Sagnik Dakshit

Sagnik Dakshit, Ph.D, ACUE
Assistant Professor

University of Texas at Tyler

Dr. 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.

Dr. Dakshit serves as a reviewer for the Journal of Healthcare Informatics Research, IEEE Transactions on Multimedia, Multimedia Systems (Springer), ACM International Conference on Multimedia Retrieval, NIPS, ICLR, ICHI 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

Explainable AI, Machine Learning, Deep Learning, FAccT ML, Healthcare Informatics

Latest Updates

March 2025: New research paper acceptance at IEEE ICHI 2025.
December 2024: New research paper acceptance at IEEE AIxVR 2025.
November 2024: Nikil Sharan Prabahar Balasubramanian defended his M.S Thesis under my supervision.
November 2024: Keynote at IEEE Metrocon 2024
November 2024: Invited Talk at Baylor University
October 2024: Completed 4 part ACUE certification on Effective Teaching
October 2024: Invited Talk at Texas State University
September 2024: I am excited to serve as co-chair for Healthcare Tech in Medicine, SBEC 2024 and Reviewer for NIPS 2024, ICLR 2025, ICHI 2025.
September 2024: I am excited to serve in the Senior Program Committee for IEEE ICHI 2025.
August 2024: New research paper acceptance at Journal of Biomedical Science Instrumentation.
July 2024: New research paper acceptance at ACM SIGITE 2024.
June 2024: KLTV7 Media Coverage of our work on LLM Self-Diagnosis
June 2024: Honored to be listed in Marquis Who's Who 2024.
June 2024: Student research abstract acceptance at 40th SBEC 2024.
May 2024: New research paper acceptance at International Journal of Advanced Computer Science and Applications.
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.

Media Coverage

WATCH: UT Tyler asst. professor studying use of ‘A.I.’ for medical self-diagnosis“The journey towards reliable AI-assisted self-diagnosis is ongoing, and it is one that must be navigated with both hope and caution.”

ETTIC, UT Tyler encourage AI partnerships with local businessesSmall business leaders learned artificial intelligence is within reach at Friday’s meeting of the East Texas Technology and Innovation Coalition. Sagnik Dakshit, computer science professor at the University of Texas

Presentations and Talks

""Functional Movement (FMOVE) Tele-Screening Application"; Southern Biomedical Engineering Conference; Shreveport, LA September 2024
"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