SC3000 Artificial Intelligence
Faculty teaching, 2024 (tutorials only)
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[Nanyang Technological University, Singapore] This course aims to teach about intelligent agents and decision making processes. Topics include Intelligent Agents, Search Algorithms, Markov Decision Process, Reinforcement Learning, Game Theory, Neural Networks Basics, Fuzzy Logic, and Fuzzy Inference Systems
SC5002 Artificial Intelligence: Fundamentals and Applications
Faculty teaching, 2024 (lecturer and course coordinator)
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[Nanyang Technological University, Singapore] This is a course open to college students from non-computer science majors. AI is finding widespread applications in finance, banking, healthcare, manufacturing and many other industries. This course is an introduction course to artificial intelligence to students who are not from computer science or computer engineering background. It will introduce to you what artificial intelligence is about and its fundamentals and applications. You will learn how software systems make intelligent searches for problem solutions, how intelligent systems learn to perform their tasks. These are fundamental knowledge for intelligent systems. You will also gain basic understanding of generative AI.
SC2103 Digital Systems Design
Faculty teaching, 2024 (tutorials only)
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[Nanyang Technological University, Singapore] This is an undergraduate course on digital system designs. It includes topics like FPGA architectures and synthesis, Arithmetic on FPGA, Timing and Pipelining, Buses and Interfaces, and Asynchronous Designs.
CENTER FOR BRAINS, MINDS AND MACHINES SUMMER COURSE
Head teaching asssitant, 2020-2023
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[Harvard-MIT CBMM] An intensive three-week course will give advanced students a “deep end” introduction to the problem of intelligence – how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines.
NEURO 140 AND 240: BIOLOGICAL AND ARTIFICIAL INTELLIGENCE
Head teaching assistant, 2020
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[Harvard University] This is a seminar-style course which provides a foundational overview of key ideas in Computational Neuroscience and the study of Biological Intelligence. At the same time, the course will connect the study of brains to the blossoming and rapid development of ideas in Artificial Intelligence. Topics covered include the biophysics of computation, neural networks, machine learning, bayesian models, theory of learning, deep convolutional networks, generative adversarial networks, neural coding, control and dynamics of neural activity, applications to brain-machine interfaces, connectomics, among others. Lectures will be taught by leading Harvard experts in the field.
EE4302: ADVANCED CONTROL SYSTEM
Teaching assistant, 2016
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[National University of Singapore] This module provides the foundation for a more advanced level control systems course. Topics include system description, controllability, observability, selection of pole locations for good design, observer design, full-order and reduced-order observers, combined control law and observer. It is also a first course in nonlinear systems and control. Topics include non-linearities in control systems, use of root-locus in analysis of non-linear systems, describing function and its use in analysis and design of control systems, non-linear ordinary differential equations, singular points, and phase-plane analysis.
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