Rubi Debnath

Rubi Debnath is a researcher at the Technische Universität München (TUM) affiliated with the Department of Embedded Systems and Internet of Things. They focus on Time-Sensitive Networking (TSN), Machine Learning for TSN, and Optimization of TSN Scheduling Algorithms using heuristics, ILP, and DRL.

• Specializes in TSN Scheduling, Runtime Reconfiguration, and Wireless-TSN
• Actively teaches IoT Security, Software Architecture for Distributed Embedded Systems, and System Design for IoT since Winter Semester 2018/2019
• Supervised over 15 Master's and Bachelor's theses on TSN, ML, and 5G-TSN integration
• Developed simulation frameworks like CyclicSim and 5GTQ

Research Trends: Recent publications address TSN scheduling optimization, ML-assisted traffic classification, and 5G-TSN integration, with a focus on low-latency communication and industrial automation.

Scientific Awards:

• IEEE ComSoc Four Minute PhD Thesis Competition - Third Prize Winner (Round 2), Round 1 Winner
• Global Fellows Program - Imperial College London, TUM, and NTU Singapore

Advising and Grants: Supervised 15+ theses on TSN, ML, and 5G-TSN. Involved in the 6G Research Hub "6G-Life" and nIoVe cybersecurity framework for IoT.