Research

Dr. Liu’s research integrates Artificial Intelligence (AI) to simulate and optimize chemical and biochemical processes, aiming to enhance operational efficiency and sustainability. His work encompasses AI-driven solutions for environmental monitoring, intelligent process control, and sustainable energy systems. Notable contributions include advanced machine learning models for air/wastewater quality prediction, intelligent fault detection systems, and deep learning applications in environmental engineering. Dr. Liu is passionate about advancing the frontier of AI applications in engineering, addressing critical challenges and promoting sustainable industrial development. His current research focuses on:

  • AI-Enhanced Process Control and Optimization
    Implementing intelligent systems to optimize chemical and biochemical processes, improving performance, safety, and sustainability.
  • Machine Learning for Industrial Data Analysis
    Leveraging machine learning algorithms to extract actionable insights from complex industrial datasets, supporting decision-making and predictive maintenance.
  • Physics-Informed Machine Learning (PIML)
    Integrating fundamental physical principles with machine learning to improve model accuracy, reliability, and predictive power in engineering applications.
  • Large Language Models (LLMs) in Engineering Applications
    Utilizing LLMs for automating knowledge extraction, enhancing documentation processes, and supporting sophisticated engineering decision-making and communication.

Openings

Postdocs:

We welcome postdocs with a solid publication record and rich experience in one or more of the following areas.
  • Artificial Intelligence
  • Large Language Models
  • Intelligent Process Control / Predictive Maintenance

Postdoctoral Funding Opportunities:

 PhD / Master students:

We welcome dynamic, team-oriented and highly motivated students from disciplines like Civil Engineering, Computer Science/Engineering, Environmental Engineering, Chemical engineering and related fields. Prospective students should be passionate about scientific research and committed to addressing key challenges. o apply, please forward your resume, academic records, and a brief introduction. Graduate students who have secured external funding are encouraged to apply.

External scholarship opportunities:

Visiting PhD students and Scholars:

We welcome highly motivated visiting PhD students and Scholars to our team.

Undergraduates:

We invite proactive undergraduate students to join our research group.

Scholarship opportunities:

**Applications are reviewed and interviewed on an ongoing basis. Due to the large number of inquiries, we are regretful that personal responses to each cannot be guaranteed. Only those shortlisted for interviews will be contacted; please refrain from sending follow-up emails or reminders.