CHANG, Tengfei - HKUST Class Schedule & Quota

Class Schedule & Quota
2026-27 Fall 2025-26 Summer 2025-26 Spring 2025-26 Winter
2026-27 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 MOES MSSM PDEV PLED ROAS SEEN SMMG SOCH SYSH UCMP UCUG UFUG UGOD

COURSE INFO

PREVIOUS CODE	IOTA 6910E
DESCRIPTION	Networked robots are increasingly used in exploration, logistics, inspection, and autonomous systems, where teams of robots must perceive their environment, share information, and make coordinated decisions. This course introduces the fundamental principles behind how such robots combine data from multiple sensors, and from one another, to build reliable perception and cooperative intelligence. Students will learn essential concepts in probabilistic sensor fusion, core filtering techniques, and modern machine-learning-based fusion approaches, and explore how these methods enable tasks such as distributed localization, collaborative mapping, and coordinated autonomy. The course provides practical skills for developing intelligent multi-robot systems and offers a strong foundation for research or advanced work in AI, robotics, and autonomous systems.

PREVIOUS CODE

IOTA 6910E

DESCRIPTION

Networked robots are increasingly used in exploration, logistics, inspection, and autonomous systems, where teams of robots must perceive their environment, share information, and make coordinated decisions. This course introduces the fundamental principles behind how such robots combine data from multiple sensors, and from one another, to build reliable perception and cooperative intelligence. Students will learn essential concepts in probabilistic sensor fusion, core filtering techniques, and modern machine-learning-based fusion approaches, and explore how these methods enable tasks such as distributed localization, collaborative mapping, and coordinated autonomy. The course provides practical skills for developing intelligent multi-robot systems and offers a strong foundation for research or advanced work in AI, robotics, and autonomous systems.

IOTA 5203 - Sensor Fusion and Cooperative Intelligence for Networked Robotics (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6387)	Mo 09:00AM - 11:50AM	Room 521H VR Room, W1	CHANG, Tengfei	30	0	30	0

[Matching between Lecture & Lab required]

COURSE INFO

PRE-REQUISITE	UFUG 1601 or UFUG 1603
DESCRIPTION	This course introduces common data structures and algorithms. Data structures include arrays and matrices, linked lists, stacks, priority queues, hash tables, trees, and graphs. Algorithms include sorting, hashing, searching, greedy methods, divide-and-conquer, dynamic programming, and branch-and-bound. Students will learn Python implementations of these data structures and algorithms, and solve programming problems with learned techniques.

PRE-REQUISITE

UFUG 1601 or UFUG 1603

DESCRIPTION

This course introduces common data structures and algorithms. Data structures include arrays and matrices, linked lists, stacks, priority queues, hash tables, trees, and graphs. Algorithms include sorting, hashing, searching, greedy methods, divide-and-conquer, dynamic programming, and branch-and-bound. Students will learn Python implementations of these data structures and algorithms, and solve programming problems with learned techniques.

UFUG 2602 - Data Structure and Algorithm Design (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L02 (6876)	TuTh 09:00AM - 10:20AM	Rm 102, E4	CHANG, Tengfei	90	89	1	0