio 1

Integration with Machine Learning

end-to-end learning with combinatorial problems (predict+optimise)

Portfolio 1

Robust and

theory and algorithms beyond conventional optimisation

Portfolio 1
Portfolio 1
Portfolio 1


picture of Jeff Smits

Jeff Smits

Research Software Engineer

picture of Koos van der Linden

Koos van der Linden

PhD candidate, optimal decision trees

generic user pic

Maarten Flippo

PhD candidate, constraint programming

generic user pic

Elif Arslan

PhD candidate, ride-sharing, forecasting

generic user pic

Konstantin Sidorov

PhD candidate, explainable
combinatorial optimisation

generic user pic

Imko Marijnissen

PhD candidate, scheduling for quantum

picture of Matthias Horn

Matthias Horn

Postdoc (2022), scheduling

Ana Tatabitovska


Imko Marijnissen

MaxSAT, now PhD student

Angelos Zoumis

Constraint Programming

Bob Dorland

Scheduling for Quantum Computers

Heqi Wang

Traffic Predictions

Jeroen van Dijk

SAT for Multi-Agent Path Finding

Thomas Bos

Explainable Predictive Maintainance

Isha Dijcks

Automating Puzzle Generation

Andrea Nardi

Graph Theory

Zhiyi Chen

(BSc honours) Algorithm Selection

Sander Waij

Multi-Agent Path Finding

Yorick de Vries

Reinforcement Learning for Logistics

Maxim Marchal

MaxSAT for Correlation Clustering

Jens Langerak


Max Ligtenberg

Predictions for Intensive Care

Bhavishya Palavali

Algorithm Selection



Dutch national funding agency


Delft AI Labs


TU Delft