XIE, Sihong - HKUST Class Schedule & Quota

Class Schedule & Quota
2025-26 Fall 2024-25 Summer 2024-25 Spring 2021-22 Winter
2025-26 Fall
Common Core Course
The class information on this page will normally be updated every 15 to 20 minutes during class enrollment period.
» Student Information System (SIS)» PG Program/Course Catalog
Notes & Links
This service was first adapted from a student contribution in 2011-12 Fall. The efforts of all concerned are duly acknowledged.

AIAA AMAT BSBE CMAA CNCC CNGF DLED DSAA EOAS FTEC FUNH INFH INTR IOTA IPEN LANG MICS MSSM PDEV PLED ROAS SEEN SMMG SOCH SYSH UCMP UCUG UFUG UGOD

COURSE INFO

DESCRIPTION	This course provides guidance to undergraduate students of the AI major for their academic path and future. This course is mostly introductory and aims to inspire UG students for their academic path development and growth of maturity during their UG study. Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Graded P or F.

DESCRIPTION

This course provides guidance to undergraduate students of the AI major for their academic path and future. This course is mostly introductory and aims to inspire UG students for their academic path development and growth of maturity during their UG study. Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Graded P or F.

AIAA 1010 - Academic Orientation for AI Students (1 unit)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6363)	01-SEP-2025 - 05-SEP-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	DAI, Enyan	155	150	5	0	The class will be delivered by the following instructors as below. W1-Enyan Dai W2-Bingzhuo Zhong W3-Xin Wang W4-Sihong Xie W5-Menglin Yang W6-Yingcong Chen W7-Junwei Liang W8-Changhao Chen W9-Zeke Xie W10-Yutao Yue W11-Li LIU W12-Xuming Hu W13-Apostolos Rikos
	08-SEP-2025 - 12-SEP-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	ZHONG, Bingzhuo
	15-SEP-2025 - 19-SEP-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	WANG, Xin
	22-SEP-2025 - 26-SEP-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	XIE, Sihong
	29-SEP-2025 - 11-OCT-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	YANG, Menglin
	13-OCT-2025 - 17-OCT-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	CHEN, Yingcong
	20-OCT-2025 - 24-OCT-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	LIANG, Junwei
	27-OCT-2025 - 31-OCT-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	CHEN, Changhao
	03-NOV-2025 - 07-NOV-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	XIE, Zeke
	10-NOV-2025 - 14-NOV-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	YUE, Yutao
	17-NOV-2025 - 21-NOV-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	LIU, Li
	24-NOV-2025 - 28-NOV-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	HU, Xuming
	01-DEC-2025 - 05-DEC-2025 Tu 09:00AM - 09:50AM	Lecture Hall B	RIKOS, APOSTOLOS

COURSE INFO

VECTOR	[3-0-0:3]
DESCRIPTION	Artificial Intelligence technologies have been maturing and are deployed in real-world applications, such as healthcare, entertainment, business, scientific research, military, etc. In all these domains, the decisions made by AI algorithms can critically impact individuals, organizations and society. The designers, auditors, and users of AI technologies thus need to be equipped with the capabilities to understand, analyze, and eventually discipline these algorithms in the broader contexts. This course will introduce students to the latest research of responsible AI and explore these capabilities in both theoretical and practical ways. Topics include but are not limited to theories and algorithms of secure machine learning, fair machine learning, interpretable AI, and case studies involving natural language processing, computer vision, and reinforcement learning.

VECTOR

[3-0-0:3]

DESCRIPTION

Artificial Intelligence technologies have been maturing and are deployed in real-world applications, such as healthcare, entertainment, business, scientific research, military, etc. In all these domains, the decisions made by AI algorithms can critically impact individuals, organizations and society. The designers, auditors, and users of AI technologies thus need to be equipped with the capabilities to understand, analyze, and eventually discipline these algorithms in the broader contexts. This course will introduce students to the latest research of responsible AI and explore these capabilities in both theoretical and practical ways. Topics include but are not limited to theories and algorithms of secure machine learning, fair machine learning, interpretable AI, and case studies involving natural language processing, computer vision, and reinforcement learning.

AIAA 5047 - Responsible Artificial Intelligence (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6004)	Fr 09:00AM - 11:50AM	Rm 201, W2	XIE, Sihong	50	30	20	0