Mudassir Shabbir

Information Technology University, Vanderbilt University

Papers

Total Citations

H-Index

About

Mudassir Shabbir is a researcher whose work bridges the critical domains of multi-robot systems and speech emotion recognition (SER), with a particular focus on under-resourced languages. His most cited work, "Resilient Distributed Diffusion for Multi-Robot Systems Using Centerpoint" (2020, 17 citations), addresses the challenge of cooperative task execution in robotic networks. By introducing a resilient diffusion algorithm, Shabbir enables robots to optimize a global cost function even when some agents are compromised, a fundamental contribution to the robustness of distributed systems. In parallel, Shabbir has pioneered SER for the Urdu language, a field with scarce resources. His paper "Speech emotion recognition for the Urdu language" (2022, 16 citations) and the creation of SEMOUR: A Scripted Emotional Speech Repository for Urdu (2021, 11 citations) represent landmark achievements. SEMOUR is the first scripted emotional speech dataset for Urdu, providing a vital foundation for training reliable SER systems. This dual-track impact—advancing both resilient robotics and multilingual affective computing—highlights Shabbir’s versatility and his significant role in making technology more inclusive and robust.