Final-year CSE student specializing in AI & Edge Computing, with hands-on experience in machine learning, deep learning, NLP, GenAI, and agent-based systems. I design and build end-to-end ML pipelines, multi-agent workflows, and RAG applications, with a strong focus on creating scalable, real-world AI solutions for cloud and edge environments.
I’m a final-year B.Tech CSE student at MIT ADT University, Pune, specializing in AI and Edge Computing. I have hands-on experience in machine learning, deep learning, NLP, GenAI, and building intelligent systems that work in real-world environments.
My journey in technology is driven by a passion for creating practical AI solutions—from end-to-end ML pipelines and multi-agent workflows to RAG applications and cloud/edge deployments. I enjoy designing systems that combine strong engineering with scalable AI models, turning complex ideas into working applications.
I continuously explore the latest advancements in AI, GenAI frameworks, and agentic architectures. Beyond academics, I thrive in collaborative environments, contribute to tech communities, and enjoy sharing knowledge that helps others grow and innovate.
Center for Advanced Modeling of Materials & Manufacturing Processes (CAMMP)
Developed a Conditional GAN pipeline for ferritic steel microstructure generation using PyTorch, achieving a significant improvement in FID score (~120 → 45–55). Built reproducible preprocessing workflows, CUDA-optimized training scripts, and automated synthetic image generation pipelines. Enhanced dataset consistency by ~40% and boosted validation throughput by 30%.
The Developers Arena
Participated in a 6-month internship focused on real-world data science projects, training modules, and performance evaluations. Gained hands-on experience in data analysis and model development under professional mentorship.
EduSkills Foundation (Altair-supported)
Completed industry-backed training on end-to-end data science workflows, including data collection, cleaning, exploratory analysis, and visualization using Python. Strengthened practical understanding of core data science methods and improved ability to communicate insights through structured visual storytelling.
MIT Art, Design & Technology University
Graduating with honors (CGPA: 8.62). Specialized in artificial intelligence and edge computing. Completed projects in machine learning, data analytics, and cross-platform application development.
Smt. Subhadrabai Ramchandra Bhumkar Junior College
Completed 12th (Science) with 86.4%, building a strong foundation in Mathematics, Physics, and Computer Science.
New Times International School
Completed 10th grade with 83.9%, with a strong academic focus in science and mathematics.
Machine learning application that analyzes sales data and predicts future trends using advanced algorithms and interactive visualizations.
Deep learning portfolio showcasing neural network models for computer vision, NLP, sequence forecasting, and real-time AI applications.
Building real-time AI systems on edge devices like Jetson Nano, Raspberry Pi, and microcontrollers.
Built a multi-agent conversational AI system using LangGraph with structured message routing, tool-augmented reasoning, and persistent state. Integrated real APIs and a Streamlit UI supporting multi-threaded chat and RAG-based queries.
Developed a RAG-powered medical chatbot using LangChain, Gemini LLMs, and Pinecone. Implemented PDF ingestion, embedding-based retrieval, and deployed the system on AWS with Docker for real-time, multi-turn medical assistance.
Created an AI-based ATS tool using Gemini LLM to compare resumes with job descriptions, extract missing keywords, and generate improvement suggestions. Features PDF parsing, scoring, and a user-friendly Streamlit interface.
Developed an ML pipeline (XGBoost, scikit-learn) with NLP (DistilBERT) and LLMs (LangChain) for lead scoring, sentiment analysis, and personalized follow-ups, integrated into a CRM-ready, modular system.
Scraped real-time T20 World Cup data and built interactive Power BI dashboards to analyze player stats, team performance, and match trends. Delivered actionable insights on top performers and tournament highlights.
WellTrack is a cutting-edge government application designed to combat malnutrition by leveraging advanced technology to monitor and track nutritional statuses of individuals. Available in both mobile and desktop versions.
I'm always interested in new opportunities and exciting projects. Whether you have a question, want to collaborate, or just want to say hi, feel free to reach out!