
A 4th year undergrad student of the department of CSE, who is passionate about Machine Learning, Deep Learning, Natural Language Processing, and Generative AI. He has contributed to backend development using gRPC and has been a part of three published research works based on NLP and ML in agriculture

A final year B.tech. student in CSE at IEM, Kolkata. Passionate about Web Development, Machine Learning, NLP and Generative AI with a strong academic record and industry experience. worked on various projects in modern technologies and have multiple published research papers. I'm also an active leader and volunteer, contributing to quiz and training activities

Highly motivated and results-driven B.Tech student at IEM Kolkata with a minor in Artificial Intelligence & Machine Learning. Strong foundation in Java, machine learning algorithms, and data analytics with hands-on project experience in predictive modeling and NLP research. Co-author of a published survey paper and active contributor to the Centre of Excellence in GenAl.

Curious about how AI and data science can solve real-world challenges, especially in domains of healthcare and finance. I love diving into projects where technology meets strategy, and right now, I'm particularly interested in exploring generative models, real-world impact of emerging technologies, and interdisciplinary research that bridges technical innovation with analytical thinking.

I'm deeply interested in Artificial Intelligence and Machine Learning, particularly in explainable AI, natural language processing, and deep learning. My goal is to develop technologies that are both innovative and responsibly applied

My interests lie in Generative AI, data science, and intelligent systems, with a focus on solving real-world problems. I work on projects in healthcare and FinTech, aiming to build innovative, scalable, and human-centric solutions through the integration of machine learning and emerging technologies.

I am passionate about research in Artificial Intelligence and Machine Learning, focusing on algorithmic efficiency, model interpretability, and ethical AI