Chemeca: Concurrent Session 4A - Manufacturing
Tracks
Track 1
| Wednesday, September 30, 2026 |
| 1:30 PM - 3:00 PM |
| Victory Room A |
Speaker
Dr. Md Tanjin Amin
Lecturer
Rmit University
Modelling Spatiotemporal Risk Evolution in Complex Systems: A Physics-Inspired Perspective
1:30 PM - 1:45 PM
Dr. Tanjin Amin is a Lecturer in Chemical and Environmental Engineering at RMIT
University. His research focuses on process systems engineering and system safety, developing
advanced methods for safety analysis, monitoring, and risk management in complex industrial
and emerging energy systems, including hydrogen, ammonia, battery technologies, and carbon
capture systems. Prior to joining RMIT, he served as a Postdoctoral Researcher and Visiting
Lecturer at Texas A&M University. Dr. Amin has co-authored more than 30 peer-reviewed
publications and has collaborated with industry and regulatory organisations such as ABS, API,
and CCPS to translate research into practical safety solutions.
Dario Manca
Phd Candidate
University Of Canterbury
TPMS-Based Catalyst Beds for Space Propulsion Produced via Multi-Material Additive Manufacturing
1:45 PM - 2:00 PM
Dario Manca is a PhD student from the Chemical and Process Engineering Department of the University of Canterbury in New Zealand. He graduated in 2019 as a materials engineer from the University of La Plata in Argentina. He worked as a process and quality engineer in the steel-making industry for ArcelorMittal France for almost four years. His interest in aerospace led him to pursue a PhD, studying catalysts for the decomposition of hydrogen peroxide.
ZIYUN ZHANG
Undergraduate Student
National University of Singapore
Learning Fluid–Particle Interactions: A Machine Learning Approach for Coarse-Grid CFD–DEM Simulation of Fluidized Beds
2:00 PM - 2:15 PM
Ziyun Zhang is an undergraduate student in Chemical Engineering at the National University of Singapore (NUS). His research focuses on multiphase flow modelling using coupled CFD-DEM approaches, with an emphasis on integrating machine learning techniques to enhance simulation efficiency and predictive capabilities. Currently, his work explores particle-fluid interactions in complex systems, aiming to improve understanding and optimisation of industrial processes. He/She is interested in the intersection of data-driven methods and traditional engineering models, and aspires to apply computational tools to solve real-world challenges in chemical engineering.
Mr Noman Yousuf
Postdoctoral Research Fellow
University Of Melbourne
Mechanistic Development of CFD-Derived Zonal Rate Models for Membrane Chromatography
2:15 PM - 2:30 PM
Dr. Yousuf is a Postdoctoral Research Fellow at the University of Melbourne within the Australian Research Council (ARC) Digital Bioprocess Development Hub. He holds a PhD in Chemical Engineering from RMIT University, where he contributed to an ARC Linkage Project on efficient wastewater sludge pipeline transport. His expertise includes Computational Fluid Dynamics (CFD), predictive modelling and model-based scale-up of complex transport and separation systems across wastewater and bioprocess engineering applications.
Prof Ian Wilson
Professor Of Soft Solids And Surfaces
University Of Cambridge
Can we predict diffusion-driven cleaning-in-place reliably?
2:30 PM - 2:45 PM
Ian Wilson is the Professor of Soft Solids and Surfaces in the Department of Chemical Engineering and Biotechnology at the University of Cambridge. He has been at Cambridge since 1994, conducting research on topics related to fluid flow, rheology and surface science related to the food, pharmaceutical and consumer goods sectors. He completed two terms as Editor-in-Chief (Food) of the IChemE journal Food & Bioproducts Processing in June 2026. He is attending Chemeca 2026 as part of a Hood Fellowship at the University of Auckland.
Dr Kenneth Ng
Technical Research Support Officer
University Of Melbourne
A hybrid machine learning model for bioprocess scale-up
2:45 PM - 3:00 PM
Dr. Kenneth Ng is a Technical Research Support Officer in the Department of Chemical Engineering at the University of Melbourne. His research focuses on improving bioprocess development and manufacturing through machine learning approaches. He is a part of the ARC Digital Bioprocessing Development Hub, a collaboration between industry and researchers for the digital transformation of the Australian biopharmaceutical manufacturing sector.