Javad Shabanpour, PhD

ML Radio Research Scientist at Nokia Bell Labs

Senior Member, IEEE

Also published as Mohammadjavad Shabanpoursheshpoli

Hi, I’m Javad!

I’m an ML Radio Research Scientist at Nokia Bell Labs in Espoo, Finland, exploring how AI can make wireless networks smarter and more energy-efficient. My research brings together neural receivers, spiking neural networks, and digital twins that connect simulations with the real world. I earned my PhD at Aalto University as a Marie Skłodowska-Curie researcher, focusing on AI-driven optimization of wireless networks through data-driven channel modeling and digital twins, building on my background in antennas and electromagnetic engineering. What drives me is turning promising machine-learning ideas into practical improvements in how we communicate.

Selected Research

IterSpikeRx: Learning to Refine Wireless Reception

We explore iterative spiking neural networks that progressively refine wireless signal estimates, aiming to combine reliable detection with efficient computation.

Digital Twins for Intelligent Surface Deployment

Using real-world measurements and calibrated ray tracing, we optimize intelligent surface deployment and assess the trade-off between wireless coverage gains and infrastructure requirements.

Advanced Antenna Design and Experimental Validation

Designed, fabricated, and experimentally verified reflector antenna prototypes with enhanced beamforming efficiency, angular stability, ultra-broadband operation, and dual polarization.