April 29, 2025 | Dubai, United Arab Emirates
eBRAINers, a quantum research team based at New York University Abu Dhabi, has been named one of the winning teams of the QInnovision World Challenge 2025. Their award-winning project, Quantum-Assisted Path Planning and Optimization for UAV Navigation with Obstacle Avoidance, responds directly to an advanced aerospace challenge posed by Thales, focused on the future of drone path planning in increasingly crowded urban airspaces.
Thales, a global leader in aerospace, defense, and security technologies, launched the challenge to explore how quantum computing could be used to address the computational complexity of real-time unmanned aerial vehicle (UAV) navigation. As cities prepare for the rise of autonomous aerial systems, the need to compute safe, efficient flight paths through dense, obstacle-rich environments has become a key technical priority for the sector. Thales invited participants to develop quantum-native approaches capable of meeting strict safety, timing, and scalability requirements that conventional algorithms cannot satisfy.
The eBRAINers team responded by designing a quantum optimization framework built on the Quantum Approximate Optimization Algorithm (QAOA). Their system transforms geospatial flight constraints into a graph-based quantum model that evaluates optimal routes while avoiding obstacles and no-fly zones. The method was successfully implemented and tested on IBM quantum hardware, confirming its viability on real quantum processors and demonstrating promising performance at scale.
“Working on the Thales use case allowed us to apply quantum tools to an urgent, operationally grounded aerospace problem,” the team stated. “We focused on building a solution that anticipates the demands of next-generation drone traffic systems while exploring the practical limits of current quantum technologies.”
The challenge was part of the QInnovision World Challenge 2025, hosted during the Quantum Innovation Summit in Dubai. It was organized by Vernewell Group and powered by Aqora, a platform supporting real-world quantum innovation. The Thales problem statement was one of several industry-authored challenges aimed at accelerating applied quantum research through competitive prototyping. Finalist teams were invited to present at the summit and participate in the Quantum Futures Forum, engaging directly with leaders from industry, academia, and policy.
The eBRAINers team includes Dr. Nouhaila Innan, Dr. Muhammad Kashif, Dr. Alberto Marchisio, and Prof. Dr. Muhammad Shafique. Their joint research spans quantum computing, AI, optimization, and aerospace systems, operating under the eBRAIN Lab and the Center for Quantum and Topological Systems (CQTS) at NYU Abu Dhabi. The Abu Dhabi-based team emphasized that their goal is not only academic but focused on building deployable quantum solutions for mission-critical systems.
A panel of expert judges from quantum research, defense, and aerospace technology evaluated submissions based on scientific merit, technical execution, and real-world relevance. The eBRAINers project was recognized for its strong algorithmic foundation, effective hardware implementation, and alignment with the strategic needs of aerospace traffic management.
What’s Next
The team is continuing to develop the framework for autonomous drone fleet coordination in urban environments, integrating AI for adaptive control and expanding the quantum-classical co-processing stack. Their work reflects the broader transition toward operational quantum computing in high-stakes industrial domains.
We are a team of researchers working together within the same lab eBRAIN, engineering division, and affiliated with the Center for Topological and Quantum Systems (CQTS) at New York University Abu Dhabi (NYUAD), representing Morocco, Pakistan, and Italy. Building on our ongoing collaboration, we combined our expertise in quantum computing, AI, and aeronautics to develop a quantum-assisted UAV path planning framework tested on real quantum hardware. Our goal is to continue extending our joint research, exploring how quantum technologies can solve real-world challenges in aerospace and beyond, and collaborating with Thales to contribute more efficient algorithms tailored to their specific use cases.
Team Members:
Dr Nouhaila Innan (Research Team Lead at eBRAIN lab, Postdoctoral Associate at CQTS, NYU Abu Dhabi), LinkedIn
Dr Muhammad Kashif (Research Team Lead at eBRAIN lab, Postdoctoral Associate at CQTS, NYU Abu Dhabi), LinkedIn
Dr. Alberto Marchisio (Research Team Lead at eBRAIN lab, Postdoctoral Associate at CQTS, NYU Abu Dhabi), LinkedIn
Prof. Dr. Muhammad Shafique (Director of eBRAIN Lab and iCAS Lab, Professor at NYU Abu Dhabi; Global Network Professor at Tandon School of Engineering, NYU, USA), LinkedIn
About eBRAINers
A team of researchers working together within the same lab eBRAIN, engineering division, and affiliated with the Center for Topological and Quantum Systems (CQTS) at New York University Abu Dhabi (NYUAD), representing Morocco, Pakistan, and Italy. Building on our ongoing collaboration, we combined our expertise in quantum computing, AI, and aeronautics to develop a quantum-assisted UAV path planning framework tested on real quantum hardware. Our goal is to continue extending our joint research, exploring how quantum technologies can solve real-world challenges in aerospace and beyond, and collaborating with Thales to contribute more efficient algorithms tailored to their specific use cases.
Team Members
Dr Nouhaila Innan (Research Team Lead at eBRAIN lab, Postdoctoral Associate at CQTS, NYU Abu Dhabi), LinkedIn
She holds a bachelor’s degree in physics and applications and a Master’s in Physics and New Technologies from Hassan II University of Casablanca, Morocco. She defended her PhD in Quantum Machine Learning at the same university in July 2024. Currently, she is a Research Team Lead at eBRAIN Lab and a Postdoctoral Associate at the Center for Quantum and Topological Systems (CQTS) at NYU Abu Dhabi. Her research focuses on Quantum Machine Learning, quantum algorithms, and real-world applications. Innan is also committed to mentoring and advancing the accessibility of quantum technologies through local and international initiatives.
Dr Muhammad Kashif (Research Team Lead at eBRAIN lab, Postdoctoral Associate at CQTS, NYU Abu Dhabi), LinkedIn
He began his academic journey with a bachelor’s degree in electrical (Electronics) Engineering from COMSATS Institute of Information Technology, Pakistan, in 2015. He earned his MSc in Electronics and Computer Engineering from Istanbul Sehir University, Turkey, in 2020, and completed his PhD at Hamad Bin Khalifa University, Qatar, in 2023, focusing on quantum advantages and trainability challenges in Quantum Neural Networks during the NISQ era. Currently, Kashif is a Research Team Lead at eBRAIN Lab, Division of Engineering, and a Postdoctoral Associate at the Center for Quantum and Topological Systems (CQTS) at NYU Abu Dhabi. His research focuses on Quantum Machine Learning and its intersections with classical machine learning.
Dr. Alberto Marchisio (Research Team Lead at eBRAIN lab, Postdoctoral Associate at CQTS, NYU Abu Dhabi), LinkedIn
He received his B.Sc. and M.Sc. degrees in Electronic Engineering from Politecnico di Torino, Italy, and his Ph.D. degree in Computer Science from TU Wien, Austria. Currently, he is a Team Lead at the eBRAIN Lab, NYU Abu Dhabi. His research interests include hardware and software optimizations for QML, quantum fintech., EdgeAI, GenAI, and neuromorphic computing. He co-authored 40+ papers and received several excellence awards.
Prof. Dr. Muhammad Shafique (Director of eBRAIN Lab and iCAS Lab, Professor at NYU Abu Dhabi; Global Network Professor at Tandon School of Engineering, NYU, USA), LinkedIn
He received his Ph.D. degree in computer science from KIT, Germany, in 2011. From Oct.2016 to Aug.2020, he was a Full Professor at TU Wien, Austria. Since Sep.2020, he is with NYU, where he is currently a Full Professor of Electrical and Computer Engineering, and Director of eBRAIN Lab and iCAS Lab at NYU Abu Dhabi, and a Global Network Professor at the NYU-Tandon School of Engineering, USA. His research interests are in QC, QML, AI/ML system design and optimization, AI4Healthcare, autonomous systems, energy efficient and robust computing. Dr. Shafique has given several keynotes, invited talks/tutorials, and organized special sessions at premier venues. He has served as PC-Chair, General-Chair, Track-Chair, and PC-member for several conferences. He received the 2015-ACM/SIGDA Outstanding New Faculty Award, multiple AI-2000 Chip Technology Most Influential Scholar Awards, and several best-paper awards/nominations. Dr. Shafique has 400+ publications, 7 books, and 20+ book chapters.
