Teaching

Teaching Experience

Nanyang Technological University (NTU), Singapore

CZ3005: Artificial Intelligence (Teaching Assistant)

Period: January 2019 - December 2019

Responsibilities:

• Conducted tutorials and lab sessions on AI topics such as search algorithms, knowledge representation, and machine learning
• Assisted in preparing course materials, including assignments and examination questions
• Held regular consultation hours to support students understanding of complex AI concepts
• Evaluated and graded student submissions, providing constructive feedback to enhance learning outcomes

Course Topics Covered:

• Search algorithms (BFS, DFS, A*, etc.)
• Knowledge representation and reasoning
• Machine learning fundamentals
• Natural language processing basics
• Computer vision applications

CZ1012: Introduction to Computing Systems (Teaching Assistant)

Period: January 2019 - December 2019

Responsibilities:

• Facilitated lab sessions covering fundamental computing concepts, including computer architecture and operating systems
• Supported students in understanding system-level programming and debugging techniques
• Collaborated with faculty to develop lab exercises that reinforce theoretical knowledge
• Assisted in grading assignments and exams, ensuring fair and consistent assessment

Course Topics Covered:

• Computer architecture fundamentals
• Operating systems concepts
• System-level programming
• Debugging techniques
• Hardware-software interaction

Mentorship

Beyond formal teaching, I have mentored numerous students and researchers:

Current and Former Students

• Xiangxi Shi (PhD, Oregon State University) - ACM MM 2021, ECCV 2022, ICLR 2024
• Jiahui Gao (PhD, University of Hong Kong) - AAAI 2022
• Peizhao Li (now Research Scientist at Google) - CVPR 2021
• Mengnan Du (now Assistant Professor at NJIT) - NAACL 2020
• Zihan Wang (PhD student at UCSD) - ACL 2022
• Zilong Wang (PhD student at UCSD) - EMNLP 2023
• Dat Huynh (PhD from Northeastern University, now Senior Research Scientist at Meta) - CVPR 2022
• Yifei Ming (PhD from UW-Madison, now Research Scientist at Salesforce) - NeurIPS 2020, EMNLP 2021
• Shengcao Cao (PhD student at UIUC) - ICLR 2024, CVPR 2025
• Yicong Gong (PhD from ANU, now Research Scientist at Adobe Research) - ICLR 2024
• Wenxiao Xiao (PhD student at Brandeis University) - ICML 2024
• Xuan Shen (PhD from Northeastern University) - AAAI 2024 ×2, CVPR 2025, 4 on submission
• Xiang Li (PhD from CMU, now Research Scientist at Google DeepMind) - ICLR 2025, CVPR 2025
• Zefan Cai (PhD from UW-Madison) - 3 NeurIPS 2025 submissions

Teaching Philosophy

My teaching approach emphasizes:

• Practical Application: Connecting theoretical concepts to real-world AI applications
• Hands-on Learning: Providing hands-on experience with cutting-edge tools and technologies
• Individual Support: Offering personalized guidance to help students achieve their learning goals
• Research Integration: Incorporating current research developments into course materials

Course Materials

While most course materials are hosted on NTUs internal learning management systems, Im happy to share relevant resources and discuss specific topics with interested students and researchers.