Sujit Roy

Lead Ai Researcher @NASA - National Aeronautics and Space Administration

Huntsville, AL, US
EMAILS
s••••••••@nasa.gov
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Jul 2022 — Present

Lead Ai Researcher @NASA - National Aeronautics and Space Administration

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Huntsville, AL, US

EDUCATION

2017 — 2021

Ulster University

Doctor of Philosophy - PhD, Computer Science (Computational Neuroscience)

N/A

Indian Institute of Technology, Kanpur

Doctor of Philosophy - PhD, Computer Science

SKILLS

Business IntelligenceBiomedical EngineeringTeam ManagementAlgorithmsMobile ApplicationsTeam BuildingTeam LeadershipSoftware EngineeringC#XamlBusiness StrategySoftware DevelopmentPythonAlgorithm DesignC++QuizmakerJavaCoding LanguagesAlgorithm DevelopmentLanguage TeachingCProgrammingBrain Computer InterfaceVisual StudioData StructuresTechnical PresentationsResearch

ABOUT SUJIT ROY

Dr. Sujit Roy is a Lead AI Researcher for IMPACT’s AI4Science team at NASA’s Marshall Space Flight Center (MSFC), Office of Data Science and Informatics. He leads the development of foundation models for NASA’s Science Mission Directorate; currently focusing on heliophysics and planetary science. Prior to his tenure at NASA IMPACT, Dr. Roy contributed to the field of Explainable AI at the University of Manchester. He received his PhD (UKIERI fellowship) in Computer Science from Ulster University in collaboration with the Indian Institute of Technology Kanpur, India. In his PhD, he contributed to the domain of Computational Neuroscience by developing algorithms for Advancing MEG- and EEG-Based Decoding of Motor Imagery for Practical Brain-Computer Interfaces. He has experience of 10 years in Research and Development in the field of machine learning and deep learning. He is also a Co-founder of BrainAlive Research Pvt Ltd. His professional repertoire spans deep learning, brain-computer interfaces, and image processing. Dr. Roy is particularly focused on advancing computer vision, explainable artificial intelligence, signal processing/synthesis, and reinforcement learning. Primary research interest areas include Generative Modelling, Computer Vision, Explainable AI, and reinforcement learning.

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