I am an Artificial Intelligence and Machine Learning graduate with hands-on experience in machine learning, data analysis, deep learning, and AI-powered web application development. I am focused on building practical, scalable solutions that address real-world business and operational challenges.
I have developed AI-driven projects involving battery failure prediction, service analytics, waste classification, and medical image classification. My work includes applying machine learning, convolutional neural networks, transfer learning, computer vision, and data visualization techniques.
I have experience building full-stack AI applications using Python, Flask, React, Firebase, SQL, and modern frontend technologies. I have integrated React-based chat interfaces with RAG backends, implemented authentication, and created persistent user-specific chat management features.
I am proficient in Python, SQL, TensorFlow, Keras, Scikit-learn, NumPy, Pandas, Matplotlib, and Seaborn. I also work with web technologies including React, Django, HTML, CSS, JavaScript, and Flask.
Through internships and technical programs, I have gained exposure to real-time datasets, supervised learning, preprocessing, model evaluation, prompt engineering, generative AI, and collaborative software delivery. I am actively seeking an opportunity where I can apply my AI, machine learning, and problem-solving skills to develop impactful solutions.
I developed a React-based chat interface for the TN Colleges RAG system using React, Vite, and Tailwind CSS. I integrated the frontend with a RAG backend to present AI-generated responses and source references.
I implemented Google authentication and persistent user-specific chat history with Supabase. I also built chat management capabilities including search, rename, delete, pin, response regeneration, and active-chat restoration.
I contributed to technical enhancements and feature improvements for web-based applications. I supported the implementation of AI-driven solutions intended to improve business workflows and operational efficiency.
I collaborated with cross-functional teams to deliver AI-driven web solutions. This role strengthened my experience in applying AI concepts within practical web application environments.
I gained practical exposure to machine learning workflows and real-time datasets during my internship. I developed familiarity with the process of working with data for machine learning applications.
The internship provided hands-on learning experience in artificial intelligence and machine learning concepts in an industry-oriented setting.
I learned supervised learning, data preprocessing, and model evaluation techniques. I gained foundational practical experience in core machine learning workflows.
This internship strengthened my understanding of preparing data, training models, and evaluating machine learning performance.
I gained hands-on experience with prompt engineering, ChatGPT, and generative AI concepts. I explored how generative AI can be used within practical technical workflows.
I implemented machine learning models using Python in the Google Colab environment. This experience expanded my familiarity with cloud-based notebook development and AI experimentation.
Bachelor of Technology, Artificial Intelligence and Machine Learning
CGPA: 8.45/10.
Class XII (Senior Secondary), BIEAP
Class X, CBSE
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