Undergraduate at Yonsei University — Physics (B.Sc.) & Integrated Technology (double major), Seoul. Most of what I ship on GitHub sits at the intersection of the three threads below.

Condensed-matter and algorithmic questions drive the modeling: Hamiltonian structure, ground-state preparation, and how approximations in time evolution show up in observables. My first-author work (Feb. 2026) is on deterministic ground-state preparation via power–cosine filtering of time-evolution operators. The same lens carries into numerics: which discretizations and filters keep the physics legible when you move to a circuit or a laptop-scale simulation.

With QIYA · QISCA I mostly build and benchmark Hamiltonian simulation and noise-aware ansatz variants in variational and sampling-style frameworks (including sample-based Krylov / SKQD sketches) using Qiskit and PennyLane, against classical references on the same problems. A second thread is quantum machine learning — diffusion-style models for image generation under the Qiskit Advocate Mentoring Program (paper Feb. 2026). Outside code: Qiskit Advocate · IBM Qiskit v2 Associate (May 2026) · Qiskit Fall Fest @ Yonsei 2025 (co‑org · intro quantum-informatics talk) · 2nd, Qiskit Hackathon Taiwan (NTU–IBM Hub) ’25 · Challenger, 2025 Quantum Challenge (SKKU QIRC).

Classical numerical methods stay in the loop. At MPMC Lab I worked on computational PDEs and hybrid quantum–classical Poisson pipelines that compare integration schemes honestly. Elsewhere (Seoul Quantum Campus incubatee) I prototyped PennyLane + TensorFlow models on applied finance-style settings. Tools are mostly Python / SciPy-stack scientific code, plus Rust / TypeScript / Move where a project needs a real software boundary — e.g. post-quantum cryptography literacy and Sui dApps with BlockBlock · DanB, and miscellaneous research utilities (KAIST–MIT Winter Camp ’26, courseware, cert prep).

Longer narrative → jeongbin.pages.dev