Debashis Gupta
Scholar

Debashis Gupta

Google Scholar ID: T0EMKBoAAAAJ
Graduate Student, Wake Forest University, NC, USA
Biomedical EngineeringRemote SensingMachine LearningComputer VisionSecurity Threats
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
155
 
H-index
4
 
i10-index
3
 
Publications
11
 
Co-authors
0
 
Contact
Emaildebashisguptaruet@gmail.comCVOpen ↗GitHubOpen ↗LinkedInOpen ↗
Publications
3 items
Interpretable Failure Analysis in Multi-Agent Reinforcement Learning Systems
2026
Cited
0
MoSAiC: Multi-Modal Multi-Label Supervision-Aware Contrastive Learning for Remote Sensing
2025
Cited
0
Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Exploration
2025
Cited
0
Resume
Academic Achievements
  • - Journal Publication: 'Vulnerability in deep transfer learning models to adversarial fast gradient sign attack for covid-19 prediction from chest radiography images', Applied Sciences, 11(9), 2021, Citations: 70
  • - Conference Publication: 'CervixMed: Detecting Cervical Cancer based on combinational data using Hybrid architecture', 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
  • - Conference Publication: 'Security threats on Data-Driven Approaches for Luggage Screening', Proc. 2024 IEEE 14th Annual Computing and Communication Workshop (CCWC)
  • - Conference Publication: 'Classification of Tumor Cell Using a Naive Convolutional Neural Network Model', Proc. of the International Conference on Machine Intelligence and Emerging Technologies, 2022, Springer
  • - Conference Publication: 'Vulnerability Analysis and Robust Training with Additive Noise for FGSM attack on Transfer Learning based Brain Tumor Detection from MRI', Data Engineering and Communication Technology, Springer, 2021
Research Experience
  • - Currently a lecturer at Bangladesh Army University of Science and Technology, Saidpur (BAUST)
  • - Conducted research under the supervision of Biprodip Pal, Assistant Professor, for almost one and a half years
Education
  • - M.Sc in Computer Science, Wake Forest University, Result: 3.945/4.00
  • - B.Sc in Engineering, Computer Science and Engineering, Rajshahi University of Engineering and Technology, Result: 3.63/4.00, Departmental Position: 4/120
  • - Dissertation Title: Vulnerability analysis of Deep Learning models to Fast Gradient Sign Attack for Chest radiography images, Advisor: Biprodip Pal, Assistant Professor
Background
  • Research interests include Generative Adversarial Network, Adversarial Attack, Optimization of Machine Learning Algorithm, Cyber Security, and Data Mining. Enjoys theoretical research but mostly focuses on real-life problems and solutions.
Miscellany
  • Loves to travel and adventure