Quantum Scientist interested in accurate predictions for quantum many-body systems.
I have explored Green’s function techniques for molecules, tensor network states for schematic hamiltonians, and coupled-cluster wave functions for strongly correlated hamiltonians.
Recently, I have made the shift to quantum computing where I explore near-term applications in quantum chemistry and quantum machine learning.
PhD in Physics, 2012
Ghent University
MSEng in Applied Physics, 2008
Ghent University
BSc in Physics, 2008
Ghent University
BSEng in Applied Physics, 2006
Ghent University
I first came to Rice University as a 2014 Belgian American Educational Foundation (BAEF) UGent Postdoctoral Fellow.
Research areas:
During my PhD, I was supported by a personal grant of the Flemish Science Foundation (FWO).
Research areas:
I got the opportunity to fill in for a last minute cancellation at the CQIQC-VIII. I made an overview of the quantum machine learning topics that we are currently investigating.
Optimization of parametrized circuits has proven very powerful for solving quantum chemistry problems on near-term quantum devices. Similar ideas can be applied to transfer the classical machine learning toolbox into the quantum realm. I’ll present our group’s recent work on hybrid quantum algorithms for machine learning including the quantum variational autoencoder, the quantum generator and a proposal for a spiking quantum neuron.