 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This is an introductory course about computational methods for physical systems such as quantum physics, spin glass et al. It requires knowledge about linear algebra and familiarity of any programming language. The course covers not only computational methods related to matrix/tensor computation, differential programming, and combinatorial optimization, but also techniques related to CUDA programming and the Julia programming language. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6009) | We 06:30PM - 09:20PM | Rm 101, W4 | LIU, Jinguo | 30 | 11 | 19 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This is an introductory course for postgraduate students with materials science background. Basic topics of solid state physics including electronic band structure, phonons, electron interactions and spin correlations will be covered. In addition, modern topics of high temperature superconductors, topological electrons, spin liquids and low dimensional systems will be introduced, providing a beginner’s guide to quantum materials. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6016) | 06-FEB-2025 - 29-MAR-2025 Mo 01:30PM - 04:20PM | Rm 150, E1 | LI, Haoxiang | 30 | 12 | 18 | 0 | |
| 31-MAR-2025 - 12-MAY-2025 Mo 01:30PM - 04:20PM | Rm 150, E1 | ZHU, Guoyi |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Biophysics lies at the interface among biology, physics and chemistry. The physical properties of biomolecules are responsible for the molecular characteristics of biological processes. Understanding how these biomolecules operate in life activities demands investigations through multidisciplinary approaches, including determinations of the atomic structures, characterizations of the kinetics and energy, constructions of the theories and models, etc. This course will offer an overview of the biomolecular structures and the physicochemical mechanisms for organizing these structures, then describe the methods for characterizing the structure and dynamics of biomolecules, and discuss the “structure-function” relationship in molecular biology. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6022) | We 01:30PM - 04:20PM | Rm 202, W1 | CHU, Xiakun | 20 | 9 | 11 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course will cover the physics of the electronic structure of pi-conjugated materials and their neutral, excited and charged states (excitons, polarons), their optical properties (absorption, emission), photophysical processes, photochemistry, energy transfer and charge transport. It will introduce the principles of design and operation of molecular based light emitting devices, solar cells etc. as well as providing an introduction to device fabrication and device engineering for maximum performance and lifetime. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6023) | Tu 01:30PM - 04:20PM | Rm 201, W1 | WU, Jiaying | 20 | 7 | 13 | 0 |
| 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. |
| 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 | 7 | 33 | 0 |
| VECTOR | [1-3 credit(s)] |
|---|---|
| DESCRIPTION | An independent study on selected topics carried out under the supervision of a faculty member. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6522) | TBA | TBA | TBA | 20 | 4 | 16 | 0 |
| VECTOR | [1-3 credit(s)] |
|---|---|
| DESCRIPTION | An independent study on selected topics carried out under the supervision of a faculty member. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6539) | TBA | TBA | TBA | 20 | 3 | 17 | 0 |
| DESCRIPTION | Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6026) | TBA | No room required | TBA | 999 | 8 | 991 | 0 |
| DESCRIPTION | Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6028) | TBA | No room required | TBA | 999 | 35 | 964 | 0 |