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Dr. Tamal Ghosh

Associate Professor | Educator | Researcher | NAAC Consultant | Counsilor

Department of Computer Science & Engineering

School of Engineering and Technology

Adamas University

Email: tamal.ghosh1@adamasuniversity.ac.in

Profile Picture

Research

Research Interests:

  • Artificial Intelligence
  • Evolutionary Computing
  • Surrogate-Assisted Optimization
  • Collaborative Machine Learning and Deep Learning
  • Industry 4.0
  • Digital Twin
  • I am actively seeking PhD or PG students who is looking to do cutting-edge research in the above areas.

    Research Scholars:

  • Mr. Kamal Paul (PhD Scholar), Adamas University, Topic: Optimal Prompt Engineering
  • Mr. Abhisek Chakraborty, (PhD Scholar), Adamas University, Topic: Multi-Objective RL Algorithm
  • Mr. Arpan Maity, (M.Tech Scholar), Adamas University, Topic: Object Detection using Modified CNN
  • Working Papers:

  • D Bhattacharjee; T Ghosh; PK DAN. Time Utilization Patter Based Cellular Manufacturing Strategy for Small Manufacturing Unit, OPSEARCH Journal.
  • T Ghosh; D Bhattacharjee. A Digital Twin-driven Near-Zero-Error Healthcare System for Enhanced Patient Safety and Services, SMART HEALTH Journal.
  • A Maity; T Ghosh. Hybrid AI Model Combining K-Means++ and YOLOv5 for Surface Anomaly Detection. IAENG International Journal of Computer Science.
  • T Ghosh. Data-Driven Optical Quality Inspection and Optimization within Automated Manufacturing Processes, Intelligent Decision Technologies Journal.
  • A Maity, T Ghosh, PK Dan. Interpretable Hybrid Feature Fusion with PSO-XGBoost for Metal Defect Classification, International Journal of Knowledge-Based and Intelligent Engineering Systems.
  • K Paul; A Basu; T Ghosh; S Saha. Improved Prompt Generation Framework using Gemma-3 based Context-Aware Language Models, IEEE SISIMPACT2025.
  • A Maity, T Ghosh. Hybrid Deep Learning Framework for Enhanced Diabetic Retinopathy Detection: Integrating Traditional Features with AI-driven Insights. Springer SSWC 2025. Kalyani.
  • A Maity, T Ghosh, T Ghosh. Nail Disease Diagnosis Using a CNN-Transformer Hybrid Architecture, ICCTE-NBU 2025, Springer.