Teaching

 

ECE 2195 - Neuromorphic Systems Design: Spring 2021-Present

This cross-disciplinary course will teach principles, design methodology, applications of neuromorphic architectures and energy efficient event-based sensors like Dynamic Vision Sensors (DVS) and silicon cochlea. The syllabus will cover a brief background of neuroscientific principles for neuron and synapse modelling as well as the evolution of neuromorphic engineering over the decades. Systems and algorithms presented in literature and industry standards will be analyzed and discussed in detail. Students will be required to apply the acquired skills in designing embedded systems on Intel's Loihi platform and/or actual circuits with industry-level CAD tools. Students will be given the opportunity to extend successful projects into design, fabrication, and testing of custom silicon integrated circuits after completion of the course. By the end of the course, students should understand the steps needed to develop a neuromorphic systems from original concept to a working demo.

 

ECE 1770 Introduction to AI Applications in ECE: Spring 2024-Present

This course will teach principles, design methodology and implementation of Artificial Intelligence (AI) systems particularly targeted towards applications in the field of Electrical and Computer Engineering. The syllabus will cover fundamentals of Python programming and foundations of AI models, followed by a deep-dive on recent Deep Learning architectures including Transformers. The second half of the course will focus on multiple domain-specific applications in ECE related tracks such as Computer Vision, Biomedical Diagnostics, Power systems, Control theory etc. Systems and algorithms presented in literature and industry standards will be analyzed and discussed in detail. Students will be required to apply the acquired skills in designing practical systems. Students will be given the opportunity to extend successful projects into conference publications after completion of the course. By the end of the course, students should understand the steps needed to develop AI systems from original concept to a working demo for ECE applications.

 

ECE 101 - Linear Circuits Theory: Fall 2021-Present

This is a first course in the fundamentals of circuit and linear analysis techniques that form the foundation of further study in the fields of electrical and computer engineering. Upon completion of the course, students will be able to recognize, analyze, and design circuits using passive elements such as sources, resistors, capacitors, and inductors using classical techniques such as KCL, KVL, Thévenin/Norton analysis, superposition, and transformation. An overview of AC analysis includes the switched response of first- and second-order circuits, phasor analysis, and AC power fundamentals. Additional topics relevant to future classes include transformers, 2-port networks, as well as frequency response and bode plot analysis. The course includes 12 laboratory experiments to reinforce the material covered in class.

 

ECE 1212 - Electronic Circuit Design Laboratory: Fall 2022

This is a laboratory course on electronic circuits design and applications. Topics include multi-stage amplifier design; operational amplifier applications; analog-digital conversion applications, and active filters.