Dr S.Y. Teng (Sin Yong)

Postdoc - Analytical Chemistry & Chemometrics

Dr S.Y. Teng (Sin Yong)
Visiting address

Heyendaalseweg 135
6525 AJ NIJMEGEN
Internal postal code: 61

Postal address

Postbus 9010
6500 GL NIJMEGEN

Working days Monday, Tuesday, Wednesday, Thursday, Friday

Marie Curie Postdoctoral Fellow

By education, Dr. Sin Yong Teng is a chemical engineer. He studied in the University of Nottingham with exchange to University of Birmingham as a multi-year Dean's List's recipient (by grade), ultimately receiving a First-Class Honours Degree in Chemical Engineering. Later, he carried out his PhD research in the renowned NETME Center and Brno University of Technology which was focused on using data-driven approaches for energy and processes. His PhD defense was award with the highest distinction (Summa Cum Laude). As a postdoc, Sin Yong joined the chemometrics group to extend his expertise in data-driven modelling from the chemical perspective. In 2022, he was awarded the Marie Curie Postdoctoral Fellowship from the European Union. He now works on the bridge of chemistry, chemometrics and chemical engineering, focusing on the energy transition and sustainable processes. Here are some keywords related to Sin Yong's expertise:
- Circularity (Process and value chains)
- Energy Systems
- Chemical Kinetics Modelling
- Process Synthesis
- Data Analysis for Processes
- Process Improvement (Integration, Optimization and Intensification)
- Mathematical Programming
- Meta-heuristics
- Advanced Neural Networks
- Graph Theory (P-graph)
- Multi-Criteria Decision Making Algorithms
- Interpretable Models

Sin Yong has received multiple top 1% awards from Web of Science and serves as a reviewer for many international journals such as Analytica Chimica Acta, Journal of Cleaner Production, Renewable Energy, Process Integration and Optimization, Artificial Intelligence Reviews, Chemometrics and Intelligent Laboratory Systems etc. He also serves as an editor in Sustainability, and Frontiers in Sustainability journals.

Master’s students who would like to work on this exciting research area can contact me (sinyong.teng@ru.nl). The most recent topic will be focused on using sample-efficient black box optimization algorithms on chemical processes.

Research theme

Research grants and prizes

Projects