I am an Engineer, Research Scholar, and AI Enthusiast with nearly five years of experience working at the intersection of Artificial Intelligence, Machine Learning, and Deep Learning, with a special interest in Explainable AI. My work focuses on turning complex algorithms into practical solutions, particularly in healthcare and agriculture. Over the years, I’ve developed predictive models, contributed to impactful projects, and published research in well-regarded Q1 and Q2 journals. As a Computer Science and Engineering graduate, I bring a strong technical foundation and a proven track record of impactful research, academic collaboration, and peer-reviewed publications. My projects span a wide range from medical imaging for COVID-19, Pneumonia, and Alzheimer’s detection to building AI-powered agricultural tools and intuitive software applications, reflecting my versatility and drive to apply AI in ways that matter. Technically, I’m skilled in Python, TensorFlow, Keras, and PyTorch, with strong expertise in data preprocessing, model evaluation, and research writing. Some of my proudest contributions include developing explainable models for lung disease detection, curating datasets for deep learning research, and co-authoring multiple international publications. Outside of research, I enjoy mentoring undergraduate students, reviewing manuscripts, and sharing knowledge through workshops, presentations, and conferences. Along the way, I’ve been recognized with scholarly publication awards and have completed 40+ certifications that fuel my curiosity and commitment to lifelong learning.