teaching
2025 1st semester
Data Structures and Algorithm EEE2020-03
In this course, we explore key data structures and algorithms (DSA) using the C++ language. Data structures and algorithms are fundamental building blocks that teach you how to solve complex problems efficiently and write optimized code. They are essential to improve your programming skills and crucial for technical interviews at top tech companies. The curriculum starts with an introduction to C and C++ programming, including arrays, pointers, structures, and classes. We then cover various data structures, including array lists, linked lists, queues, stacks, trees, hash tables, and graphs. Additionally, we discuss important algorithms, such as sorting, searching, and shortest path problems.
Introduction to Artificial Intelligence GEV6101-01
Introductory lecture for students of graduate school of engineering.
Interdisciplinary AI Engineering ENG3406-01
Team teaching lecture for undergraduate students.
2024 2nd semester
Generative AI for Multimedia EEE8322-01
In this course, we explorer the recent advances of deep generative models. The coursework covers important theories and applications of various generative models, including VAEs (Variational Autoencoders), GANs (Generative Adversarial Networks), autoregressive models, normalizing flows, diffusion models, and recent multimodal generative models.
Data Structures and Algorithm EEE2020-03
In this course, we explore key data structures and algorithms (DSA) using the C++ language. Data structures and algorithms are fundamental building blocks that teach you how to solve complex problems efficiently and write optimized code. They are essential to improve your programming skills and crucial for technical interviews at top tech companies. The curriculum starts with an introduction to C and C++ programming, including arrays, pointers, structures, and classes. We then cover various data structures, including array lists, linked lists, queues, stacks, trees, hash tables, and graphs. Additionally, we discuss important algorithms, such as sorting, searching, and shortest path problems.
3D Multimodal Image Generation and Evaluation ENG6801-01
Team teaching lecture for graduate students.
Interdisciplinary AI Engineering ENG3406-01
Team teaching lecture for undergraduate students.
2024 1st semester
Digital Signal Processing EEE4420-03
This course covers the fundamental mathematical theories of digital signal processing, including interpretations and methods in the time and frequency domains of digital signals, Discrete Fourier Transform (DFT), sampling, and digital filters. Furthermore, the course explores the application of digital signal processing theories to modern artificial intelligence algorithms.