معرفی
Professor Tao Chen is an academic and administrative leader at the University of Surrey, serving as Associate Vice-President (International) and Professor in the School of Chemistry and Chemical Engineering. He plays a pivotal role in advancing the university's global engagement strategy, focusing on transnational education (TNE) through collaborative projects with internal stakeholders and external partners. His responsibilities include guiding international partnerships, brand development, student recruitment, research collaboration, and mobility initiatives.
He holds a PhD and is a Fellow of the Institution of Engineering and Technology (FIET). His research interests revolve around Digital Chemical Engineering, emphasizing computer modeling of chemical processes using multiscale mechanisms and machine learning. Key application areas include skin penetration, food engineering, radiotherapy dosimetry, and manufacturing processes. He also focuses on model-based chemical product design and process optimization, leveraging interdisciplinary approaches in biomedical engineering, environmental sustainability, and industrial systems.
Professor Chen's recent publications highlight interdisciplinary work, including machine learning applications in spectroscopy, advanced process control methodologies, fire safety modeling, drug delivery systems, and sustainable aquaculture optimization. His research often bridges theoretical and applied domains, addressing real-world challenges through innovative engineering solutions.
In terms of academic contributions, he supervises doctoral student Anukrati Goel (EPSRC-funded) and research fellow Dr. Yuqing Xia (BEIS-funded). He leads significant grants, such as the EPSRC-funded project 'Soilless cultivation for rapid bioenergy willow' (EP/X013294/1, £453,816, 2023–2025). His teaching includes Year 2 modules in Computation for Chemical Engineers and Transfer Processes, plus an MSc module in Advanced Process Control. He annually oversees 4–6 MSc dissertation projects and 1–2 MEng research projects, integrating experimental work with modeling.
