Nikolaus Vertovec

Nikolaus Vertovec

Junior Fellow in Artificial Intelligence

Oxford University

Biography

I am a Career Development Fellow in Artificial Intelligence at St Hugh’s College, Oxford, and a member of the Oxford Control & Verification group within the Department of Computer Science. My work focuses on safe reinforcement learning and safe learning-based control.

I earned my Bachelor’s degree in Electrical Engineering from ETH Zurich in 2019. Following this, I worked at NASA’s Jet Propulsion Laboratory on the Mars 2020 rover mission. In 2024, I completed my DPhil at Oxford’s Department of Engineering Science.

My research interests include the verification of learned models, finite-sample learning, and safe reinforcement learning. I have applied my research to spacecraft trajectory design and airborne wind energy systems, among other applications.

Interests
  • Reachability analysis
  • Statistical learning theory
  • Reinforcement Learning
  • Airborne Wind Energy
Education
  • DPhil in Engineering Science, 2024

    Oxford University

  • BSc in Electrical Engineering and Information Technology, 2019

    ETH Zürich (Swiss Federal Institute of Technology)

Experience

 
 
 
 
 
NASA Jet Propulsion Laboratory
Intern
Oct 2019 – Mar 2010 Pasadena, USA
Worked on the Mars2020 Rover
 
 
 
 
 
Akademische Raumfahrtsinitiative Schweiz (ARIS)
GNC Engineer
Sep 2018 – Jul 2019 Zurich, Switzerland
Designed the Control Systems for a Sounding Rocket
 
 
 
 
 
ETH Zürich
Teaching Assistant
Feb 2019 – Jul 2019 Zurich, Switzerland
Taught Numerical Methods for second-year bachelor students

Recent Publications

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(2024). Finite sample learning of moving targets .

(2024). Safety-Aware Hybrid Control of Airborne Wind Energy Systems. In Journal of Guidance, Control, and Dynamics, vol. 47, no. 2, pp. 326–338.

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(2023). State Aggregation for Distributed Value Iteration in Dynamic Programming. In IEEE Control Systems Letters, vol. 7, pp. 2269–2274.

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(2022). Multi-objective low-thrust spacecraft trajectory design using reachability analysis. In European Journal of Control, vol. 69, p. 100758.

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(2022). Verification of safety critical control policies using kernel methods. In 2022 European Control Conference (ECC), London, United Kingdom, pp. 1870-1875.

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(2021). Multi-objective minimum time optimal control for low-thrust trajectory design. In 2021 European Control Conference (ECC), Delft, Netherlands, pp. 1975-1980.

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