I am a recent Computer Science graduate from Gadjah Mada University (UGM), where I completed my bachelor’s degree in 2026 with a cumulative GPA of 3.95/4.00 and a major GPA of 3.99/4.00. My research interests center on quantum computing and efficient classical simulation, with broader interests in theoretical quantum information, high-performance computing, resource-efficient systems, and optimization.

My recent quantum-computing work investigates ways to approximate and simulate quantum computations efficiently on classical hardware. As a research assistant at the National Research and Innovation Agency (BRIN), I worked on quantum-circuit modeling and efficient classical simulation. This work contributed to my first-authored paper on deep-learning-integrated pairwise-qubit subsystem simulation, presented at SCA/HPCAsia 2026 in Osaka, Japan.

Alongside quantum computing, I have worked on energy-aware HPC scheduling and power management, failure-prone wireless-sensor-network simulation, and logistics optimization software. At UGM, I collaborated on research spanning reinforcement learning for HPC systems, scheduling, simulation, and combinatorial optimization.

I am currently exploring PhD opportunities in quantum computing, quantum information, scientific computing, and high-performance computing. I am especially interested in research that combines strong computational methods with questions about how complex quantum or large-scale computing systems can be modeled and simulated efficiently.

Research interests

• Quantum computing and efficient classical simulation
• Theoretical quantum information
• High-performance and energy-efficient computing
• Stochastic and combinatorial optimization

For publications, see the publications page. A fuller overview of my work is available on the research page, and my current CV can be downloaded from the CV page.