At Politecnico di Torino, I built and evaluated a Python framework for smart-grid negotiation that combines data-driven opponent modeling with confidence-gated LLM support. I assessed learned preferences and negotiation outcomes across simulations.
My research also includes comparing ERFNet and EoMT-DINOv2 for road-scene segmentation across five out-of-distribution benchmarks. Progressive unfreezing improved mIoU from 55.5 to 76.9.
I completed an M.Sc. in Information Technology Engineering – Computer and Communication Networks at Ferdowsi University of Mashhad, where my thesis examined PMU-based fault detection in smart power grids. I also published research on dynamic service function chain placement in mobile edge computing.
In industry, I developed a CNN-based inspection model at Metal Drum Company and maintained ASP-based systems as an IT Support Specialist. I’m currently studying Data Science and Engineering at Politecnico di Torino.
