Teaching Experience

Courses Taught at Stevens

Teaching Development

Research Supervision Courses at Stevens

Theses Supervised at Stevens

Ph.D. Committee Service at Stevens

Invited Lectures and Talks

Past Teaching Assistant Experience

Courses Taught at Stevens

EE 602 Analytical Methods in Electrical Engineering - Fall 2023, Fall 2024, Fall 2025, Fall 2026.
EE/CPE 345 Modeling and Simulation - Spring 2024, Spring 2025, Spring 2026.
CS/EE 605 Probability and Stochastic Processes I - Spring 2026. New course.

Average student rating (on instructor effectiveness as a teacher) across all completed courses from Fall 2023 to Spring 2026: 4.49 of 5.

Teaching Development

Beyond delivering courses, I build the material students learn from.

At Stevens. Both of my graduate courses — EE 602 Analytical Methods in Electrical Engineering and CS/EE 605 Probability and Stochastic Processes I — were established courses that other faculty had taught before me. Rather than teach from the existing material, I decided to create my own entirely for both: lecture notes, slides, assignments, and in-class demonstrations. The reason was to keep each course up to date with recent developments and trends in its field.

At the University of Notre Dame. During my postdoctoral work I collaborated with two MathWorks engineers on a set of Simulink teaching modules for an undergraduate control systems course.

A virtual laboratory for experimenting with delays — in both sensing and actuation — and with sampled-data systems.
A demonstration that feedback control applies not only to conventional time-driven systems but also to event-driven systems modelled by Petri nets.

The motivation was access: these let a student run the experiment on a laptop instead of queuing for scarce and expensive physical rigs.

One of the Simulink teaching modules built with MathWorks engineers, a virtual laboratory for delays and sampling in a feedback loop.

Virtual Lab Setup Created in Matlab to Demonstrate/Experiment with Feedback Based Petri net Control Schemes

At the University of Peradeniya. As an instructor before graduate school, I designed and fabricated two laboratory setups so that students could implement analog and digital controllers themselves using simple integrated circuits, rather than only simulating them. The point was to put a real controller in their hands: a circuit that misbehaves teaches something a simulation that converges does not.

Control laboratory boards I designed and fabricated at the University of Peradeniya: analog (left) and digital (right) controller implementations.

I also conducted revision classes organised by the student union before each mid- and end-semester examination. Each covered one course over a full day, for an audience of 50 to 350 students, and I was invited to run at least three every semester. They taught me to derive a course's fundamentals from scratch and to show how its pieces connect, under real time pressure.

Research Supervision Courses at Stevens

CPE 485/486 Undergraduate Senior Thesis - Fall 2025, Spring 2026.
EE/CPE 800 Special Problems in Electrical Engineering - Spring 2026, Fall 2026.
EE/CPE 423 Senior Design - AY 2023-24.
EE 801 Special Problems - Spring 2024.

Theses Supervised at Stevens

Mohammad Javad Najafirad, Ph.D. dissertation, from Fall 2023. Dissipativity-Based Co-Design of Controllers and Topology for Resilient Microgrids. Proposal defended April 2026; expected graduation May 2027.
Theodore Rogalski, M.S. thesis, from Fall 2026. Working title: Safety-Aware Multi-Agent Reinforcement Learning for Persistent Maritime Monitoring with Unmanned Surface Vehicles.
TingYou Chung, M.S. thesis, Fall 2025 to Spring 2026. Performance-Energy Trade-offs in Energy-Aware Persistent Monitoring Systems. Defended April 2026.
Theodore Rogalski, Undergraduate thesis, Fall 2025 to Spring 2026. Fully Decentralized, Safety-Aware Deep Reinforcement Learning for the Discrete Time Persistent Monitoring Problem with a Graph Topology. Defended April 2026; the resulting paper was accepted to the IEEE-HKN Papers Conference.

Ph.D. Committee Service at Stevens

Xinchi Huang, Stevens, proposal defense September 2026. Learning-Based Perception and Control for Multi-Robot Formation and Mobile Manipulation. Advisor: Yi Guo.
Zhuzhu Wang, Stevens, proposal defense 2026. Coordinated Control of Offshore Wind Farms for Power System Frequency Support. Advisor: Lei Wu.
Zihao Song, University of Notre Dame, dissertation defense 2025. Achieving Resilience for Cyber-Physical Systems: Offline and Online Approaches. Advisors: Hai Lin and Panos J. Antsaklis.
Afshin Eisazadeh Kharabeh, Stevens, proposal defense 2025. Time Series Data Classification Using Deep Learning with Applications. Advisor: Yu-Dong Yao.
Xianbang Chen, Stevens, dissertation defense 2025. Boosting Power System Operation Economics via Closed-Loop Predict-and-Optimize. Advisor: Lei Wu.
Weilun Wang, Stevens, proposal defense 2024 and dissertation defense 2025. On Optimal Planning and Operation of Smart Grid Edge Devices: Electric Vehicles and Distributed Energy Resources. Advisor: Lei Wu.

Invited Lectures and Talks

[L19] From Model-Based Foundations to Data-Driven Intelligence: Toward Resilient Networked Cyber-Physical Systems, ECE Department Seminar Series (EE 820), Stevens Institute of Technology, 2025.

[L18] Online Distributed Graph Neural Networks for Distributed Optimal Control of Networked Cyber-Physical Systems, iCNS/ECE Symposium on AI Research and Innovations, 2025.

[L17] Generalized Control and Topology Co-Design Framework for Networked Cyber-Physical Systems, Keynote, 2025 Spring IEEE Metropolitan AI Applications Symposium, 2025.

[L16] Decentralization and Dissipativity: A Framework for Control and Topology Co-Design in Networked Cyber-Physical Systems, Webinar, IEEE PES, RAS and IES Sri Lanka chapters, 2024.

[L15] Decentralization and Dissipativity: A Framework for Control and Topology Co-Design in Networked Cyber-Physical Systems, Symposium on Emerging Topics in Networks, Systems and Cybersecurity, Stevens Institute of Technology, 2024.

[L14] Intelligent Control and Optimization Techniques for Next-Generation Complex Dynamic Interconnected Systems, Stevens Institute of Technology, Spring-2023.

[L13] Intelligent Control and Optimization Techniques for Next-Generation Complex Dynamic Interconnected Systems, New York University, Spring-2023.

[L12] Leveraging ChatGPT for Optimization: Learning, Solving, and Discovering Opportunities, University of Notre Dame, Spring-2023.

[L11] Robust Control using Integral Quadratic Constraints, EE 60655: Advanced Control Systems, University of Notre Dame, Spring-2023.

[L10] Optimization of Networks: Network Flow Problems, EE 60551: Optimization, University of Notre Dame, Spring-2023.

[L9] Optimization of Networks: Network Simplex, EE 60551: Optimization, University of Notre Dame, Spring-2023.

[L8] Introduction to Matlab and Simulink, EE 40455: Control Systems, University of Notre Dame, Fall-2022.

[L7] Optimization of Networks: Network Flow Problems, EE 60551: Optimization, University of Notre Dame, Spring-2022.

[L6] Optimization of Networks: Network Simplex, EE 60551: Optimization, University of Notre Dame, Spring-2022.

[L5] Control of Networks: Stability and Stabilization, EE 60655: Advanced Control Systems, University of Notre Dame, Spring-2022.

[L4] Model Based Networked Control Systems Design, EE 60655: Advanced Control Systems, University of Notre Dame, Spring-2022.

[L3] Introduction to Matlab and Simulink, EE 40455: Control Systems, University of Notre Dame, Fall-2021.

[L2] Control and Optimization of Autonomous Systems, Conference Workshop: International Conference on Innovation and Emerging Technologies (ICIET), University of Sri Jayewardenepura, 2021.

[L1] Current Trends in Control and Optimization of Complex Autonomous Systems, Electrical and Electronic Engineering Society Workshop, Department of Electrical and Electronic Engineering, University of Peradeniya, 2021.

Past Teaching Assistant Experience

[T10] Probability with Statistical Applications (EK 500), Boston University, Fall-2020.

[T9] Energy and Thermodynamics (ME 304), Boston University, Spring-2020.

[T8] Probability with Statistical Applications (EK 500), Boston University, Fall-2019.

[T7] Energy and Thermodynamics (ME 304), Boston University, Spring-2019.

[T6] Adaptive Signal Processing (EE 515), University of Peradeniya, Fall-2016.

[T5] Industrial Robotics (EE 536), University of Peradeniya, Fall-2016.

[T4] Digital Signal Processing (EE 325), University of Peradeniya, Fall-2016.

[T3] Non-linear and Multi-variable Systems (EE 539), University of Peradeniya, Spring-2016.

[T2] Estimation and Identification (EE 534), University of Peradeniya, Spring-2016.

[T1] Automatic Control (EE 323), University of Peradeniya, Spring-2016.

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