Teaching

Program: Food Technology
Institution: Singapore Institute of Technology
Role: Course Developer and Sole Instructor
Period: 2026

This course introduces students to the complete data analytics workflow, from problem formulation and data preparation to analysis, visualization, interpretation, and communication of insights.

Topics include data quality, descriptive and comparative analysis, data visualization, relationships and patterns, Python fundamentals, and responsible use of AI. Students work with Excel and Jupyter/Python and apply analytics to food-technology datasets and real-world problems.

Teaching approach: Applied data analysis · Project-based learning · Excel · Python · Responsible AI

Programs: Pharmaceutical Engineering and Chemical Engineering
Institution: Singapore Institute of Technology
Role: Co-Instructor
Period: 2026

Contributes to undergraduate teaching in process safety, including lectures and assessments on process hazards, toxic release modeling, risk assessment, and safety management systems.

The course emphasizes quantitative analysis and engineering judgment for identifying, evaluating, and managing risks in chemical and process industries.

Teaching areas: Process Hazards · Risk Assessment · Consequence Analysis · Safety Management

Type: Interdisciplinary industry-based AI project course
Institution: Singapore Institute of Technology
Role: Co-Instructor
Period: 2026–Present

Students work in interdisciplinary teams with industry partners to develop practical AI-enabled solutions to real-world problems.

Teaching and supervision cover problem definition, data analytics, machine learning, natural language processing, Generative AI, feasibility assessment, responsible AI, technical reporting, and industry presentation.

Teaching approach: Industry-Based Learning · Machine Learning · NLP · Generative AI · Responsible AI · Team Projects

Project-based learning is an important part of teaching and student development in A-SMART Lab. Students apply analytical and computational methods to authentic engineering, food-technology, sustainability, and industry problems.

Student projects include:

• Final Year Projects
• Bachelor Thesis projects
• Industry Team Projects
• Independent research projects
• Interdisciplinary AI and data analytics projects

Projects emphasize problem formulation, data analysis, computational modeling, critical interpretation, responsible use of AI, and communication of actionable insights.

Program: Petroleum Engineering
Institution: University of Alberta, Canada
Role: Teaching Assistant
Years: 2014, 2015, and 2017
Enrollment: Approximately 70 students per year

Supported undergraduate teaching in applied reservoir engineering, including course instruction, student learning activities, and technical problem solving in petroleum reservoir engineering.

Program: Petroleum Engineering
Institution: University of Alberta, Canada
Role: Teaching Assistant
Year: 2014
Enrollment: Approximately 60 students

Supported undergraduate instruction in petroleum reservoir fluids and the application of fluid-property concepts to reservoir engineering problems.