Dr Arunachalam Sundaram

School of Science, Engineering & Environment

Photo of Dr Arunachalam Sundaram

Contact Details

SEE Building, University of Salford, Greater Manchester, M5 4WT, United Kingdom.

Current positions

Lecturer

Biography

Dr. Arunachalam Sundaram is a faculty member at the School of Science, Engineering, and Environment at the University of Salford and serves as the Program Lead for the Greater Manchester Institute of Technology. He earned his B.E. in Electrical and Electronics Engineering from Annamalai University, an M.E. in Power Systems Engineering (Gold Medalist), and a Ph.D. in Electrical Engineering from Anna University. He also completed a Post Graduate Program in Artificial Intelligence and Machine Learning from the University of Texas at Austin. With nearly two decades of academic experience, Dr. Arunachalam Sundaram has taught diverse graduate and undergraduate students, managed academic programs, and developed industry-relevant courses. His research interests include artificial intelligence, EV, machine learning, optimization techniques for power systems engineering, and smart grids, with numerous publications in high-impact journals. Previously, he was an Associate Professor and Program Director at Jubail Industrial College in Saudi Arabia. He is recognized for his strong interpersonal, research, and writing skills, and his ability to create interactive learning environments.

Areas of Research

Power Systems
Machine Learning
Smart Grids
Renewable Energy
Optimization Algorithms
EV

Areas of Supervision

My research focuses on leveraging advanced optimization and machine learning methodologies to enhance the efficiency, reliability, and sustainability of power systems and smart grids. I am keen to support researchers in exploring these cutting-edge topics and contribute to the advancement of this dynamic field.I am interested in guiding scholars in the following research areas:
- AI-Driven Optimization for Smart Grids
- Integration of Electric Vehicles (EVs) in Power Systems
- Machine Learning for Power System Fault Detection
- Optimization Techniques for Integrating and Managing Renewable Energy Sources
- Resilience of Power Grids Against Extreme Events
- Integration of Machine Learning Techniques to Economic and Emission Dispatch
- Optimization Applied to Power Systems Engineering
- Energy Management Systems for Smart Cities

Teaching

I am currently teaching the following courses:

- Level 6 Course: Powertrain, Hybrid, and Electric Vehicles
- Level 5 Course: Machines and Drives

Over the past twenty years, I have had the privilege of teaching a wide array of undergraduate and postgraduate courses, enriching my experience and diversifying my expertise. My teaching portfolio includes the following undergraduate courses:

- Power System Analysis and Control
- Circuit Analysis
- FACTS (Flexible AC Transmission Systems)
- Transmission and Distribution
- Protection and Switchgear
- Basic Electrical Engineering
- Electrical Troubleshooting
- Control Engineering

At the postgraduate level, I have taught:

- Advanced Power System Analysis
- FACTS (Flexible AC Transmission Systems)
- HVDC (High-Voltage Direct Current)

In addition to lecture courses, I have also instructed various laboratory courses, ensuring students gain hands-on experience and practical skills in the following areas:

- Transmission and Distribution Lab
- Troubleshooting Lab
- Control and Protection Lab
- Advanced Power System Simulation Lab
- Power System Simulation Lab
- Electrical Circuits Lab
- Engineering Practices Lab
- Control System Lab

My extensive teaching experience has equipped me with the ability to guide students effectively through complex concepts and practical applications, fostering a deep understanding and enthusiasm for the field of electrical and power systems engineering.