Frederik Baymler Mathiesen, PhD Candidate @ TU Delft

Delft Center for Systems and Control. HERALD Lab.


C-3-260, Building 34

Mekelweg 2, 2628 CD

Delft, Netherlands


I am a third-year PhD student at Delft Center for Systems and Control, TU Delft under the supervision of Dr. Luca Laurenti and Dr. Simeon Calvert. I obtained my BSc and MSc in Computer Science with a specialization in Machine Learning from the Aalborg University (AAU), Denmark, in 2019 and 2021 respectively. As part of my MSc, I spent a semester at UC Berkeley as a visiting student with a focus on Computer Science and Fintech.

During my studies at AAU, I worked for Ambolt and IntelliGo on various Machine Learing-related projects, primarily focusing on real-time monitoring and optimization of traffic lights.

Research interests

My research is centered around verification and synthesis of safe controllers in uncertain and stochastic environments. The primary application domain is autonomous vehicles where I model human behavior using probabilistic machine learning and verify controllers with stochastic barrier functions.

Keywords: Stochastic Barrier Functions, Bayesian Neural Networks, Verification of Neural Networks, Scenario Approach Theory, Autonomous Vehicles.


  • The Scenario Approach for Stochastic Barrier Functions, Cyber-Physical Systems lab @ ICTEAM, UCLouvain, April 2023.

Press coverage

Aalborg University logo

Awards and grants

  • Student Travel Grant, American Control Conference, 2023.
  • Fintech scholarship, Spar Nord Foundation, Spring 2020, including placement at UC Berkeley.

Selected publications

  1. arXiv
    Inner approximations of stochastic programs for data-driven stochastic barrier function design
    Frederik Baymler Mathiesen, Licio Romao, Simeon C. Calvert, and 2 more authors
  2. Safety Certification for Stochastic Systems via Neural Barrier Functions
    Frederik Baymler Mathiesen, Simeon C. Calvert, and Luca Laurenti
    IEEE Control Systems Letters, 2023