Imen Jendoubi

00216 71 180 108

Office: 117



Imen Jendoubi received her Ph.D. degree with honors in Electrical and Computer Engineering from McGill University, Canada in 2023. Prior to that, she obtained a Master’s degree in Energy Engineering (obtained with honors) from Ecole Polytechnique Montréal, Canada in 2019. She also holds a National Engineering Diploma in Advanced Sciences and Technologies with distinction from the National School of Advanced Science and Technology and the Preparatory Institute for Scientific and Technical Studies in Tunisia, where she was awarded the presidential prize for excellence in engineering at the national level. As part of her engineering studies, she joined RWTH Aachen University in Germany as an exchange student in 2017. Her fields of expertise include machine learning, optimization methods, and mathematical programming and simulation with a focus on their application in planning and operating low-carbon networks considering operational flexibilities and smart grid technologies.


  • Machine learning
  • Mathematical programming and simulation
  • Operations research and optimization methods
  • Artificial intelligence with application to power network management and smart grid design.


  • Digital System Design
  • Signal Processing
  • Control System Design
  • Mathematical Foundations of Machine Learning
  • Machine Learning


  • I. Jendoubi and F. Bouffard, “Multi-agent hierarchical reinforcement learning for energy management,” Applied Energy, vol. 332, p. 120500, 2023. 
  • I. Jendoubi and F. Bouffard, “Data-driven sustainable distributed energy resources’ control based on multi-agent deep reinforcement learning,” Sustainable Energy, Grids and Networks, vol. 32, p. 100919, 2022.
  • I. Jendoubi and F. Bouffard, “Hybrid storage system control for real-time power balancing in a hybrid renewable energy system,” Les Cahiers du GERAD, pp. 1–27, Aug. 2022.
  • I. Jendoubi, K. Sheshyekani, and H. Dagdougui, “Aggregation and optimal management of TCLs for frequency and voltage control of a microgrid, ” IEEE Transactions on Power Delivery, vol. 36, no. 4, pp. 2085–2096, 2021.
  • K. Sheshyekani, I. Jendoubi, M. Teymuri, M. Hamzeh, H. Karimi, and M. Bayat, “Participation of distributed resources and responsive loads to voltage unbalance compensation in islanded microgrids, ” IET Generation, Transmission & Distribution, vol. 13, no. 6, pp. 858–867, 2019.
  • I. Stoyanova, I. Jendoubi, and A. Monti, “Model predictive control for cooperative energy management at city-district level,” in 2018 Power Systems Computation Conference (PSCC), pp. 1–7, 2018.