BS in Applied AI & Data Science student @ IIT Jodhpur
Building robust, intelligent applications at the intersection of deep neural analytics, mathematical modeling, and production-grade software infrastructures.
My engineering foundation is built on absolute logical rigour. Forged in the intense residential environments of JNV and Sikar, I approach data science from a mathematical, first-principles perspective.
Currently pursuing a BS in Applied AI & Data Science at IIT Jodhpur, I bridge the gap between abstract mathematics and production-grade software. I specialise in machine learning, full-stack web development, and Android architectures. To me, a model is only as powerful as the infrastructure that serves it. I don't just train architectures—I build the real-world pipelines that make them scale.
Consistent high performance in rigorous technical curriculum.
Transformer architectures and large language models.
I don't just train models in Jupyter notebooks. I containerize, deploy, and monitor them using industry-standard MLOps practices.
Currently pursuing a BS in Applied AI & Data Science with a strong focus on Machine Learning, Artificial Intelligence, Statistics, Programming, and Data Analytics.
8.375
ML • AI • Android • Web
A systematic progression through rigorous academic environments, building the mathematical and algorithmic foundation required for advanced AI research.
Focusing entirely on deep learning architectures, scalable data pipelines, automated machine learning (MLOps), and advanced statistical algorithms.
JEE Preparation and 12th board diagnostics execution. Intensive quantitative problem solving.
11th standard systematic progression under residential system criteria.
6th - 10th standard foundational reasoning modules execution.
Advanced algorithmic optimization, data structuring, and backend scripting.
Architecting CNNs, RNNs, and custom neural networks for predictive analysis.
Data parsing, feature engineering, and high-dimensional statistical modeling.
Integrating Large Language Models, semantic parsing, and RAG architectures.
Current CGPA
Projects
Technologies
Started AI Journey
A selection of end-to-end applications demonstrating my ability to build robust machine learning models, from scratch frameworks, to applied GenAI tools.
A modular deep learning framework built strictly in Python and NumPy without relying on PyTorch or TensorFlow. Implements forward/backward propagation, activation layers, and custom optimizers to deeply understand mathematical mechanics.
An AI-powered IDE extension that automatically translates legacy codebases into modern frameworks, cutting migration time in half using applied Generative AI and LLM parsing.
Android-based artificial intelligence application for scanning, parsing, and scoring applicant resumes automatically.
A recommendation engine designed to intelligently match students with optimal curriculum paths based on historical data.
Conversational AI bot configured to dynamically interview candidates and extract relevant competency metrics.
Integration and deployment of Large Language Models (LLMs) via API to a scalable edge network on Vercel.
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Active open-source contributions, research logs, and version control mastery. My GitHub is the public ledger of my daily coding, data engineering, and deployment habits.
Engaging deeply with IIT Jodhpur curriculum data science projects, focusing on statistical modeling optimizations.
Documenting machine learning roadblocks, architectural decisions, and MLOps strategies for future reference.
Comprehensive mastery of core supervised and unsupervised algorithms.
Verified CredentialAdvanced data analysis, cleaning methodologies, and structuring pipelines.
Verified CredentialProven ability to rapid-prototype, build, and deploy ML models under strict deadlines.
Competition LogGoogle AI Studio
Google Cloud Skills Boost
Kaggle
IIT Jodhpur Coursework
Upcoming Certifications
A deep dive into building fault-tolerant data ingestion systems using modern Python and containerization.
Lessons learned while optimizing LLMs for contextual semantic similarity scoring in the real world.
Connecting Java-based Android apps to unstructured web data flows efficiently without breaking Firebase logic.
I am actively seeking machine learning internships, open-source collaborations, and rigorous data science roles.
Whether you are building scalable AI architectures, need an Android integration, or just want to discuss transformer models—my inbox is always open. Let's engineer something impactful.
