ZHANG, Tongyi - HKUST Class Schedule & Quota

Class Schedule & Quota
2024-25 Spring 2024-25 Fall 2023-24 Summer 2021-22 Winter
2024-25 Spring
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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COURSE INFO

VECTOR	[3-0-0:3]
DESCRIPTION	Materials informatics integrates materials science and engineering with artificial intelligence (AI), machine learning (ML), and database to accelerate the innovation in the whole materials development continuum and to speed up the process from data to material knowledge. The 2024 physics and chemistry Nobel Prizes on AI are greatly promoting and accelerating the development of materials informatics. This is a continued course in materials informatics to introduce advanced AI and ML algorithms with more focus on global Bayesian optimization, transfer learning, transformer, and graph neural networks. The course will be lectured through vivid and practical examples from materials science and engineering. Notably, this course is designed for students whose majors are in broader fields of sciences and engineering, but not in AI and computer sciences and engineering. This course will empower those with limited knowledge of AI and ML to learn Materials Informatics without too much difficulty.

VECTOR

[3-0-0:3]

DESCRIPTION

Materials informatics integrates materials science and engineering with artificial intelligence (AI), machine learning (ML), and database to accelerate the innovation in the whole materials development continuum and to speed up the process from data to material knowledge. The 2024 physics and chemistry Nobel Prizes on AI are greatly promoting and accelerating the development of materials informatics. This is a continued course in materials informatics to introduce advanced AI and ML algorithms with more focus on global Bayesian optimization, transfer learning, transformer, and graph neural networks. The course will be lectured through vivid and practical examples from materials science and engineering. Notably, this course is designed for students whose majors are in broader fields of sciences and engineering, but not in AI and computer sciences and engineering. This course will empower those with limited knowledge of AI and ML to learn Materials Informatics without too much difficulty.

AMAT 6000A - Advanced Materials Informatics (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6244)	We 09:00AM - 11:50AM	Rm 228, E2	GAN, Zecheng ZHANG, Tongyi	40	0	40	0