About me

I am a Research Intern at the Max Planck Institute for Intelligent Systems, supervised by Bernhard Schölkopf.

I work on JEPA-style world models.

Before moving into machine learning, I completed my MSc at ETH Zurich and BSc at TU Munich, where I focused on quantum computing, particularly quantum algorithms and quantum learning theory.

Education

  1. ETH Zurich

    2023 — 2026

    MSc Quantum Engineering

  2. Technical University of Munich

    2020 — 2023

    BSc Physics

Selected Papers

[*] equal contribution  ·  see my Google Scholar for the full list

  • Sensorimotor World Models thumbnail

    Sensorimotor World Models: Perception for Action via Inverse Dynamics

    Petr Ivashkov, Randall Balestriero, Bernhard Schölkopf

    arXiv (2026)

  • Learning Lindbladians with QEC thumbnail

    Learning Arbitrary Lindbladians with Quantum Error Correction

    Nikita Romanov, Petr Ivashkov, Weiyuan Gong, Ishaan Kannan, Andi Gu, Hong‑Ye Hu, Susanne F. Yelin

    arXiv (2026)

  • Ansatz-free Lindbladian learning thumbnail

    Ansatz-Free Learning of Lindbladian Dynamics In Situ

    Petr Ivashkov*, Nikita Romanov*, Weiyuan Gong, Andi Gu, Hong‑Ye Hu, Susanne F. Yelin

    arXiv (2026)

  • QKAN thumbnail

    QKAN: Quantum Kolmogorov-Arnold Networks with Applications in Machine Learning and Multivariate State Preparation

    Petr Ivashkov, Po‑Wei Huang, Kelvin Koor, Lirandë Pira, Patrick Rebentrost

    npj Quantum Information 12, 73 (2026)

  • Quantum Monte Carlo thumbnail

    From Quantum-Enhanced to Quantum-Inspired Monte Carlo

    Johannes Christmann*, Petr Ivashkov*, Mattia Chiurco, Guglielmo Mazzola

    Phys. Rev. A 111, 042615 (2025)

  • Dynamic-circuit POVMs thumbnail

    High-Fidelity, Multiqubit Generalized Measurements with Dynamic Circuits

    Petr Ivashkov, Gideon Uchehara, Liang Jiang, Derek S. Wang, Alireza Seif

    PRX Quantum 5, 030315 (2024)