GONG, Zijun - 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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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

PRE-REQUISITE	DSAA 2011
DESCRIPTION	Learning and optimization serve as the foundational block for many artificial intelligence algorithms. Our initial focus is on convex analysis and on modeling problems as convex problems, while later on in the course we will shift the focus to different algorithms for convex optimization and nonconvex optimization. The techniques introduced in this course will be motivated by needs of problems and applications in Machine Learning and Deep Learning. The topics range from foundational material to cutting-edge trends.

PRE-REQUISITE

DSAA 2011

DESCRIPTION

Learning and optimization serve as the foundational block for many artificial intelligence algorithms. Our initial focus is on convex analysis and on modeling problems as convex problems, while later on in the course we will shift the focus to different algorithms for convex optimization and nonconvex optimization. The techniques introduced in this course will be motivated by needs of problems and applications in Machine Learning and Deep Learning. The topics range from foundational material to cutting-edge trends.

AIAA 3225 - Learning and Optimization for Artificial Intelligence (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6559)	Mo 01:30PM - 02:50PM	Rm 102, E1	GONG, Zijun WANG, Xin	40 Quota/Enrol/Avail UG Year 3&4 AI students: 40/0/40	0	40	0
L01 (6559)	Fr 09:00AM - 10:20AM	Rm 102, E1	GONG, Zijun WANG, Xin	40 Quota/Enrol/Avail UG Year 3&4 AI students: 40/0/40	0	40	0

COURSE INFO

DESCRIPTION	This course introduces students to the fundamentals of discrete-time signal processing, for both linear time invariant (LTI) and non-LTI systems. For LTI systems, the topics include the sampling theorem, Fourier transform, convolution, and spectrum analysis, which lays the foundation for OFDM in wireless communications. Advanced topics will also be covered for time-variant systems, such as Heisenberg transform, Wigner distribution and Fractional Fourier transform, and their applications in radar, sonar and the OTFS modulation in wireless communications.

DESCRIPTION

This course introduces students to the fundamentals of discrete-time signal processing, for both linear time invariant (LTI) and non-LTI systems. For LTI systems, the topics include the sampling theorem, Fourier transform, convolution, and spectrum analysis, which lays the foundation for OFDM in wireless communications. Advanced topics will also be covered for time-variant systems, such as Heisenberg transform, Wigner distribution and Fractional Fourier transform, and their applications in radar, sonar and the OTFS modulation in wireless communications.

IOTA 5104 - Fundamentals of Discrete-Time Signal Processing (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6383)	Th 09:00AM - 11:50AM	Rm 238, E1	GONG, Zijun YANG, Liuqing	30	0	30	0

[Matching between Lecture & Tutorial required]

COURSE INFO

EXCLUSION	UFUG 2102
DESCRIPTION	Linear algebra is central to almost all areas of mathematics and is also used in most sciences and fields of engineering. This course provides a comprehensive introduction to topics of linear algebra studies, including linear systems, vector spaces, matrices, linear mappings and matrix forms, inner products, orthogonality and Gram-Schmidt process, eigenvalues and eigenvectors, symmetric matrices and diagonalization, and determinants.

EXCLUSION

UFUG 2102

DESCRIPTION

Linear algebra is central to almost all areas of mathematics and is also used in most sciences and fields of engineering. This course provides a comprehensive introduction to topics of linear algebra studies, including linear systems, vector spaces, matrices, linear mappings and matrix forms, inner products, orthogonality and Gram-Schmidt process, eigenvalues and eigenvectors, symmetric matrices and diagonalization, and determinants.

UFUG 2103 - Linear Algebra (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L04 (6810)	WeFr 04:30PM - 05:50PM	Rm 149, E1	GONG, Zijun	52	0	52	0
T04 (6820)	Mo 12:00PM - 12:50PM	Rm 122, E1	GONG, Zijun	52	0	52	0