Thrilled to share insights from my enriching research stay at the University of Ottawa with Professor Hussein Al Osman’s DISCOVER Lab!
As part of the TEAMING project—a Marie Curie Staff Exchange initiative fostering international research mobility—I explored AI-driven solutions to extend EV battery lifespan through intelligent usage prediction and management.
Key achievements:
• Integrated cutting-edge EV datasets and explored different Machine Learning and Deep Learning models for battery optimization
• Co-supervised 6 master’s students on innovative AI applications
• Strengthened partnerships with McMaster University’s critical software and battery experts through several visits
• Initiated PhD collaboration to sustain this trilateral partnership (CEA, University of Ottawa, McMaster University)
The TEAMING framework enabled invaluable knowledge exchange, combining Ottawa’s AI expertise, McMaster’s world-class critical software and battery engineering. Discussions with Professor Al Osman on AI field and beyon, broadened my research perspective.
This Marie Curie exchange demonstrates how international mobility programs catalyze breakthrough innovations in sustainable transportation.

During my recent research stay (almost one year) at the University of Ottawa’s School of Electrical Engineering and Computer Science, I had the privilege of working with Professor Hussein Al Osman and his team in the DISCOVER Lab. This collaboration on extending electric vehicle battery lifespan through artificial intelligence-driven usage prediction and management strategies.
Integrating with a Multidisciplinary Team
From day one, the warm welcome from Professor Al Osman’s group made the integration seamless. The DISCOVER Lab’s expertise in AI applications for multimedia systems provided a unique perspective on our battery management challenges. The interdisciplinary environment, combining computer science, electrical engineering, and human-computer interaction, created fertile ground for innovative approaches to EV battery optimization.
Expanding the Partnership: McMaster University
A particularly enriching aspect of this stay was the opportunity to connect with our Marie Curie TEAMING project partners at McMaster University. During two visits to their state-of-the-art facilities, including the McMaster Automotive Resource Centre with its extensive battery testing capabilities, I was impressed by the teams expertise in critical software, battery systems and automotive electrification. These visits transformed what could have been distant project partnerships into genuine collaborative relationships. Together, we began developing joint research proposals and defining experimental protocols that leverage McMaster’s world-class testing infrastructure alongside our AI-driven optimization strategies.
Building the Foundation: Data and Methods
One of our first challenges involved screening and selecting appropriate open-access datasets for EV usage prediction. We evaluated multiple sources, ultimately focusing on recent datasets from Osonuga et al. (2024), Pozzato et al. (2023), and Deng (2024), which provide comprehensive real-world EV driving patterns, charging behaviors, and battery performance metrics. These datasets offered the diversity needed to develop robust predictive models that could generalize across different driving conditions and user behaviors.
The state-of-the-art review revealed exciting opportunities in combining traditional time-series forecasting with cutting-edge deep learning architectures. We explored various methodologies, from classical XGBoost, to Long Short-Term Memory networks and to Temporal Convolutional Networks. The goal: develop AI algorithms capable of predicting individual EV usage patterns across multiple time horizons—from hourly to seasonal—enabling proactive battery preconditioning and optimal state-of-charge management.
Collaborative Research and Knowledge Exchange
Working with six master’s students on different aspects of the project proved incredibly rewarding. Each student brought unique perspectives, in their exploration of AI methodology to address our problem. Professor Al Osman’s mentorship an environment where innovative ideas flourished.
Our discussions extended beyond technical matters. Professor Al Osman’s insights into the broader implications of our work enriched my understanding of how our research fits into larger global challenges. And also, I will now miss our conversation about economics and geopolitics!
Looking Forward: Sustained Collaboration
The research stay has catalyzed a lasting partnership. We’ve initiated a PhD project to continue this collaborative work, ensuring the momentum built during this exchange continues. This long-term commitment reflects our shared vision: creating AI systems that can extend EV battery lifespan dramatically through intelligent management, while maintaining user satisfaction and comfort.
Disseminating Knowledge
Throughout the stay, I participated in conferences held in Ontario and Quebec covering battery technology, EV systems, and artificial intell

Vincent Heiries

CEA – University of Ottawa