Explore My Research

Industrial Research

Demystifying Defects: Federated Learning and Explainable AI for Semiconductor Fault Detection

Lead Author

A novel semiconductor fault detection framework that combines Federated Learning and Explainable AI to enable high-accuracy, privacy-preserving, and interpretable defect classification across decentralized datasets

Federated LearningExplaianable AIFault DetectionEdge Intelligence

Undergraduate Thesis

Impact of Digital Transformation on Mental Health of IT Professionals

Principal Investigator

An explainable machine learning framework that predicts technostress and burnout in IT professionals using hybrid survey-synthetic data and SHAP-based insights to support proactive mental health interventions.

Explainable AIStress DetectionDigital TransformationMental Health

Smart Grid and Electric Vehicles

Data-Driven SoC Forecasting in Electric Vehicles: A Federated Learning Perspective

Co-Author

A data-driven State of Charge forecasting framework for Electric Vehicles that leverages Federated Learning and ensemble machine learning to deliver privacy-preserving, accurate, and scalable battery state estimation across decentralized sources

Federated LearningElectric Vehicles (EVs)State of Charge EstimationPrivacy-Preserving ML

Cybersecurity and Smart Infrastructure

Enhancing Cybersecurity in Internet of Vehicles: A Machine Learning Approach with Explainable AI for Real-Time Threat Detection

Lead Author

A machine learning and Explainable AI-based cybersecurity framework for the Internet of Vehicles that enables real-time, interpretable, and high-accuracy threat detection while ensuring model transparency and operational reliability in connected vehicular networks.

CybersecurityInternet of VehiclesMachine LearningPrivacy-Preserving ML