Sagnik Dakshit

Sagnik Dakshit is an Assistant Professor in the Computer Science Department at the University of Texas at Tyler. He holds a Ph.D. in Computer Science from the University of Texas at Dallas and a B.Tech in Computer Science and Engineering from West Bengal University of Technology (India). His research focuses on Machine Learning, Artificial Intelligence, and Healthcare Informatics, with a particular emphasis on Explainable AI systems and their applications in improving quality of life.

Dr. Dakshit’s work has been supported by collaborations with industry partners such as Robert Bosch, Seagate Technologies, HP Machine Learning Labs, and Nokia Bell Labs, as well as prior experience in software development at IBM and Tata Technologies. His teaching philosophy emphasizes hands-on project-based learning in Machine Learning, AI, and Healthcare Informatics.

His research trends span healthcare time series analysis, ECG classification frameworks, and AI ethics in medical applications. Notable contributions include work on explainable CNN models for ECG signals, VR-based attention measurement systems, and bias analysis in healthcare decision support systems.

Dr. Dakshit has been actively involved in academic-industrial projects, including the SSBC 2020 sclera segmentation benchmarking competition. His publications reflect a blend of theoretical advancements and practical clinical applications.