Seongmuk Khang

I am a quantum algorithm researcher at Qunova Computing. My broader research goal is to design quantum algorithms that can outperform classical methods under realistic hardware constraints and for real-world problems, while clarifying the conditions under which practical quantum advantage can be achieved.

I received my B.Eng. in Informatics and Imaging Systems from the Faculty of Engineering at Chiba University, with support from the Korea-Japan Joint Scholarship Program for Science and Engineering Students. I later earned my M.Eng. in Applied and Cognitive Informatics from the Division of Mathematics and Informatics at Chiba University, conducting research under the supervision of Prof. Yuichiro Fujiwara.

My research focuses on the trainability and training dynamics of parameterized quantum circuits, studied through light-cone structure, the QNTK, and Hessian analysis. At Qunova Computing, I also work on hybrid quantum-classical methods for the Shortest Vector Problem on structured lattice instances.