Quantum Machine Learning Conference Announces June Agenda

According to the event page on quantiki.org, the free, online Quantum Machine Learning Conference takes place on 27 June 2026 at 10:00 CEST, organised by QPoland and Fundacja Quantum AI, and supported by strategic partner Cogit. The event page lists a registration and submission deadline of 26 June 2026 (quantiki.org).

The quantiki.org programme lists six scheduled talks and speakers: "Introduction to Quantum Machine Learning" by Pawel Gora; "Data Quality in the Era of Quantum Computing" by Sven Groppe; "Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations" by Artur Miroszewski; "Paradoxes of High-Dimensional Quantum Models" by Jacob Cybulski; "Multi-Source Classification with Quantum Architecture Search" by Sebastian Dziura; and "Quantum Associative Memory with Photonic Quantum Memristors" by Karol Bartkiewicz (quantiki.org).

Conferences focused on quantum machine learning typically mix fundamental theory and early application work, providing a forum for cross-pollination between quantum hardware researchers and ML practitioners. Sessions on data quality, measurement allocation, and architecture search reflect practical concerns when adapting classical ML workflows to noisy or resource-constrained quantum hardware.

Observers should track whether presenters publish accompanying code, data, or preprints after the talks, and whether follow-on workshops or collaborative projects emerge from the meeting. Tracking registration activity prior to the 26 June deadline can indicate community interest in the specific topics listed on the programme.

The event page on quantiki.org provides registration instructions and links for staying updated; interested attendees must sign up by the stated deadline (quantiki.org).