Enquiry for Science Major/Minor/Programme Requirements
AILT9023 Artificial intelligence in physics (3 credits) Academic Year 2026
Offering Department Physics Quota 60
Course Co-ordinator Dr F K Chow, Physics < judychow@hku.hk >
Teachers Involved (Dr F K Chow,Physics)
(Dr J C S Pun,Physics)
(Prof S C Y Ng,Physics)
(Prof Y J Tu,Physics)
(Prof Z Y Meng,Physics)
Course Objectives This course aims to equip students with conceptual understanding and hands-on experience at the intersection of AI and physics.  Students will explore the contribution of physics in the development of AI, particularly in areas such as neural networks and optimization methods used in AI.  They will also learn how to properly use the tools and techniques of AI to enhance learning, analyze data, and unveil new knowledge and insight in physics.
Course Contents & Topics In recent years, the applications of Artificial Intelligence (AI) in physics have rapidly expanded along advances in AI technology.  Meanwhile, physics principles play crucial roles in the development and applications of AI, particularly in the design and modeling of neural networks.  It is essential for physics students to acquire knowledge of AI because it provides useful tools and techniques for analyzing data, discovering patterns, and simulating complex systems.  Building on the foundation established in AILT1001, this course aims to deepen students' understanding of AI and its potential for driving discoveries and advancing knowledge across various fields of physics.  In addition, students will explore and reflect on the ethical implications of using AI in different scenarios throughout their learning and research in physics.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 elaborate the contribution of physics to the development of AI
CLO 2 apply AI effectively at various stages of the research process in physics
CLO 3 recognize how AI accelerates research in different fields of physics
CLO 4 evaluate the impact and ethical considerations of using AI for the advancement of knowledge in physics
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Pass or already enrolled in PHYS2250 or PHYS2265.
NOT for Year 1 students.
Priority will be given to students majoring in Physics and Physics (Intensive).
Course to PLO Mapping
Offer in 2026 - 2027 Y        2nd sem    Examination No Exam     
Offer in 2027 - 2028 Y
Course Grade Distinction/Pass/Fail
Grade Descriptors
Distinction Thorough mastery of principles and subject matter in the course required for attaining almost all the course learning outcomes. Give accurate and comprehensive explanation to almost all the principles and concepts. Demonstrate the ability to apply relevant theories and concepts to a wide range of familiar and unfamiliar situations. Strong ability to apply AI tools and techniques in a comprehensive and logical manner. Express the ideas in a comprehensive and cogent manner. Display excellent verbal skills and deliver a compelling and well-structured presentation at an appropriate level.
Pass General and sufficient command of principles and subject matter in the course required for attaining most of the course learning outcomes. Give clear explanation to most of the principles and concepts but with some minor gaps and errors. Demonstrate the ability to apply relevant theories and concepts to most familiar situations. Satisfactory ability to apply AI tools and techniques in a comprehensive and logical manner. Express the ideas in a coherent and clear manner. Display average verbal skills and deliver an adequate presentation at an appropriate level.
Fail Little or no evidence of command of principles and subject matter in the course required for attaining the course learning outcomes. Give clear explanation to limited principles and concepts with significant gaps and errors. Demonstrate very little or no ability to apply relevant theories and concepts to familiar situations. Limited ability to apply AI tools and techniques in a comprehensive and logical manner. Express the ideas in a fragmented and confusing manner. Display poor verbal skills and deliver a disorganized presentation at an inappropriate level.
Communication-intensive Course N
Course Type Lecture-based course
Course Teaching
& Learning Activities
Activities Details No. of Hours
Group work 24.0
Lectures 12.0
Tutorials 10.0
Reading / Self study 20.0
Assessment Methods
and Weighting
Methods Details Weighting in final
course grade (%)		 Assessment Methods
to CLO Mapping
Assignments Completion of online quizzes 20.0 1,2,3,4
Presentation Application of AI on a mini research project in physics 40.0 2,3,4
Test Final assessment for evaluating students’ achievement of the course learning outcomes 40.0 1,2,3,4
Required/recommended reading
and online materials		 P. V. Coveney and R. R. Highfield, AI needs physics more than physics needs AI, Front. Phys. 13, 1731777 (2026)
L. Ding, Students' perceptions of using ChatGPT in a physics class as a virtual tutor, International Journal of Educational Technology in Higher Education 20(1), 63 (2023)
L. Jiao et al., AI meets physics: a comprehensive survey, Artificial Intelligence Review 57, 256 (2024)
M. Krenn et al., On scientific understanding with artificial intelligence, Nature Reviews Physics 4, 761 (2022)
Q. Miao and F.-Y. Wang, Artificial Intelligence for Science (AI4S) (Springer, Switzerland, 2024), Chapter 3, pp.41-52
D. B. Resnik and M. Hosseini, The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool, AI and Ethics 5, 1499 (2025)
Course Website http://moodle.hku.hk
Additional Course Information The offering of this course in Semester 2 of the 2026/27 academic year is subject to final approval by the University.


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