Principal Investigator:

Dr. Tianlong (Taylor) Liu

Dr. Tianlong (Taylor) Liu is an Assistant Professor in the Department of Chemical and Biochemical Engineering at Western University and the Principal Investigator of the SustainAI Group.  He received his Ph.D. in Civil Engineering from the University of British Columbia (UBC), Canada, in 2020. Dr. Liu collaborates closely with various industries and has contributed to diverse interdisciplinary research programs spanning academia and industry, linking chemical engineering, environmental engineering, and biochemical engineering with industrial partners. His research lies at the intersection of AI and sustainable process engineering, with a focus on developing AI-enhanced process simulation, physics-informed machine learning (PIML) models, and data-driven optimization and control strategies for industrial and environmental systems. For more information, see page Dr. Tianlong (Taylor) Liu.

 


 

Current Group Members

Souvik  TA

Souvik TA

PhD Candidate

Research Interests / Specializations: My research is dedicated to leveraging the capabilities of Artificial Intelligence to develop superior, industry-oriented models. These models not only excel in their predictive capabilities, but they also prioritize explainability and ensure alignment with the fundamental laws of nature for greater reliability and coherence.
Miguel  Pardo Gomez

Miguel Pardo Gomez

PhD Student

Research Interests / Specializations: Physics-Based Modeling, Microbial Fuel Cells, Machine Learning, Hybrid Modeling, Time Series
Biography: I earned my bachelor’s degree in Chemical Engineering in 2022 and completed a graduate specialization in Statistics in 2024. I’m interested in working with data, building models, and understanding the behavior of dynamic systems. I enjoy working with time series, exploring how they change over time and how we can model and predict those changes. My work involves combining mathematical models with machine learning, always with an interest in making results interpretable and useful. I like clear ideas, well-structured code, and models that make sense.
Tailai  Chen

Tailai Chen

PhD Student

Research Interests / Specializations: Machine Learning in Biomaterials, Nanocomposites, Smart Hydrogels, Biomedical Devices
Biography: I received my B.Sc. in Biochemistry from Queen’s University in 2023 and am currently a PhD student in Chemical and Biochemical Engineering at Western University. Co-supervised by Professors Tianlong Liu and Jin Zhang, my research focuses on integrating machine learning with nanocomposite design, aiming to optimize the multifunctional properties of medical hydrogels. I am especially interested in predictive modeling and multi-objective optimization to accelerate materials development for healthcare applications.
Xiangyuan Huang

Xiangyuan Huang

PhD Student

Research Interests / Specializations: Physics-informed Machine Learning, Predictive maintenance, Wastewater Treatment, Decanter Centrifuge
Biography: Hello, my name is Xiangyuan Huang. I’m currently pursuing a master’s degree in Chemical and Biochemical Engineering at UWO. My research focuses on applying physics-informed machine learning and process modeling to optimize instrument performance in wastewater treatment. I have a strong interest in sustainable water management, data-driven decision-making, and bridging engineering with AI. I'm excited to collaborate and learn from others in this field.
Ruining Cheng

Ruining Cheng

Master

Research Interests / Specializations: Machine Learning, Time-Series Forecasting, AI-Enhanced Process Simulation, Data-Driven Optimization
Biography: I received my bachelor's degree in Pharmaceutical Engineering from East China University of Science and Technology in 2025 and now currently a master student in CBE at UWO. My research focuses on integrating machine learning with real-world industrial and environmental systems, with an emphasis on ensuring physical consistency, interpretability, and engineering relevance. I am particularly interested in developing hybrid modeling frameworks that combine data-driven architecture with first-principles knowledge from transport phenomena, thermodynamics, and reaction engineering.
Aakash Vajaria

Aakash Vajaria

Undergraduate Research Student


Tina Xu

Tina Xu

Undergraduate Research Student

Research Interests / Specializations: I am interested in how artificial intelligence can support the development of data-driven models for sustainable environmental and industrial systems. Specifically, I hope to explore AI-Enhanced Process Control and Optimization, as well as Machine Learning for Industrial Data Analysis. By integrating AI with core engineering principles, I aim to develop scalable, intelligent solutions for real-world industrial and environmental challenges.
Biography: I am a second-year undergraduate student at Western University studying Computer Science, with a foundational background in first-year Engineering. Through academic work and early experience in data science, I have developed a strong interest in AI-driven technologies and their potential to solve real-world problems. I am actively building my technical and analytical skills, with a focus on machine learning and optimization methods. Looking ahead, I hope to contribute to the advancement of intelligent, sustainable technologies that create measurable impact.