We are pleased to announce that a new paper from LINCS Lab has been accepted for publication in IEEE Internet of Things Magazine.
The paper, titled “Securing the Future of IoMT in the Post-Quantum Era: An Edge-Native Federated Learning Approach,” is authored by Taym Alshoghri, Deemah H. Tashman, Mohammad Reza Gerami, and Prof. Soumaya Cherkaoui.
New accepted paper in IEEE Internet of Things Magazine Read More »
LINCS Lab is proud to announce its strong presence at the IEEE International Conference on Communications (ICC) 2026, held in Glasgow, Scotland, with six research papers accepted at this major international conference in communications and networking.
IEEE ICC is one of the flagship international conferences of the IEEE Communications Society, bringing together researchers, academics, and industry professionals from around the world to exchange the latest advances in communications technologies.
LINCS Lab at ICC 2026 in Glasgow with Six Research Papers! Read More »
LINCS Lab is pleased to announce that two papers from the lab have been accepted at the 22nd International Wireless Communications & Mobile Computing Conference (IWCMC 2026). The papers address key challenges in next-generation wireless systems, including RIS-assisted 6G IoT resource allocation in the FR3 spectrum and adversarial robustness in AI-driven RAN slicing.
LINCS Lab to Present Two Papers at IEEE IWCMC 2026 Read More »
We are pleased to announce that our paper, “Learning Gaussian Processes with Randomized Quantum Local Kernels,” has been published in International Conference on Quantum Communications, Networking, and Computing (QCNC 2026).
We are pleased to announce that our Lincs Lab member Wissal Hamhoum, a PhD student at Polytechnique Montréal, has successfully passed her PhD Comprehensive Exam. The examination committee composed of …
Congratulations to Wissal Hamhoum on Successfully Passing the PhD Comprehensive Exam Read More »
On April 17, 2026, Lincs lab hosted a workshop titled “Advances in Quantum Machine Learning for Network Anomaly Detection and Time-Series Forecasting” at Polytechnique Montréal, with both onsite and online participats from 13 universities and to industry professionals across various companies.
Reflections on our Quantum ML Workshop Read More »
We are pleased to announce that our paper, “Trustworthy AI-Driven Dynamic Hybrid RIS: Joint Optimization and Reward Poisoning-Resilient Control in Cognitive MISO Networks,” has been published in IEEE Transactions on Network and Service Management.
New Publication in IEEE Transactions on Network and Service Management Read More »
O-RAN is fundamentally data-driven. Its intelligent control loops—enabled by its Near-Real-Time and Non-Real-Time RAN Intelligent Controllers (RICs)— support continuous monitoring, closed-loop control, and policy-driven optimization. These capabilities create a natural foundation for machine learning, allowing networks to learn from data, adapt to dynamic conditions, and make informed decisions in real time.
Making Open RAN Intelligent: The Role of Machine Learning Read More »
We are pleased to announce that our paper, “ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunities,” has been accepted for publication in IEEE Communications Surveys & Tutorials (Early Access).
New Paper Published in IEEE Communications Surveys & Tutorials Read More »
As wireless networks evolve toward the 6G era, they face growing challenges in managing the immense number of connected devices while maintaining energy efficiency and spectrum utilization. In a recent IEEE IWCMC 2025 publication, “Quantum-Aided Active User Detection for Energy-Efficient CD-NOMA in Cognitive Radio Networks,” Deemah H. Tashman and Prof. Soumaya Cherkaoui propose a quantum-enhanced approach for detecting active users in Cognitive Radio Networks – a key step in optimizing communication and reducing interference.
