معرفی
Ho Fai Po is a Lecturer in Applied Mathematics at Aston University, affiliated with the School of Engineering and Technology within the College of Engineering and Physical Sciences. His research lies at the intersection of statistical physics, Bayesian inference, and machine learning, focusing on modeling complex biological and disordered systems.
Research Interests: His work centers on applying theoretical frameworks from statistical physics to understand emergent behaviors in complex systems. Key areas include cortical neuronal networks, spin glasses, energy landscapes, and optimization problems. He employs principled machine learning and combinatorial optimization to infer structure and function from data, with applications in computational neuroscience and systems biology.
Publication Trends: His recent publications span journals like PNAS Nexus, Scientific Reports, and Physical Review E, reflecting a strong focus on statistical mechanics applied to both biological and engineered systems. The articles demonstrate a consistent theme of using physics-inspired methods to solve inference and optimization challenges in networked systems.
Collaborations and Research Output: He actively collaborates with researchers such as D. Saad and C. H. Yeung. His work includes six research articles and two publicly available datasets related to neuronal network analysis. These contributions highlight his role in advancing data-driven modeling of complex systems.
Academic Background:
- Bachelor’s in Mathematics and Economics
- Master’s in Mathematics
- PhD in Statistical Physics
Professional Experience:
- Research Associate in Mathematics, Aston University
- Lectureship in Data Analytics, University of the West of England (UWE)
- Lecturer in Applied Mathematics, Aston University (July 2025–present)