research
Research themes in quantum computing, high-performance computing, simulation, and optimization.
My work spans several areas of computational research, with a common emphasis on efficient modeling, simulation, and optimization of complex computing systems.
Quantum computing and efficient classical simulation
My main current research direction is the classical simulation of quantum computations. At BRIN, I worked with Dr. Ahmad Ridwan Tresna Nugraha on quantum-circuit modeling and methods for reducing the classical cost of simulating quantum systems.
This line of work includes my first-authored SCA/HPCAsia 2026 paper, “Deep Learning-Integrated Pairwise-Qubit Subsystems for Highly Efficient Quantum Circuit Simulation,” which explores a pairwise-qubit subsystem approach integrated with deep learning. I have also worked on efficient computation of single-qubit marginal measurement probabilities for simulating certain classes of quantum algorithms.
See my quantum-computing publications →
High-performance and energy-efficient computing
At UGM, I contributed to research on power-aware HPC scheduling and power management, including reinforcement-learning-enabled simulation and curriculum-learning approaches for power-management systems.
The broader goal of this work is to improve the efficiency of HPC systems by coordinating scheduling decisions, idle-node management, and power states while retaining useful system-level performance characteristics.
Simulation software and optimization
I have also contributed to research software for domains where system behavior must be studied under constraints or uncertainty. This includes FaultNet-Sim, a C++ simulator for failure-prone wireless sensor networks, and MedRoPax, software for a heterogeneous vehicle-routing problem with three-dimensional loading and packing constraints in medical-supply distribution.
These projects connect my interests in simulation with stochastic and combinatorial optimization.
Research direction
For doctoral study, I am particularly interested in problems at the intersection of quantum computation, classical simulation, scientific computing, and high-performance systems. I am interested both in algorithmic questions and in the practical computational methods needed to study systems that are expensive to simulate directly.