Sagnik Dakshit, Ph.D
Assistant Professor
Assistant Professor
University of Texas at Tyler
Sagnik Dakshit as an Assistant Professor in the Computer Science department at The University of Texas at Tyler. His research focuses my on Explainable and Human-allied AI systems in Healthcare. He has been working on developing tools, algorithms and methods for addressing the predominant challenges for the efficient development of deployable decision support systems. His research targets improvement in health, wellbeing and patient outcomes using (1) Physiological multi-modal time-series signals, (2) Healthcare 2D and 3D Vision, (3) Human Centered Computing technologies.
He obtained his Ph.D. in Computer Sciences from The University of Texas at Dallas , USA, specializing on Intelligent Systems and B.Tech from WBUT, India. During his Ph.D., he has worked on various research projects with Robert Bosch, Seagate Technologies, HP Machine Learning Lab, Nokia Bell Labs. Prior to his Ph.D he has worked on software development projects with IBM, and Tata Technologies.
Sagnik serves as a reviewer for the Journal of Healthcare Informatics Research, IEEE Transactions on Multimedia, Multimedia Systems (Springer), ACM International Conference on Multimedia Retrieval, and ACM Information Hiding and Multimedia Security. He was part of the Program Committee for the International Conference on Healthcare Informatics 2020 Special Session on COVID-19.
Research Interests
Machine Learning
Deep Learning
FAccT ML
Healthcare Informatics
Mixed Reality
Latest Updates
April 2024: New research paper acceptance at International Conference on Healthcare Informatics 2024.
April 2024: New research paper acceptance at Artificial Intelligence in Medicine Conference 2024.
August 2023: I have joined University of Texas at Tyler as an Assistant Professor.
Presentations and Talks
"Abstaining ECG Classifiers Through Explainable Prototypical Spaces"; IEEE International Conference on Healthcare Informatics; FL June 2024
"Investigation Of Augmentation Methods For Deep Learning ECG Classification"; International Conference on Artificial Intelligence in Medicine, Utah July 2024
“CVAE-based Generator for Variable Length Synthetic ECG”, International Conference on Healthcare Informatics; TX, USA, 2023
“Twelve Lead Double Stacked Generalization for ECG Classification”, International Conference on Healthcare Informatics; TX, USA, 2023
“Core-set Selection Using Metrics-based Explanations (CSUME) for multiclass ECG”, International Conference on Healthcare Informatics; MN, USA, 2022
Keynote on “Improving Healthcare Time-Series Deep Learning Models” at Current Research in Engineering and Technology (ICCRET-2021), Kolkata, India, Nov 2021.
The Present and Future of ML & AI at Calcutta Institute of Engineering and Management, 2021.
STEM Mentoring Career Panel – ” How I ended up in Technology, why I am passionate about it, and how it impacts our lives.” Thomas Elementary School, Plano, TX, 2019
A peek into the world of Artificial Intelligence organized by STEM Professional Series (My Passion for Science). Microsoft Theatre, 2020, Stonebriar Mall, Frisco.
Invited Guest Mentor for Final Year Engineering Projects at Calcutta Institute of Engineering and Management, 2021
Work Experience
Assistant Professor Fall 2023
Research/Teaching Assistant 2018-2023
Deep learning Research Intern Summer 2023
Machine Learning Research Intern Summer 2022
Machine Learning Research Intern Summer 2021
Aug. Human Sensing Research Intern Summer 2020
Software Development Intern Winter 2017
Software Development Intern Summer 2016