Associate Professor of Chemical Engineering
Smart Systems Engineering and Design
Digital Twin of Chemical/Bio-process
SMARTLY AND INTELLIGENTLY MANAGING AND DESIGNING MANUFACTURING SUPPLY CHAIN NETWORKS
Process systems engineering (PSE) deals with the design, operation, control and optimization of various chemical, physical, and biological processes by resorting to systematic computer-aided approaches. For industrial applications, PSE techniques can be applied to design and analyze various manufacturing networks and supply chains for strategic operation and management.
SYSTEMATICALLY UNDERSTANDING AND DESIGNING GENES, PROTEINS, CELLS AND THEIR INTERACTIONS AT HOLISTIC LEVEL
Main research focus is placed on elucidating complex biological parts/systems and improving/designing their characteristics and properties towards biotechnological and healthcare applications. The central task of this bigdata- and hypothesis-driven research is to comprehensively collect, manage and analyze the global cellular information, e.g., high-throughput omics data, and to generate predictive computational models of the intricate biological processes, i.e., metabolic, signaling and regulatory networks. Thus, better understanding the cellular physiology, regulation and metabolism as well as multi-cellular interactions at the systems level and subsequently designing strategies for achieving desirable states are a prime target of this research. To this end, we can exploit various PSE techniques (statistical analysis, machine learning, mathematical modeling, process control and systems optimization). Current applications include, but not limited:
- Bioprocess Digital Twin for advanced biomanufacturing
- Gut, soil, food and skin microbiome and (synthetic-) microbial community interactions for health, environment, biotechnological and cosmetic applications
“Enzyme capacity-based genome scale modelling of CHO cells” Metab. Eng., 60: 138-147 (2020).
“Multi-omics profiling of CHO parental hosts reveals cell-line specific variations in bioprocessing traits” Biotechnol. Bioeng., 116(9): 2117-2129 (2019).
“Genome and evolution of the shade-requiring medicinal herb Panax ginseng” Plant Biotechnol. J., 16(11): 1904-1917 (2018).
“Mammalian systems biotechnology reveals global cellular adaptions in a recombinant antibody-producing CHO cell line” Cell Syst., 4(5): 530-542 (2017).
“A consensus genome-scale reconstruction of Chinese hamster ovary cell metabolism” Cell Syst., 3(5): 434-443 (2016).
“Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis” Plant Physiol., 169(4): 2982-2991 (2015).
“Codon Optimization On-Line (COOL): a web-based multi-objective optimization platform for synthetic gene design” Bioinformatics, 30(15): 2210-2212 (2014).
“Elucidating the rice cells metabolism under flooding and drought stresses using flux-based modelling and analysis” Plant Physiol., 162(4): 2140-2150 (2013).
“Combined in silico modeling and metabolomics analysis to characterize fed-batch CHO cell culture” Biotechnol. Bioeng., 109(6): 1415-1429 (2012).
Bioprocessing Technology Institute, A*STAR (2005-2021)
National University of Singapore (2005-2018)
선임연구원 (KAIST, 2004-2005)