Quantum Techniques in Machine Learning 2020

Cambridge, Massachusetts, USA
09-12 November 2020

UPDATE: Registration is now open!


Quantum Techniques in Machine Learning (QTML) is an annual international conference 

focusing on the interdisciplinary field of quantum technology and machine learning. The goal of the conference is to gather leading academic researchers and industry players to interact through a series of scientific talks focussed on the interplay between machine learning and quantum physics.


QTML was first hosted in Verona, Italy (2017), then Durban, South Africa (2018), and was last held in Daejeon, South Korea (2019). This is the conference's fourth annual year, and will be held online.

Example topics at QTML include, but are not limited to:

  • Quantum algorithms for machine learning tasks

  • Quantum state reconstruction from data

  • Machine learning for experimental quantum information

  • Machine learning for Hamiltonian learning

  • Variational quantum algorithms

  • Learning and optimization with hybrid quantum-classical methods

  • Quantum machine learning applications for industry

  • Tensor network methods and quantum-inspired machine learning

  • Data encoding and processing in quantum systems

  • Quantum learning theory


Important Dates

Nov 5

Last Day to Register

Nov 9-12




Confirmed Speakers

•    Annabel Bohrdt (TUM, Harvard)

•    Hans Briegel (Innsbruck)
•    Juan Carrasquilla (Vector Institute)
•    Patrick Coles (Los Alamos National Lab.)
•    Vedran Dunjko (Leiden University)
•    Aram Harrow (MIT)

•    Estelle Inack (Perimeter Institute)

•    Maria Kieferova  (University of Technology Sydney)

•    Emine Kucukbenli (Harvard)
•    Nana Liu (Shanghai Jiao Tong University)
•    Eleanor Rieffel (NASA Ames)
•    Maria Schuld (University of KwaZulu-Natal, Xanadu)

•    Dries Sels (Harvard)
•    Miles Stoudenmire (Flatiron Institute)
•    Giacomo Torlai (Flatiron Institute)
•    Lei Wang (Chinese Academy of Sciences)

Program Schedule
Full Program Details Coming Soon!


Registration is free!




Once registered, you will receive intermittent emails with further details on how to access the conference webinar and poster sessions.

The last day to register is November 5.

About QTML


QTML 2020 Contact Information

QTML Steering committee

  • Alessandra Di Pierro (Università di Verona)

  • Stefano Mancini (Università di Camerino)

  • Francesco Petruccione (University of KwaZulu-Natal)

  • June-Koo Kevin Rhee (KAIST)

Organizing committee for QTML 2020

  • Jonathan Olson (Zapata Computing, Chair)

  • Alessandra Di Pierro (Università di Verona)

Program committee for QTML 2020

  • Alejandro Perdomo-Ortiz (Zapata Computing, Co-Chair)

  • Roger Melko (University of Waterloo/Perimeter Institute, Co-Chair) 

  • Alessandra Di Pierro (Università di Verona)

  • Amira Abbas (University of KwaZulu-Natal)

  • Giovanni Acampora (Università di Napoli Federico II)

  • Matthias Degroote (University of Toronto)

  • Vedran Dunjko (LIACS, Leiden University)

  • Christina Giarmatzi (University of Queensland)

  • Aroosa Ijaz (Xanadu, Canada)

  • Maria Kieferova (University of Technology Sydney)

  • Lucas Lamata (Universidad de Sevilla)

  • Alba Cervera Lierta (University of Toronto)

  • Nana Liu (Shanghai Jiao Tong University)

  • Daniel Park (Korea Advanced Institute of Science and Technology)

  • Minh Ha Quang (RIKEN)

  • June-Koo Kevin Ree (Korea Advanced Institute of Science and Technology)

  • Davide Venturelli (USRA Research Institute for Advanced Computer Science, NASA)


Scientific advisory committee for QTML 2020

  • Hans Briegel (University of Innsbruck)

  • Juan Carrasquilla (Perimeter Institute, Vector Institute)

  • Ignacio Cirac (Max Planck Institute of Quantum Optics)

  • Eun-Ah Kim (Cornell University)

  • Eleanor Rieffel (NASA)

  • Maria Schuld (Xanadu, University of KwaZulu-Natal)


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