Process Systems Engineering and Sustainable Production Lab
Research Field
Dr. Tsai-Wei Wu is an Assistant Professor in the Department of Chemical Engineering at National Cheng Kung University (NCKU), Taiwan. Before joining NCKU, she was a Project Assistant Professor at Tohoku University, Japan (April 2024 – July 2025). Her academic journey is rooted in the rigorous application of systems engineering to solve complex sustainability challenges in chemical manufacturing.
Her research advances Process Systems Engineering (PSE) for sustainability, with two tightly connected thrusts: (1) Carbon Capture, Utilization, and Storage (CCUS) technology design, and (2) Life Cycle Assessment (LCA) for industrial decarbonization. Over the recent years, she has investigated the development of techno-economically feasible and environmentally robust chemical processes for the net-zero transition.
Dr. Wu’s research group is dedicated to Sustainable Process Systems Engineering. Her research group develops models of green chemical processes, optimizes the network of CO2-reduction technologies, and evaluates sustainability across different aspects using LCA methodology.
Research Thrust 1 : Taiwan's Net-Zero Pathway: CCTUS Network Optimization and Electrification Potential Assessment
- Objective: To establish an optimization model for a national-level Carbon Capture, Utilization, and Storage (CCTUS) system and to evaluate the true decarbonization potential and potential environmental impacts of chemical industry electrification.
Research Thrust 2 : Process Scale-up and Circular Economy Assessment of Novel Carbon Capture Adsorbents
- Objective: To develop process simulation models from lab-to-industrial scale for promising novel adsorbents, and to complete rigorous Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA) to facilitate industrial adoption.
2023 The Postdoctoral Research Abroad Program, sponsored by the Ministry of Science and Technology (MOST), Taiwan
- Ph.D. in Chemical Engineering (2018-2022) National Taiwan University (Process Systems Engineering Lab)
- M.S. in Chemical Engineering (2012-2014) National Tsing Hua University (Separation and Chemical Reaction Engineering Lab)
- B.S. in Chemical Engineering (2008-2012) National Tsing Hua University
Job Description
Key Responsibilities:
LLM Pipeline Development: Design and implement a RAG (Retrieval-Augmented Generation) or fine-tuning pipeline (using PyTorch/JAX) to analyze chemical process literature.
Automated LCI Extraction: Instruct the model to identify and extract input/output flows, energy consumption, and reaction conditions from unstructured text/PDFs and format them into structured LCI tables (JSON/CSV).
Domain-Specific Fine-Tuning: Utilize your domain knowledge (Mass/Energy Balance, Unit Operations) to curate datasets and fine-tune open-source models (e.g., Llama 3, Mistral, or Gemma) for higher accuracy in chemical contexts.
UI/UX Prototyping: Build a user-friendly web interface where researchers can upload papers and verify the generated LCI tables.
Preferred Intern Educational Level
Undergraduate student
Skill sets or Qualities
Technical Skills (AI & Programming):
- LLM Frameworks: Strong proficiency in PyTorch, JAX/Flax, and Hugging Face Transformers. Experience with model fine-tuning is essential.
- NLP & Data Processing: Experience with tokenization, JSONL formatting, and handling unstructured data.
- Python Ecosystem: Expert-level Python (Pandas, NumPy) for data manipulation.
Domain Knowledge (Chemical Engineering):
- Understanding of Unit Operations and Chemical Reaction Engineering (to correctly identify system boundaries in literature).
- Familiarity with Material and Energy Balance concepts (crucial for validating LCI data integrity).