Postdoctoral Fellow

Aspuru-Guzik group, University of Toronto

Jul 2018 – Present Toronto, ON
Research areas:

  • Near-term applications of quantum computing
  • Quantum chemistry algorithms
  • Variational quantum eigensolver
  • Quantum Machine Learning

Postdoctoral Fellow

Aspuru-Guzik group, Harvard University

Jan 2018 – Jul 2018 Cambridge, MA
Research areas:

  • Near-term applications of quantum computing
  • Quantum chemistry algorithms
  • Variational quantum eigensolver

Postdoctoral Fellow

Scuseria group, Rice University

Sep 2014 – Aug 2017 Houston, TX

I first came to Rice University as a 2014 Belgian American Educational Foundation (BAEF) UGent Postdoctoral Fellow.

Research areas:

  • Coupled-cluster ansatzes
  • Symmetry breaking and restoration
  • Strong correlation

Postdoctoral Fellow

Verstraete group, Ghent University

Jan 2013 – Jun 2014 Ghent, Belgium
Research areas:

  • Projected Entangled Pair States
  • Transfer matrix formalism
  • AKLT model excitations

PhD student

Van Neck group, Ghent University

Sep 2008 – Dec 2012 Ghent, Belgium

During my PhD, I was supported by a personal grant of the Flemish Science Foundation (FWO).

Research areas:

  • Green’s function techniques
  • Random Phase Approximation
  • Molecular hamiltonians

Recent Publications

more publications

Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such …

Recent & Upcoming Talks

I was supposed to give a live seminar in Fredericton to the Data Scince Practitioners East Meetup. Covid-19 decided otherwise and I gave my talk over Zoom. I presented work from our research group in quantum machine learning and gave some examples of more future-proof examples where quantum computing and data science meet.

A talk about the quantum machine learning projects in the Aspuru-Guzik group. I focused on the chemical motivation of the projects. This culminates in a current research direction: detect quantum phases in the latent space of a quantum variational autoencoder.

I will be giving a lecture on quantum computing for quantum chemistry at the CECAM workshop in Tel Aviv.

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.

A group meeting talk about our recent preprint. Drawing links between neuromorphic neural networks and quantum neurons.


  • Lash Miller #434, 80 St. George Street, Toronto M6S 3H5