I am a physicist interested in quantum devices, artificial intelligence and topology in condensed matter physics.
I am leading Quantum Matter and AI (QMAI) group at Kavli Institute of Nanoscience (TU Delft). Get to know the rest of our team here and learn more about the boundary crossing research that my group is doing here.
Get in touch via email: email@example.com.
02/2024 new PhD student Aram Shojaei. Welcome!
02/2024 Arash's paper on quantifying non-stabilizerness of quantum circuits published in SciPost Physics. Congratulations!
01/2024 Eliska's high level intro talk on intersection of quantum physics and machine learning @ CERN can be streamed here
12/2023 New preprint about needs and challenges in automating semiconductor quantum devices.
11/2023 We have three new postdocs: Ana Silva, Dmytro Oriekhov and Thomas Spriggs. Ana is supported by NWO Quantum Inspire, Dima by Kavli Innovation Award and Thomas by Quantum Delta. Welcome!
11/2023 Arash and Vini presented their results at QTML2023.
10/2023 Our conditional generative adversarial technique for Hamiltonian learning published in Physical Review Applied. Congratulations, Rouven!
10/2023 Our EdX course "Machine Learning for Semiconductor Quantum Devices" is up!
09/2023 Together with Delft colleagues we received a 5 million EUR Kavli Institute Innovation Award.
06/2023 Eliska's Perimeter talk on Automated Control of Engineered Quantum Materials can be streamed here.
06/2023 Together with QuTech and amazing team of international collaborators we received an ARO grant. We'll be doubling our efforts on automated control of spin qubits!
05/2023 Jin's second PhD paper published in Physical Review Research! We figured out how to use topology to stabilize entanglement on a superconducting chip.
04/2023 Together with QuTech and Uni Aalto we made a generative model that can learn key parameters in experimental Kitaev chains really really well. Paper now on arXiv! Congratulations Rouven!
02/2023 Automated Bound State Reconstruction in Bilayer Graphene Quantum Dots now published
in Physical Review Applied! Congratultions Jozef!
01/2023 New PhD student Valentina Gualtieri!
12/2022 Untrained Physically Informed Neural Network for Image Reconstruction of Magnetic Field Sources
now published in Physical Review Applied as Editors' Suggestion.
12/2022 We received NWO Quantum Delta funding!
11/2022 Together with other EU institutions we kicked off Quantum Flagship project IGNITE!
10/2022 Machine Learning for Quantum Experiments course is live!
09/2022 new PhD student Tanko Tanev!
08/2022 Eliska's lectures and notebooks for Topological Matter School now online
07/2022 very cool collaboration with Basel University on NN-assisted reconstruction of magnetization maps on arXiv!
05/2022 Jin's second PhD paper out on arXiv! We show how to engineer superconducting circuits using symmetries that protect entanglement in a topological way.
05/2022 Arash's first PhD paper out on arXiv! We show exciting connection between specific correlators in quantum circuits and quantum resources of the resulting state.
04/2022 Book of lecture notes from Warsaw Machine Learning School is now on arXiv!
03/2022 Our new optimizer for recontructing Hamiltonians of bilayer graphene quantum dots is now on arXiv!
02/2022 Our Hamiltonian learning for large scale quantum systems (and Jin's first PhD paper) now published in Physical Review A!
02/2022 Our interpretable neural network quantum states now published in Physical Review Research .
12/2021 Eliska receives NWO grant VENI.
12/2021 QMAI is joining Dutch Quantum Cloud computer Quantum Inspire.