CV

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Education

• Ph.D. candidate in Chemical Engineering, National Taiwan University, Sep 2023 - Present
• M.S. in Chemical Engineering, National Taiwan University, Sep 2021 - Aug 2023
• B.S. in Chemical and Materials Engineering, Chang Gung University, Sep 2017 - Jun 2021

Work experience

• Feb 2024 - Present: Project Research Assistant
  • National Center for High-Performance Computing (NCHC), HPC & Cloud Technologies Division
  • Developed high-performance computing workflows for large-scale scientific simulation, including CUDA GPU acceleration
  • Extended and applied physics-informed machine learning methods to scientific computing problems
  • Supported reproducible model development and deployment for computational research projects
• Sep 2021 - Present: Graduate Research Assistant
  • Complex Fluid Theory Lab
  • Developed multivariate time-series and spatiotemporal deep learning models to predict phase-field morphology evolution
  • Built a GPU-enabled 3D solver for ternary non-solvent-induced phase separation (NIPS)
  • Integrated phase-field simulation with physics-informed neural networks (PINNs) for forward and inverse modeling
  • Research focus: polymer field-theoretic simulation and self-consistent field theory (SCFT)
• Sep 2020 - Jun 2021: Research Assistant
  • Process Engineering Lab
  • Designed air separation unit (ASU) processes for ultra-high-purity nitrogen and oxygen production
  • Developed hybrid membrane/ASU process models to evaluate industrial and experimental high-permeability membranes
  • Applied simulated annealing (SA) for reaction-kinetic parameter regression
  • Contributed to simulation and techno-economic analysis for hybrid membrane/cryogenic air-separation systems

Skills

• Programming Languages
  • Python, Julia (scientific computing, deep learning workflows)
  • C/C++ (numerical methods, HPC-oriented implementation)
  • CUDA (GPU acceleration for large-scale simulation)
  • MATLAB (modeling, optimization, algorithm prototyping)
• Academic and Research Skills
  • Phase-field modeling and simulation
  • Polymer field-theoretic simulation and self-consistent field theory (SCFT)
  • Physics-informed neural networks (PINNs) for forward and inverse problems
  • Multivariate time-series and spatiotemporal deep learning
  • Process simulation and design for gas separation (ASU, hybrid membrane/cryogenic systems)
  • Techno-economic analysis and model-based process evaluation

Publications

L-MAU: A multivariate time-series network for predicting the Cahn-Hilliard microstructure evolutions via low-dimensional approaches

Chen SJ, Yu HY. L-MAU: A multivariate time-series network for predicting the Cahn-Hilliard microstructure evolutions via low-dimensional approaches. Computer Physics Communications. 2024 Dec 1;305:109342.

Connecting Structural Characteristics and Material Properties in Phase-Separating Polymer Solutions: Phase-Field Modeling and Physics-Informed Neural Networks

Lin LC, Chen SJ, Yu HY. Connecting structural characteristics and material properties in phase-separating polymer solutions: phase-field modeling and physics-informed neural networks. Polymers. 2023 Dec 14;15(24):4711.

Rigorous simulation and techno-economic evaluation on the hybrid membrane/cryogenic distillation processes for air separation

Chen SJ, Yu BY. Rigorous simulation and techno-economic evaluation on the hybrid membrane/cryogenic distillation processes for air separation. Journal of the Taiwan Institute of Chemical Engineers. 2021 Oct 1;127:56-68.

Talks

Exploring Novel Block Copolymer Microstructures via Reciprocal-Space Niching Genetic Algorithms and Self-Consistent Field Theory

March 16, 2026

International conference paper at APS Global Physics Summit 2026 (APS March Meeting), Session MAR-L67, Denver, CO, USA (and online)

Abstract PDF

Self-Consistent Field Theory for Nanostructure Discovery

July 02, 2025

Domestic conference paper at 2025 Annual Conference of the Taiwanese Colloid and Interface Society (2025 TWCIS) & International Symposium on Interface Science, Taiwan

Abstract PDF

Numerical Simulation for Nonsolvent-Induced Phase Separation by Ternary Phase-Field Theory

May 03, 2024

Domestic conference paper at 2024 Symposium on Thermodynamics and Process Systems Engineering, Taiwan

Abstract PDF

Innovative Machine Learning Approaches for Predicting the Dynamics of the Phase-Field Microstructures

May 19, 2023

Domestic conference paper at 2023 Symposium on Thermodynamics and Process Systems Engineering, Taiwan

Abstract PDF

Innovative Machine Learning Approaches for Predicting the Dynamics of the Phase-Field Microstructures

December 02, 2022

Domestic conference paper at 2022 Chemical Engineering Conference by Taiwan Institute of Chemical Engineers (TwIChE), Taiwan

Abstract PDF

Hybrid Membrane Process for Cryogenic Air Separation Unit

May 14, 2021

Domestic conference paper at 2021 Symposium on Thermodynamics and Process Systems Engineering, Taiwan

Abstract PDF

Honor & Award

• Honorable Mention in Student English Oral Presentation Contest, 2025 TWCIS
• Honorable Mention in Student English Oral Presentation Contest, 2022 TwIChE
• Excellent Presentation Award in the Symposium of Thermodynamics and Process System Engineering, 2021 NTU
• Second Place Award in Undergraduate Student Process Design Contest, 2021 TwIChE
• Undergraduate Academic Excellence Award, Chang Gung University, 2021 CGU

Internship Experience

• Jun 2020 - Sep 2020: Intern
  • Fuburg Company, Taiwan
  • Experiment and improvement on superabsorbent polymer product
  • Competitor analysis and data collection of company product

Service and leadership

• Sep 2018 - Sep 2019: Vice Director
  • Piano club in Chang Gung University