I partner with universities and industry on efficient, deployment-ready AI — model compression for resource-constrained environments and edge deployment with TinyML, applied to smart buildings, agriculture, and healthcare.

• University of Cambridge, UK — Deep learning for AI healthcare
• University College Dublin, Ireland — Tiny transformers for smart healthcare forecasting
• University of Queensland, Australia — Hybrid deep learning for AI healthcare
• Huzhou University, China — Applied ML/DL, sentiment analysis, fraud detection
• Hamad Bin Khalifa University, Qatar — Applied DL in security
• University of Rome "Roma Tre", Italy — Applied DL across domains
• University of Calabria, Italy — Smart environments & digital twins
• ICAR-CNR, Italy — TinyML for sensor streams and edge deployability
• North South University, Bangladesh — DL for disease classification
• RUET, Bangladesh — Fault detection & classification via ML/DL

Collaborations bridging research and real-world impact — efficient transformers, forecasting, and edge AI, especially projects with measurable deployment outcomes and transparent evaluation.