Gourav Gupta

About

I am Gourav Gupta from India having around 6 years of hands-on experience on Big Data, Artificial Intelligence, HCI, Deep Learning, Computer Vision, IoT, and Digital Twin.

I was as associated with PeopleStrong Private Limited as a Data Specialist (Big Data & Artificial Intelligence). Currently, I am associated as a Chief Analytical Advisor at ArogyaPandit.AI (arogyapandit.com) startup.
Moreover, I am a part of reviewer panel in the Journal of Big Data i.e. Springer Publication. I have published research papers in Big Data Technology and published several articles on medium and Linked in. I have done several certifications on Big Data Technology from IEEE, Amazon, and etc. I had given several talks on Advanced Analytics and Intelligence.

Currently, I am working on distributed Deep learning using Elephas framework on various Computer Vision and Analytics applications. Also, I am co-author of one AI book "Practical Machine Learning with Apache Spark".

Employment

• Peoplestrong Technology Private Limited Data Specialist
  2019 - 2022
• Q3 Technologies Data Engineer L3
  2018 - 2019
• Altruist Technology Big Data Analyst
  2017 - 2018

Education

• Technological Institute of Textile and Science Bachelor of Technology
  2012 - 2016

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• An AI-Enabled Predictive Harm Response Management Algorithmic Tool to Reduce Adverse Events in Health Care Settings (PreHaRM): Protocol for a Three-Phase Model Development and Pilot-Testing Study
  JMIR Research Protocols 2026 DOI: 10.2196/75474
  +Save
• VarDiff: A Conceptual Model for Representing Variable Differences Between Clinical Decision Support Systems
  Applied Sciences 2026 DOI: 10.3390/app16073331
  +Save
• Clinical Decision Support Systems Redeployment – Levels of Matching Between Variables in Different Ecosystems
  2025 DOI: 10.3233/SHTI251136
  +Save
• An AI-Enabled Predictive Harm Response Management Algorithmic Tool to Reduce Adverse Events in Health Care Settings (PreHaRM): Protocol for a Three-Phase Model Development and Pilot-Testing Study (Preprint)
  2025 DOI: 10.2196/preprints.75474
  +Save
• Adaptive Semantic Framework for CDSS to a new environment
  2024 DOI: 10.1145/3641142.3641159
  +Save
• Practical Machine Learning with Apache Spark
  BPB Publications 2022
  +Save
• Exploring Bias in Sclera Segmentation Models: A Group Evaluation Approach
  IEEE Transactions on Information Forensics and Security 2022 DOI: 10.1109/TIFS.2022.3216468
  +Save
• Towards generalized morphing attack detection by learning residuals
  Image and Vision Computing 2022 DOI: https://doi.org/10.1016/j.imavis.2022.104535
  +Save
• NIR Iris Challenge Evaluation in Non-cooperative Environments: Segmentation and Localization
  2021 IEEE International Joint Conference on Biometrics (IJCB) 2021 DOI: 10.1109/IJCB52358.2021.9484336
  +Save
• SSBC 2020: Sclera Segmentation Benchmarking Competition in the Mobile Environment
  2020 IEEE International Joint Conference on Biometrics (IJCB) 2020 DOI: 10.1109/IJCB48548.2020.9304881
  +Save