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Jakub Mareček

Jakub received his bachelor and masters degrees from Masaryk University, in Brno, the Czech Republic, and his Ph.D. degree from the University of Nottingham, Nottingham, U.K., in 2006, 2009, and 2012, respectively. He has worked in two start-ups, at ARM Ltd., at the University of Edinburgh, at the University of Toronto, at IBM Research -- Ireland, and at the University of California, Los Angeles. He is currently a faculty member at the Czech Technical University in Prague, the Czech Republic. He designs and analyses algorithms for optimisation and control problems across a range of application domains, including power systems, quantum computing, and robust statistics.

For more details, please see:
CV

List of pre-prints and publications

List of patents

GitHub profile

Supervisor to the following students

Antonio Bellon (CTU)
Xiaoyu He
(CTU)
Dominik Hodan (Imperial College London)
Shenyuan Ma (CTU)
German Martinez Matilla (CTU)
Allahkaram Shafiei
(CTU)
Quan Zhou (Imperial College London)

Mentor to the following post-docs

Johannes Aspman
Gilles Bareilles
Ales Wodecki

Close collaborators at CTU

Didier Henrion
Vyacheslav Kungurtsev

Previously, I have worked with a number of excellent post-doctoral fellows:

  • Georgios Korpas, whose PhD was from the Trinity College Dublin (2019). Subsequent position: Research scientist at HSBC.
  • Libor Caha, whose PhD was from the Slovak Academy of Sciences (2021). Subsequent position: Post-doc at Technical University of Munich.
  • Philipp Haehnel, whose PhD was from the Trinity College Dublin (2018). Subsequent position: Post-doc at Harvard University.

Previously, I have also worked with a number of PhD students while at IBM Research.

  • Olivier Massicot at the University of Illinois Urbana-Champaign (2019-2020). Continues his PhD studies at UIUC.
  • Anna de Rosier at the University of Gdansk (2019–2020): Subsampling in Testing Non-Locality. Subsequent position: Post-doc at Maynooth University.
  • Cunlu Zhou at the University of Notre Dame (2018): Alternative Methods in Semidefinite Programming; Subsequent position: Post-doc at the University of Toronto
  • Jie Liu at the Lehigh University (2017–2018): Hybrid Methods for Polynomial Optimisation; Subsequent position: Research Scientist at Innopeak Technology
  • Jing Xu at the University of Pennsylvania (2017): Robust Parameter Estimation in Gaussian Mixture Models; Subsequent position: ML Engineer at Facebook (FAIR)
  • Alan Liddel at the University of Notre Dame (2016): Hybrid Methods for Polynomial Optimisation; Subsequent position: Software Engineering Manager at Path Robotics
  • Martin Takac at the University of Edinburgh (2014): First-Order Methods for Semidefinite Programming; Subsequent position: Tenured faculty associate professor at Lehigh University
  • Wann-Jiun Ma at the University of Notre Dame (2014): First-Order Methods for Semidefinite Programming; Subsequent position: Post-doc at Duke University
  • Tim McCoy at the University of Notre Dame (2013): Homotopy Methods in Power Systems; Subsequent position: Software engineer at Google
AutoFair (Human-Compatible AI with Guarantees)

AutoFair (Human-Compatible AI with Guarantees)

Horizon Europe project for fair AI algorithms supported by the EU with 3,8 million Euros. Imperial College London, the Israeli Institute of Technology Technion and the National and Capodistrian University of Athens as well as partners from the industry collaborate on developing explainable and transparent algorithms.

Research Results

Predictability and Fairness in Social Sensing

Predictability and Fairness in Social Sensing

The manner in which agents contribute to a social-computing platform (e.g., social sensing, social media) is often governed by distributed algorithms. We explore the guarantees available in situations, where fairness among the agents contributing to the platform is needed.

Warm-starting Quantum Optimization

Warm-starting Quantum Optimization

Many optimization problems in binary decision variables are hard to solve. In this work, we demonstrate how to leverage decades of research in classical optimization algorithms to warm-start quantum optimization algorithms. This allows the quantum algorithm to inherit the performance guarantees from the classical algorithm used in the warm-start.

AI Act on the horizon: Companies should start preparing

AI Act on the horizon: Companies should start preparing

Before Christmas, so-called trilogue negotiations between the European Parliament, the Council of the European Union and the European Commission culminated in a preliminary agreement on a regulation known as the Artificial Intelligence Act ("Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence"). A few more formal steps will be needed, but the regulation will be in force before the European Parliament elections in June 2024. And after transitional periods (from 6 to 36 months, depending on the risks), it will come into effect.

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