Workshop “A Hands-on Introduction to Quantum Machine Learning (QML)” by Dr. Hakan DOĞA Held
The workshop titled “A Hands-on Introduction to Quantum Machine Learning (QML)” delivered by Dr. Hakan DOĞA was held on March 2, 2026 at 10:30 AM in Room C101 of the Faculty Building. The event attracted significant interest and provided participants with a comprehensive overview of the fundamentals of quantum machine learning (QML) as well as current developments in the field.
During the workshop, Dr. DOĞA discussed kernel-based methods in quantum machine learning, highlighting their potential and limitations while also addressing alternative approaches. In the final part of the program, a brief demonstration of Quantum Kernel Training (QKT) was presented using a simple dataset.
Dr. Hakan DOĞA is a mathematician specializing in quantum algorithm development at the intersection of mathematics, quantum computing, and biomedical research. His research covers areas such as protein structure prediction, quantum molecular simulations, clinical trial optimization, and tensor-based quantum methods for biomedical data analysis. He has collaborated with the Cleveland Clinic and has participated in international initiatives including DARPA Quantum Benchmarking, the NIH Quantum Challenge, and Wellcome Leap Q4Bio. Originally trained in low-dimensional topology and geometry, he also works on quantum algorithms for computing topological invariants such as the Jones polynomial and Betti numbers.
The event was organized by Prof. Dr. Orkide COŞKUNER WEBER and Dr. Semih ALPSOY from the Department of Molecular Biotechnology. The workshop concluded with an engaging question-and-answer session and discussions with the participants.
