Quantum Machine Learning Conference Announces June Agenda

The free online Quantum Machine Learning Conference will take place on 27 June 2026 at 10:00 CEST, organized by QPoland and Fundacja Quantum AI with strategic partner Cogit. The event features six talks on topics including data quality for quantum computing and quantum associative memory, with speakers such as Pawel Gora, Sven Groppe, and Karol Bartkiewicz. Registration closes on 26 June 2026.

Quantum Machine Learning Conference Announces June Agenda According to the event page on quantiki.org, the free online Quantum Machine Learning Conference is scheduled for 27 June 2026 at 10:00 CEST and is organised by QPoland and Fundacja Quantum AI , with Cogit listed as a strategic partner. The page lists a registration deadline of 26 June 2026 and a short programme of six talks covering topics such as data quality for quantum computing, quantum associative memory, and high-dimensional quantum models, with speakers including Pawel Gora , Sven Groppe , Artur Miroszewski , Jacob Cybulski , Sebastian Dziura , and Karol Bartkiewicz quantiki.org . What happened 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 . Technical details 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 . Industry context 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. What to watch 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. Practical note 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 . Scoring Rationale This is a niche but relevant community event for quantum ML practitioners. It is useful for researchers tracking early experimental methods and cross-disciplinary collaboration, but it is not a major industry-shaping release. Practice with real Ride-Hailing data 90 SQL & Python problems · 15 industry datasets 250 free problems · No credit card See all Ride-Hailing problems /problems/datasets/mobility