9th International Conference on
Quantum Techniques
in Machine Learning
16-21 November, Singapore
Theme for 2025:
AI for Quantum, Quantum for AI
Quantum Techniques in Machine Learning (QTML) is a leading international conference at the forefront of quantum science and machine learning. Held annually, it brings together researchers and industry experts to explore how quantum computing can transform learning, optimization, and data-driven discovery. Through a series of scientific talks and discussions, QTML fosters collaboration and advances research on the interplay between quantum mechanics and machine learning, from foundational theory to real-world applications.
QTML was first hosted in Verona, Italy (2017), then in Durban, South Africa (2018), Daejeon, South Korea (2019), virtual (2020, hosted by Zapata Computing), virtual (2021, hosted by RIKEN-AIP), Naples (2022), CERN (2023), Melbourne (2024). The ninth edition, QTML 2025, will be hosted by the Centre for Quantum Technologies in Singapore.
Congratulations to authors with papers accepted for QTML2025! See the accepted papers listed here.
Early Bird Registration until 25 Sept 2025
Student: SGD 850
Student (with conference dinner): SGD 1050
Standard: SGD 1050
Standard (with conference dinner): SGD 1250
Late Registration from 26 Sept 2025 – 16 Oct 2025
Student: SGD 1050
Student (with conference dinner): SGD 1250
Standard: SGD 1250
Standard (with conference dinner): SGD 1450
Registration fee include
– Full access to all conference sessions, tutorials and poster sessions
– Daily lunch, morning & afternoon coffee breaks
– Conference materials (name badge, door gifts etc.)
– Admission to the conference dinner if you have registered for conference dinner option.
Speakers
We are pleased to announce the keynote, invited and tutorial speakers for Quantum Techniques in Machine Learning in 2025. Find more details of the speakers here
Conference Topics
We welcome contributions on a broad range of topics, including but not limited to:
Quantum algorithms for machine learning applications
Hybrid quantum-classical approaches for learning and optimization
Encoding and processing of data in quantum systems
Theoretical foundations of quantum learning
Quantum variational circuits and their applications
Quantum state and process tomography with learning-based approaches
Tensor methods and quantum-inspired machine learning
Quantum state reconstruction from data
Quantum-enhanced robustness in machine learning models
Machine learning techniques for experimental quantum information science
Fuzzy logic in quantum machine learning
Quantum kernel methods and their applications
Important Dates
1. Call for Papers Announcement: April 15, 2025
2. Paper Submission Deadline: June 8, 2025, 23:59 (Anywhere on Earth)
3. Poster Submission Deadline: extended to June 25, 2025, 23:59 (Anywhere on Earth)
4. Registration Opens: 25 August, 2025
5. Notification to Authors: 25 August, 2025
6. Early-Bird Registration Deadline: September 25, 2025 (Anywhere on Earth)
7. Registration Deadline: October 16, 2025 (Anywhere on Earth)
8. Conference Dates: November 16–21, 2025
QTML 2025 Committees
Programme Committee
- Maria Schuld (Co-chair) – Xanadu
- Ryan Sweke (Co-chair) – African Institute for Mathematical Sciences (AIMS)
- Abhinav Deshpande – University of Maryland
- Adrian Perez-Salinas – Freie Universität Berlin
- Alba Cervera Lierta – Barcelona Supercomputing Center
- Alessandra Di Pierro – Università di Verona
- Alexey Melnikov – Terra Quantum AG
- Annabelle Bohrdt – LMU München
- Antonio Mele – Freie Universität Berlin
- Armando Angrisani – EPFL
- Ben Jaderberg – IBM
- Brian Coyle – QC Ware
- Chae-Yeun Park – Yonsei University
- Dar Gilboa – Google
- David Windridge – Middlesex University
- Davide Venturelli – NASA
- Elias Combarro – University of Oviedo
- Eliska Greplova – Delft University of Technology
- Eric Anschuetz – Caltech
- Evan Peters – University of Waterloo
- Francesco Tacchino – IBM
- Ilya Sinayskiy – University of KwaZulu-Natal
- Ingo Roth – TII Abu Dhabi
- Jakob Kottmann – University of Augsburg
- Jarrod McClean – Google
- Jean-Roch Vlimant – Caltech
- Jens Eisert – Freie Universität Berlin
- Kohei Nakaji – NVIDIA
- Kunal Sharma – IBM
- Leonardo Banchi – University of Florence
- Lirandë Pira – National University of Singapore
- Lukasz Cincio – Los Alamos National Laboratory
- Manuel Rudolph – EPFL
- Marcel Hinsche – Freie Universität Berlin
- Marco Cerezo – Los Alamos National Laboratory
- Mark Wilde – Cornell University
- Martin Larocca – Los Alamos National Laboratory
- Matthias C. Caro – University of Warwick
- Michele Grossi – CERN
- Mina Doosti – University of Edinburgh
- Nana Liu – Shanghai Jiao Tong University
- Oscar Dahlsten – City University Hong Kong
- Patrick Rebentrost – National University of Singapore
- Ruslan Shaydulin – JPMorgan Chase
- Ryan LaRose – Michigan State University
- Shanawaz Ahmed – Chalmers University of Technology
- Shouvanik Chakrabarti – JPMorgan Chase
- Sofiene Jerbi – Freie Universität Berlin
- Srinivasan Arunachalam – IBM
- Sumeet Khatri – Virginia Tech
- Tai-Danae Bradley – City University of New York
- Thiparat Chotibut – Chulalongkorn University
- Tobias Haug – TII Abu Dhabi
- Vedran Dunjko – LIACS, Leiden University
- Vojtech Havlicek – IBM
Steering Committee
- Alessandra Di Pierro, Università di Verona, Italy
- Francesco Petruccione, Stellenbosch University, South Africa
- June-Koo Kevin Rhee, KAIST, South Korea
- Michele Grossi, CERN, Switzerland
- Giovanni Acampora, Università di Napoli, Italy
- Muhammad Usman, CSIRO and University of Melbourne, Australia
Organising Committee
- Patrick Rebentrost (Co-chair), CQT, National University of Singapore
- Lirandë Pira (Co-chair), CQT, National University of Singapore
- Marco Tomamichel, CQT, National University of Singapore
- Dario Poletti, CQT, Singapore University of Technology and Design
- Yvonne Gao, CQT, National University of Singapore
- Valerio Scarani, CQT, National University of Singapore
- Tan Shao Tao, CQT, National University of Singapore (Admin Support)
- Casandra Lim, CQT, National University of Singapore (Admin Support)
Locations
Tutorials
Sunday 16 November
Tutorials will be held at
National University of Singapore
Lecture Theatre 31,
Faculty of Science S16
6 Science Drive 2,
Singapore 117546
By Train: Kent Ridge MRT Station
By Bus: 95 / 96 / 151
From the airport: Approx. 20 mins by taxi/car
Conference
Monday 17 Nov - Thursday 20 Nov
QTML 2025 conference sessions will be at
Marina Bay Sands Singapore
Sands Expo and Convention Centre,
Level 3, Heliconia Junior Ballroom
10 Bayfront Ave, Singapore 018956
By Train: Bayfront MRT Station
By Bus: 97 / 106 / 518 / 133 / 502
From the airport: Approx. 18 mins by taxi/car
Conference
Friday 21 November
Last Day of QTML 2025
Parallel sessions will be at
National University of Singapore
Lecture Theatre 16 & 17
School of Computing COM2
15 Computing Drive
Singapore 117418
By Train: Kent Ridge MRT Station
By Bus: 95 / 96 / 151
From the airport: Approx. 20 mins by taxi/car
Sponsors
If you are interested in becoming a sponsor, please get in touch with Lirandë Pira at
lpira@nus.edu.sg