Sebastian H

Research Intern — Quantum Machine Learning

Purdue University • Fulltime

May 2025 - Aug 2025 • 3 mos

Developed a hybrid classical-quantum computing system to solve differential equations applied to power grid modeling, as part of Purdue's Summer Undergraduate Research Fellowship (SURF). Key contributions: * Designed and implemented quantum circuits using single-qubit architectures, researching the boundary between classical and quantum computational advantages for differential equation solving * Built a hybrid pipeline combining classical numerical methods with quantum circuit execution, targeting real-world power systems applications * Presented weekly progress reports to research supervisors, maintaining rigorous documentation of experimental results and circuit designs * Independently investigated quantum computing literature to inform circuit design decisions and benchmark hybrid performance This experience gave me hands-on exposure to quantum ML frameworks, circuit design tools, and the research workflow of a top US engineering program.