resume

MMath

University of Indonesia

Mathematics

• Matrix Theory and Linear Algebra
• Data Science Statistics
• Advanced Computing and Big Data
• Data Science Computing
• Advanced Data Exploration and Visualization
• Advanced Machine Learning
• Applied Deep Learning

MS (Withdraw)

Japan Advanced Institute of Science and Technology

Information Science

• Analysis for Information Science
• Discrete Signal Processing
• Information Theory

BS

Bandung Institute of Technology

Engineering Physics

• Engineering Mathematics
• Probability and Statistics
• Engineering Computation
• System Dynamics and Simulation
• Signal Processing
• Computational Material Science
• Molecular Dynamics Simulation

SAKURA Exchange Program in Science Scholarship

Japan Science and Technology Agency (JST)

The Sakura Science Exchange Program by JST invites young talents worldwide to Japan for short-term visits, fostering international collaboration in science, technology, and culture.

Kolmogorov-Arnold Informed Neural Networks: Advancing AI in Epidemiological Modeling

International Symposium on Biomathematics

Developed Kolmogorov-Arnold-Informed Neural Networks (KINNs) for epidemiological modeling, utilizing the interpretability and efficiency of Kolmogorov-Arnold Networks (KANs). Demonstrated higher prediction accuracy, faster convergence, and improved parameter estimation compared to Physics-Informed Neural Networks (PINNs), effectively addressing multi-scale outbreaks, nonlinear infection dynamics, and diverse population distributions. This research enhances the precision and efficiency of infectious disease modeling.

Octahedral morphology of NiO with (111) facet synthesized from the transformation of NiOHCl for the NOx detection and degradation: experiment and DFT calculation

Inorganic Chemistry Frontiers

Developed a novel synthesis method for NiO with dominant (111) facets, achieving superior nitrogen oxide (NOx) gas sensing and photocatalytic performance. Demonstrated a 16.5% response to 300 ppb NOx and over 50% deNOx photocatalytic efficiency under UV light. Computational analysis revealed that abundant Ni atoms on the (111) facet enhance NO adsorption and promote molecular decomposition, aligning with experimental findings.