YU, Jiadong - 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.
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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

VECTOR	[3-0-0:3]
DESCRIPTION	This course focuses on applying reinforcement learning (RL) to cyber-physical systems (CPS), which integrate computation, networking, and physical processes. It covers the fundamentals of RL and its application in designing intelligent decision-making algorithms for CPS. Topics include model-based and model-free RL approaches, safe RL practices to ensure the safety of CPS, and the integration of RL with other techniques, such as model predictive control in CPS. The course will also explore different applications of RL in CPS.

VECTOR

[3-0-0:3]

DESCRIPTION

This course focuses on applying reinforcement learning (RL) to cyber-physical systems (CPS), which integrate computation, networking, and physical processes. It covers the fundamentals of RL and its application in designing intelligent decision-making algorithms for CPS. Topics include model-based and model-free RL approaches, safe RL practices to ensure the safety of CPS, and the integration of RL with other techniques, such as model predictive control in CPS. The course will also explore different applications of RL in CPS.

IOTA 5201 - Reinforcement Learning for Intelligent Decision Making in Cyber-Physical Systems (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6169)	Tu 01:30PM - 04:20PM	Rm 149, E1	YU, Jiadong	40	39	1	0

[Matching between Lecture & Tutorial required]

COURSE INFO

PRE-REQUISITE	UFUG 1102 OR UFUG 1105
DESCRIPTION	This course covers the basic concepts of Statistics and Probability Theory, gives a systematic introduction to Statistical Inference, Test Statistic, Regression, and Bayesian Statistics, and deepens the understanding of these theories and techniques through practical applications.

UFUG 2104 - Applied Statistics (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L03 (6605)	MoWe 09:00AM - 10:20AM	Rm 222, W1	YU, Jiadong	35	32	3	0
T03 (6609)	Fr 12:00PM - 12:50PM	Rm 222, W1	YU, Jiadong	35	32	3	0