COMP7250(PG): Machine Learning, Spring 2026
COMP3065(UG): AI Application Development, Spring 2026
SCIE3005(UG): AI for Science, Summer 2025
COMP7250(PG): Machine Learning, Spring 2025
COMP7160(PG): Research Methods in Computer Science, Autumn 2024
COMP3057(UG): Intro to AI and Machine Learning, Autumn 2024
COMP7250(PG): Machine Learning, Spring 2024
COMP7160(PG): Research Methods in Computer Science, Autumn 2023
COMP3057(UG): Intro to AI and Machine Learning, Autumn 2023
COMP7250(PG): Machine Learning, Spring 2023
COMP7180(PG): Quantitative Methods for DAAI, Autumn 2022
COMP7160(PG): Research Methods in Computer Science, Autumn 2022
COMP3057(UG): Intro to AI and Machine Learning, Autumn 2022
COMP7250(PG): Machine Learning, Spring 2022
COMP7160(PG): Research Methods in Computer Science, Autumn 2021
COMP3057(UG): Intro to AI and Machine Learning, Autumn 2021
COMP7250(PG): Machine Learning, Spring 2021
COMP4015(UG): AI and Machine Learning, Autumn 2020
COMP7250(PG): Machine Learning, Spring 2020
AAAI 2026: Trustworthy Machine Reasoning with Foundation Models [Website] [Slides]
AAAI 2026: When AI "Forgets" for Good: The Science and Practice of Machine Unlearning for AI Safety [Slides]
AAAI 2026: Handling Out-of-Distribution Data in the Open World: Principles and Practice for Reliable AI [Slides]
WWW 2025: Trustworthy AI under Imperfect Web Data [Slides]
VALSE 2025: Trustworthy Machine Learning under Imperfect Data [Slides]
AAAI 2024: Trustworthy Machine Learning under Imperfect Data [Website] [Slides]
IJCAI 2024: Trustworthy Machine Learning under Imperfect Data [Slides]
ECML 2024: Trustworthy Machine Learning under Imperfect Data
ACML 2023: Trustworthy Learning under Imperfect Data
CIKM 2022: Learning and Mining with Noisy Labels
IJCAI 2021: Learning with Noisy Supervision
ACML 2021: Learning under Noisy Supervision
ACML 2019: Towards Noisy Supervision: Problems, Theories, and Algorithms