Talks & Teaching
Few selected recorded scientific presentations on the recent research topics in QMAI:
Quantum Error Correction via Hamiltonian Learning, Perimeter Institute for Theoretical Physics (2019)
Predicting Phase Transitions in Many-Body Physics, Swiss Federal Institute of Technology Lausanne (2020)
Fully Automated Identification of 2D-material Samples, Virtual Science Forum (2019)
Understanding Quantum Matter Using Intelligent Machines, QWorld Webinar, 2021
Quantum Big Data: Where Condensed Matter Meets Quantum Computing, QRST Toronto, 2021
If you would like to have slides from any of my the non-recorded talks, please just get in touch: email@example.com
Machine Learning for Quantum Experiments @ TU Delft
Currently, I am teaching TN2513 Computational Science for bachelor students at TU Delft. We use inverted classroom approach , where students learn the methods by completing Jupyter Notebooks while asking questions via forum.
I also contribute to AP3681 Fairytales of Theoretical Physics, a masters course at TUDelft, where students get to work on exciting problems in contemporary theoretical physics.