Bhusan Chettri

Dr Bhusan Chettri is an AI researcher working on machine learning and AI for sound and speech with a strong focus on explainable AI (understanding how a model forms its decision). Dr Chettri is activally looking for new opportunities to learn and invest in the sector of Artificial Intelligence and Ambient intelligence for Voice. Bhusan Chettri(Member, IEEE) received the M.Sc. degree in speech and language processing from the University of Sheffield in 2014. Then he worked as a Research Assistant with the Speech and Hearing Research group, Sheffield University for two years. He earned his undergraduate and post-graduate degrees in Computer Science from Sikkim Manipal University, India in 2005 and 2008 respectively. Before moving to Sheffield for MSc degree he also earned an MBA degree in Computer Systems from SMUDE, India. He received the Ph.D. degree in Electronic Engineering from Queen Mary University of London (QMUL) in 2020. During May to October 2019, he was a visiting researcher with the Computational Speech research group, University of Eastern Finland to work on Voice Anti-Spoofing project (NOTCH) with Professor Tomi Kinnunen. While doing his PhD at QMUL he served as a lab demonstrator during his first year and later got opportunity to teach Data Analytics to the MSc students as a part-time Lecturer. After his PhD completion he became a full time Lecturer in Data Analytics with the School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL), U.K. Between May to December 2020, he worked as a Postdoctoral Researcher on the speaker anti-spoofing NOTCH project. His main research focuses on machine learning and its applications to speaker recognition, spoofing and countermeasures for robust speaker recognition. He is also interested in opening black-boxes towards understanding how a model forms a particular decision. Interpretable machine learning, explainable machine learning, understanding biases in training data and how they influence predictions – are his current research interests.

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