Hualin Zhan

Dr. Hualin Zhan is a Research Fellow at the School of Engineering, Australian National University, leading the physics-machine learning nexus team within the ANU Perovskite Photovoltaics group. His research integrates physics and machine learning to advance solar energy and energy storage materials, focusing on quantitative analysis of photovoltaic devices at the ion/electron level to enable precision-driven breakthroughs.

Research interests include:

• Machine Learning for scientific discovery in energy materials
• Theoretical physics of ion/electron transport
• Perovskite solar cell optimization
• Nanoscale energy storage systems

His publications demonstrate strong focus on machine-learning applications for energy materials, with 60% of recent works involving perovskite optimization and 40% exploring fundamental ion transport mechanisms. Key trends include Bayesian optimization for material parameter extraction and nanocircuitry design for energy storage.

Awards and leadership:

• ACAP Fellowship (2023) and Best Oral Presentation at PVSEC-35 (2024)
• Lead CI for ACAP project on autonomous PV materials discovery (2025)
• Founder of nexSAS research group accelerating next-gen energy materials