معرفی
Kyle Madden serves as a Research Fellow at Ulster University within the School of Computing, Engineering and Intelligent Systems at the Derry~Londonderry campus. His work bridges theoretical computer science with industrial applications, focusing on intelligent systems development for manufacturing and IoT environments.
Education:
- PhD in Computer Science (awarded June 2025) from Ulster University with thesis: “Spiking neural networks for detecting denial-of-service attacks in networks-on-chip” supervised by Dr. Jim Harkin and Dr. Liam Mc Daid.
Dr. Madden’s research spans cutting-edge domains in neuromorphic engineering and industrial IoT. He pioneers frameworks for translating spiking neural networks to FPGA hardware while optimizing power efficiency, develops cloud-based IoT systems for industrial decision-making, and applies computational intelligence to 3D printing quality control. His work integrates user experience considerations in smart manufacturing interfaces and advances event-based sensor data processing through neuromorphic event alarm systems.
Recent publications (2024-2025) reveal strong thematic focus on deploying AI solutions in real-world industrial contexts. Key trends include hardware acceleration of neural networks for manufacturing, cloud-IoT integration using AWS infrastructure, and human-centered design for industrial IoT applications. His research consistently addresses practical implementation challenges in sensor data processing and neural network deployment.
Scientific Awards:
- No awards documented in available information
Dr. Madden has no listed advisees in the provided materials. His research outputs indicate collaborative project involvement, particularly in EU-funded industrial IoT initiatives and neuromorphic computing consortia, though specific grant details aren’t disclosed. Current work appears integrated within Ulster University’s Computer Science research group focusing on intelligent systems.
He actively contributes to research teams developing neuromorphic event-based processing systems and industrial IoT frameworks. Recent work on FrostRune demonstrates leadership in creating asymmetric translational pipelines from high-level neural models to FPGA deployment, positioning him within hardware-aware AI research communities.
