Doctor of Philosophy in Electrical and Computer Engineering, University of Wisconsin-Milwaukee
Roles
Director, EE Undergraduate Program, UDC, 2022-Present Director, Smart Grids & Artificial Intelligence Laboratory (SGAI), UDC, 2019-Present Director, Center of Excellence for Renewable Energy (CERE), UDC, 2017-Present Director, Center of Renewable Energy, Alfred University, 2015-16
Courses Taught
Power Electronics Electric Machinery Control Systems Electric Circuits I, II
Expertise
Power Electronics and Renewable Energy Systems – Teaching and supervising research on power converters, grid integration, and energy storage technologies
Smart Grid and AI Applications – Applying artificial intelligence and machine learning to optimize power system operation and enhance grid resilience
Electrical Engineering Curriculum Development – Designing and improving undergraduate and graduate coursework in electrical engineering, emphasizing practical applications
Supervision of Research Projects – Guiding students in projects related to energy systems, power electronics, and AI-driven solutions for electrical grids
Academic Mentorship and Advising – Supporting students in their academic and career development, including NSF proposal writing and research dissemination
Archiving University Research and Course Materials – Managing course content, student projects, and research materials for institutional records
Research Focus / Works in Progress
Key Topics or Themes
Power Electronics & Motor Drives – Development of advanced high-efficiency DC-DC converters, bidirectional power conversion, and electric motor control strategies
Renewable Energy & Smart Grids – Optimization of renewable energy integration into power grids, including wind and solar energy, with a focus on reliability and efficiency
Artificial Intelligence & Machine Learning in Energy Systems – Application of AI and Bayesian statistics for predictive modeling, energy forecasting, and real-time optimization of grid performance
Electric Vehicles & Vehicle-to-Grid (V2G) Systems – Investigating V2G technologies, charging infrastructure, and stochastic modeling of EV charging demand
Wireless Power Transfer (WPT) – Exploring innovative designs to improve efficiency and misalignment tolerance in wireless power transfer for electric vehicles and consumer electronics
Risk & Reliability Analysis in Power & Energy Systems – Developing probabilistic models for resilience-based power infrastructure planning and smart grid fault detection
Microreactors & Nuclear Energy Optimization – Investigating remote control and deployment strategies for safe and efficient microreactors
Methodologies
Probabilistic Risk Assessment (PRA) & Bayesian Statistics – Quantifying uncertainty in energy systems and optimizing performance through probabilistic modeling
Monte Carlo Simulations – Simulating energy demand, power system behavior, and risk assessment under different operational scenarios
Artificial Intelligence & Data Science Techniques – Using machine learning, deep learning, and optimization algorithms for smart grid control, predictive maintenance, and anomaly detection
Computational Modeling & Simulation – Utilizing numerical simulations for power electronics circuit design, grid stability analysis, and renewable energy system performance
Hardware-in-the-Loop (HIL) & Experimental Validation – Implementing real-time simulations and lab-based validation of power electronics and energy storage systems
Copula-Based Dependence Modeling – Applying statistical modeling techniques for analyzing multivariate dependence structures in wind farms and energy forecasting
Leadership
University of the District of Columbia (UDC), Associate Professor, Electrical and Computer Engineering, 2023-Present University of the District of Columbia (UDC), Assistant Professor, Electrical and Computer Engineering, 2017-23 University of the District of Columbia, Leader of research and education initiatives, 2017-Present Frontiers in Energy Research, Editorial Board Member, Smart Grid Section, 2022-Present
Impact
Selected Publications
Rezazade, S., Shahirinia, A., Naghash, R., & Afjei, E. (2022). A novel efficient hybrid compensator for wireless power transfer. IEEE Transactions on Industrial Electronics.https://doi.org/10.1109/TIE.2022.3169840
Abbasian, S., Farsijani, M., Tavakoli Bina, M., & Shahirinia, A. (2022). A nonisolated common-ground high step-up soft-switching DC–DC converter with single active switch. IEEE Transactions on Industrial Electronics.https://doi.org/10.1109/TIE.2022.3198262
Amjadifard, R., Tavakoli Bina, M., Khaloozadeh, H., Bageroskuee, F., & Shahirinia, A. (2023). Suggesting a non-unity turn ratio two-winding coupled inductor for filtering CM EMI noise in an SRC. IEEE Transactions on Consumer Electronics.https://doi.org/10.1109/TCE.2023.3287982
Naderi, A., Abbaszadeh, K., Moradzadeh, M., & Shahirinia, A. (2020). High gain bidirectional quadratic DC-DC converter based on coupled inductor with current ripple reduction capability. IEEE Transactions on Industrial Electronics.https://doi.org/10.1109/TIE.2020.3013551
Saleki, A., Tavakoli Bina, M., & Shahirinia, A. (2021). Suggesting hybrid HB and three-quarter-bridge MMC-based HVDC systems: Protection and synchronous stability under DC faults. IEEE Transactions on Power Delivery. https://doi.org/10.1109/TPWRD.2021.3114297
Selected Presentations
Shahirinia, A. (2024, November). A novel method of Coupling coefficient estimation for a series-series wireless power transfer system. IEEE Industrial Electronics Conference, Chicago, Illinois.
Shahirinia, A. (2020, November). Dependent wind speed models: Copula approach. IEEE International Conference on Electric Power & Energy Conference, Edmonton, Canada.
Shahirinia, A. (2020, September). Wind speed prediction and visualization using long short-term memory networks (LSTM). IEEE International Conference on Information Science and Technology, Bath, London.
Shahirinia, A. (2019, July). Compute process and measurement noise covariances for human motion estimation: A Kalman filter approach with IoT sensors. IEEE International Conference on Cyber Technology in Automation, Suzhou, China.
Selected Grants
National Science Foundation. (2019). Predictive models for wind-penetrated power systems using the Bayesian approach.
Department of Defense. (2020). Acquisition of advanced robotics and autonomous vehicle technology (ARAVT) for research in smart grid systems, teaching, and K-12 outreach at the University of the District of Columbia.
National Science Foundation. (2020). Workforce development for new generation of cybersecurity systems.
National Institute of Standards and Technology. (2018). Professional research experience program at the University of the District of Columbia.
DC Water Resources Research Institute. (2019). Development of streamflow prediction model and software package for Anacostia River at non-gauged locations based on Bayesian approach.
Recognitions
Outstanding Professor, UDC, 2020-21 Chancellor Award for Academic Excellence, University of Wisconsin-Milwaukee, 2010-14 Best Paper Award, IEEE International Conference on Electric Power & Energy Conference, 2020 Outstanding Teaching Assistant, University of Wisconsin-Milwaukee, 2011 Best Paper Award, 7th Annual Green Energy Summit, 2010
Invited Participations
Shahirinia, A. (2023). Invited speaker on AI applications in smart grids and renewable energy. Frontiers in Energy Research Webinar Series.
Shahirinia, A. (2022). Expert panelist on wireless power transfer for dlectric vehicles. IEEE Power & Energy Society Technical Conference, Boston, Massachusetts.
Shahirinia, A. (2021). Guest lecturer on Bayesian statistical modeling in power systems.University of Wisconsin-Milwaukee Graduate Seminar Series, Milwaukee, Wisconsin.
Shahirinia, A. (2020). Smart grid resilience strategies. Department of Energy Smart Grid Workshop, Washington, D.C.
Shahirinia, A. (2019). Expert panelist on renewable energy grid entegration challenges.National Science Foundation Energy Systems Symposium. Arlington, Virginia.
