Teaching, in addition to research, is an important lifelong endeavour for engineering educators and faculty. It encompasses the conventional role as an effective disseminator of knowledge in the classroom environment as well as the more challenging responsibility of technically and ethically guiding students. In addition, a successful educator is not one who is invariably superbly trained in technical content as teaching and learning are not mutually independent. Last but not least, as engineering is a technologically-driven and evolving field, it is important to continuously supplement and augment traditional aids with technological media. As an aspiring educator, I believe it is important to intellectually stimulate and making an effort in constructing interpersonal rapport with students. These two traits are not exclusive and an effective educationalist should be conversant in both. While the former relating to the clarity and organization of technical content improves with practice, developing a relationship that fosters learning is more daunting and honed through experience. A learning environment where there is high interpersonal rapport is the essential foundation for high intellectual excitement and valuation of learning.

Classes Taught

  • 30.114 Advanced Feedback & Control (Course Lead & Developer)
    Extending feedback control theory and applications to include periodic signals and discrete-time systems. Mathematical modelling and analysis of discrete time systems in various disciplines using state-space, pulse transfer function and z-transform. Relating controllability and observability and their canonical forms to synthesize and design advanced continuous and discrete-time controllers. Introduction of pole-placement based controller design and formulation of state observers.

Course Syllabus, Course Map

Spring 2015 (Instructor Rating: 4.7/5.0), Spring 2016 (4.9/5.0), Spring 2017 (4.8/5.0)

  • 30.101 Systems & Control (Course Lead  & Developer)
    Lumped parameter mathematical modelling and analysis of continuous time systems and signals in various disciplines using state-space and transfer function approaches and the Laplace transform. Analysis of linear time-invariant (LTI) systems and signals in time and frequency domains for synthesis and design of automatic feedback controllers.

Course Syllabus, Course Map

Spring 2014 (4.6/5.0), Spring 2015 (4.8/5.0), Spring 2016 (4.7/5,0), Spring 2017 (4.3/5.0)

A key and highly unique feature of this class is the 2D competitive infused designette. Designettes are glimpses, snapshots, small-scale, short turnaround and well-scoped design problems that provide a significant design experience. Here, an inductive-based week long design activity strategically held in the middle of the semester was conceived to introduce and motivate the notion of feedback control. During the course of the week, students in teams design, analyze and synthesize automatic controllers to enable a standardized differential wheeled robotic platform to traverse a line circuit autonomously. The strategy to achieve this capability is intentionally left to be open-ended, and students have the design freedom to select and position sensors needed to sense the track, as well as implement and troubleshoot the programming required to enable autonomous control. The activity culminates with a pulsating head-to-head single elimination tournament to decide the overall champion.

S. Foong, K. Subburaj and K. L. Wood, “An Inductive, Design-Centric Approach to Control Engineering Education with a Competitive Atmosphere,” 2017 ASME Dynamic Systems and Control Conference, Tysons, VA. doi: 10.1115/DSCC2017-5157

S. Foong, “A Design-Centric Control Education with a Competitive Flavor,” ASME Dynamic Systems and Control Division Newsletter Summer 2016. Download.

  • 10.007 Modelling the Systems World
    This subject is divided into two parts – Systems Modelling and Systems Optimisation. Systems modelling introduces the basics of mathematical modelling. Students will also learn how to solve differential equations (first order and second order) and the Laplace Transform method. Systems Optimisation introduces students to mathematical tools for optimisation, in particular convex optimisation, numerical solution algorithms, and networks. Throughout the course, a number of applications that require modelling of real-world systems will be discussed.

Spring 2017 (4.6/5.0)

  • 3.007 Introduction to Design
    The SUTD freshmore course, Introduction to Design, introduces participants to concepts of design at a variety of scales and through both engineering and architectural design disciplines. Participants will be exposed to core technology and design themes including principles, design processes, modes of thinking and analysis, relationships between form, space, structure and materiality, and social and cultural aspects of design. The subject introduces essential skills and mindset of innovation, entrepreneurship, and methodologies in design including teamwork and workflow organization, team building and leadership, written and oral communication, site analysis, graphic and analytical representation, fabrication techniques, and a variety of computational techniques. Student teams formulate and complete design projects, setting and achieving milestones under a team of instructors composed of both engineers and architects; projects will be defined in connection with applications in outreach, transportation, the built environment, energy, infrastructure and others.

Fall  2012 (4.5/5.0), Fall 2013 (4.2/5.0), Fall 2014 (4.8/5.0)

  • Integrated Learning Programming (ILP) Part 2 – Physics
    The ILP is a bridging programme unique to SUTD. Four preparatory subjects – Mathematics, Physics, Biology, and Chemistry, are offered to students commencing studies in SUTD. The programme is designed with the aim of instilling fundamental mastery in math and science in students with no or limited knowledge or who simply desire to have a refresher course in a particular area of study.

Fall 2012 (4.6/5.0)