Gorka Muñoz-Gil

I'm a Marie SkƂodowska-Curie postdoctoral fellow in the Quantum Information and Computation group at the University of Innsbruck (UIBK), Austria.

I got my PhD in the Quantum Optics theory group at ICFO ( November 2020! ). Before that I got a MSc in Photonics at the Universitat PolitĂšcnica de Catalunya and BSc in Physics at the Universitat AutĂČnoma de Barcelona .

A longer description of what I have been doing during these years can be found in my CV





Main areas of research

In recent years, I have been captivated by the potential Machine Learning (ML) techniques offer to the study of Physics, and in particular in the design of interpretable solutions that can assist researchers to gain further insight from their experiments!

Anomalous diffusion: from life to machines

Anomalous diffusion was the focus of my PhD Thesis. Motivated by collaborations with Prof. Maria GarcĂ­a-Parajo (ICFO) and Prof. Carlo Manzo (UVic), I developed theoretical models to better understand micro- and nano-particle motion in cells. Realizing the potential of ML to bridge experimental observations with theory, we pioneered its use in anomalous diffusion and organized the AnDI Challenge, a scientific competition that has already celebrated two editions.
Since then, I have advanced anomalous diffusion characterization by proposing the STEP method—which probes diffusion at the single-step level—and showing that unsupervised learning can rediscover the fundamental components of our diffusion theories (link). We have also validated these approaches experimentally, gaining new insights into the process of particle condensation (link). Lately, we have studied how artifical learning agents can be used to find diffusion-based optimal foraging strategies (link).

ML in Quantum Physics

I also apply Machine Learning to the quantum realm, starting with the deep connection between Boltzmann machines and spin models, which led to the (RAPID) architecture. We then employed reinforcement learning for the certification of quantum systems (link).
More recently, we introduced powerful denoising diffusion models for quantum circuit synthesis, which earned a cover feature in Nature Machine Intelligence. This approach opens exciting new avenues in quantum computing that I look forward to exploring further.

Science beyond science

Science doesn’t end with publications. I love engaging in diverse projects that extend my research beyond the lab. For instance, I’m part of the Night up project, studying light pollution through citizen science. I also collaborated on a quantum-inspired music piece, performed by Reiko Yamada at the Sonar Festival 2021. In addition, I frequently participate in outreach initiatives for students and the general public—see the Teaching tab for more details!

News

Mar 2025 :trophy: I won the Postdoc Poster Prize award at the AI4Quantum conference for our poster on generating quantum circuits with diffusion models!
Mar 2025 :european_union: I recently contributed to the “Artificial Intelligence and Quantum Computing White Paper”, a call to the EU to invest in combining quantum computing and artificial intelligence.
Mar 2025 :page_with_curl: New pre-print! We introduce a reinforcement learning framework for optimizing stochastic search processes via adaptive resetting, uncovering interpretable strategies that surpass existing benchmarks.

Recent selected publications

  1. Proc. Natl. Acad. Sci.
    Stochastic particle unbinding modulates growth dynamics and size of transcription factor condensates in living cells
    Muñoz-Gil, Gorka, Romero, Catalina, Mateos, Nicolas, Llobet Cucalon, Lara Isabel, Filion, Guillaume, Beato, Miguel, Lewenstein, Maciej, Garcı́ia-Parajo, Marı́ia, and Torreno-Pina, Juan
    Proceedings of the National Academy of Sciences 2022
  2. i.p.a. Nat. Commun.
    Quantitative evaluation of methods to analyze motion changes in single-particle experiments (AnDi Challenge 2)
    Muñoz-Gil, Gorka, Bachimanchi, Harshith, Pineda, JesĂșs, Midtvedt, Benjamin, Lewenstein, Maciej, Metzler, Ralf, Krapf, Diego, Volpe, Giovanni, and Manzo, Carlo
    In principle accepted in Nature Communications 2023
  3. Nat. Mach. Intell.
    Quantum circuit synthesis with diffusion models
    FĂŒrrutter, Florian, Muñoz-Gil, Gorka, and Briegel, Hans J
    Nature Machine Intelligence 2024