teaching

1. Aug 2024 - Dec 2024 TA at University of Notre Dame, PhD level

CSE 60556 Large Language Models: Basics and Practice: This course aims at graduate students who are interested in using and/or developing large language model (LLMs) techniques. It is designed for those who have knowledge and programming experience of machine learning. In it, we introduce tasks and datasets related to language models (LMs), LLM architectures, LLM training techniques, reasoning methods, knowledge augmentation methods, efficient LLM methods, various LLM applications (e.g., assistant, education, healthcare, RecSys, planning), and challenges in LLMs for social good…

2. Jul 2023 - Aug 2023 Company-sponsored lecturer at Shenzhen University

Theory and Practice of Large Models: This course introduces students to the fundamental principles and techniques of AI compilers, with a focus on practical applications using the TPU-MLIR project. Through this course, students will learn how to design, develop, and optimize AI compilers to achieve efficient utilization of TPUs. The course will provide students with a deep understanding of AI compilers and equip them with the skills necessary to build a solid foundation for their future careers in artificial intelligence.

3. Sep 2022 - Dec 2022 TA at Columbia University, MS level

ELEN E6770 Network Virtualization and Cloud Computing: Further study of areas such as communication protocols and architectures, flow and congestion control in data networks, performance evaluation in integrated networks.