Curriculum Vitae
Research scientist working on post-training, reinforcement learning and generative models. A PDF version is available here.
Positions
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Jan 2026 — present
Member of Technical Staff Project Prometheus
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Mar 2025 — Jan 2026
Research Scientist Meta Superintelligence Labs, Zurich Post-training reasoning — led and coordinated efforts around data value and efficient learning in RL and SFT. Led self-improvement and self-play research for agentic models.
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Apr 2025 — present
Guest Scientist ETH Zurich Student supervision on topics of discovery with generative models and RL.
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Oct 2024 — Apr 2025
Postdoctoral Researcher ETH AI Center, Zurich Discovery with generative models and reinforcement learning. Supervisors: Andreas Krause, Marco Hutter, Bernhard Schölkopf.
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May 2024 — Oct 2024
Research Scientist Intern Meta, Zurich Efficiency and fine-tuning of large-scale text-to-image and text-to-video diffusion models.
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Apr 2019 — May 2024
Graduate Researcher Max Planck Institute for Intelligent Systems, Tübingen Research in machine learning, reinforcement learning and implicit layers.
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Jul — Dec 2022
Research Scientist Intern DeepMind, London Score-based (diffusion) generative modeling for inverse design.
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May — Sep 2021
Applied Research Scientist Intern Amazon, Berlin Reinforcement learning for task-oriented dialogue systems, amortized variational inference, normalizing flows.
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Jul — Dec 2018
Researcher Max Planck Institute for Intelligent Systems, Tübingen Research in hierarchical reinforcement learning.
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Sep — Oct 2017
Research Intern Volkswagen AG Data:Lab, Munich Continuous control of mobile robots, path planning and unsupervised object sorting with VAEs and region proposal networks.
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2017
Research Assistant Forschungszentrum Informatik, Karlsruhe Reinforcement learning for continuous motor control via liquid state machines.
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Jan — Jul 2017
Research Fellow Blue Brain Project, EPFL, Geneva Reinforcement learning and reservoir computing for motor control with spiking neural networks.
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Apr — Jul 2016
Data Analytics Intern IBM Research and Development, Böblingen Data analytics and machine learning using Apache Spark.
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Nov 2015 — Mar 2016
Student Research Assistant Fraunhofer IOSB, Karlsruhe Knowledge modeling using Bayesian networks; graphical framework for Bayesian network inference in Java.
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2015
Student Research Assistant CVHCI, Karlsruhe Institute of Technology Classifiers for video analysis of emotion, valence and violence.
Education
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Nov 2024
PhD in Computer Science (summa cum laude, top 1–5%) Max Planck Institute for Intelligent Systems, Tübingen Thesis: Structured, Constrained and Creative Learning. Advisory committee: Georg Martius, Peter Dayan, Michael Muehlebach. Examination committee: Georg Martius, Peter Dayan, Mathias Niepert, Matthias Hein.
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Aug 2017
MSc in Artificial Intelligence Karlsruhe Institute of Technology Fields of study: machine learning, robotics, intelligent systems.
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Jul 2014
BSc in Computer Science University of Zagreb