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We are happy to announce the tutors who will guide you through the Jupyter notebooks during the hands-on tutorials!


Anna Dawid-Łękowska (University of Warsaw & Institute of Photonic Sciences, Barcelona)
Ania is doing a Ph.D. jointly at the University of Warsaw and Institute of Photonic Sciences, Barcelona, under the supervision of Dr. Michał Tomza and Prof. Maciej Lewenstein. Her research interests are interpretable and reliable machine learning applied in quantum physics and quantum simulations with ultracold molecules. She obtained a Master’s degree in Chemistry and a Bachelor’s in Chemistry and Biotechnology at the University of Warsaw. Ania is also a part of the school’s Organizing Committee.



Niklas Käming (Universität Hamburg)
Niklas is a Ph.D. student in the group of Prof. Klaus Sengstock at the University of Hamburg. His research focus is the detection of new phases of matter from experimental data and modeling of quantum many-body states with machine learning techniques to develop new experimental protocols for cold quantum gas experiments. Since 2020 he teaches the application and development of distributed algorithms on HPC systems. He acquired his Bachelor’s and Master’s degree with a focus on quantum many-body physics and distributed algorithms at the University of Hamburg.


Korbinian Kottmann (Institute of Photonic Sciences, Barcelona)
Korbinian is a Ph.D. student in the theory groups of Prof. Antonio Acín and Prof. Maciej Lewenstein at ICFO in Barcelona. His main interests are (Quantum) Machine Learning, Quantum Many-Body Physics, and everything relating the two. He did his Master’s degree in Physics at the Ulm University in Germany.


Gorka Muñoz Gil (Institute of Photonic Sciences, Barcelona)
Gorka is a Postdoctoral Researcher at the Prof. M. Lewenstein group at ICFO. His research interests range from classical and quantum many-body physics, their analysis with machine learning techniques, and the development of physically inspired machine learning algorithms. Especially, he works in developing experimentally friendly techniques that bridge theoretical models with real-world data.



Borja Requena Pozo (Institute of Photonic Sciences, Barcelona)
Borja is doing a Ph.D. at the Institute of Photonic Sciences, Barcelona, under the supervision of Prof. Maciej Lewenstein and Prof. Ferran Mazzanti. His research focuses on the development of numerical methods based on machine learning to study problems in quantum many-body physics. He obtained his Master’s degree in Intelligent Interactive Systems at Pompeu Fabra University and his Bachelor’s degree in Engineering Physics at the Polytechnic University of Catalonia.



Topics covered:

  1. Phase classification with supervised and unsupervised learning. Lectures: Eliška Greplová
  2. Gaussian Process Regression. Lectures: Roman Krems
  3. Quantum Neural States. Lectures: Giuseppe Carleo and Filippo Vicentini
  4. Reinforcement learning. Lectures: Florian Marquardt

We will work in Google Colaboratory. You need to bring your own computers!