Hi, I'm Pathik Rupwate. With 4+ years of hands-on experience and an MS from the University of Chicago, I architect and deploy end-to-end predictive models, Generative AI agentic workflows (MCP, RAG, LangChain), and computer vision pipelines that turn complex datasets into measurable business growth.
Comprehensive toolset spanning production machine learning, Generative AI agent architectures, and enterprise analytics.
Test live, browser-native implementations of production predictive models, computer vision neural networks, and autonomous multi-tool agent workflows.
Evaluate how unsupervised Isolation Forests and ensemble models detect high-risk loan defaults under severe class imbalance. Adjust credit metrics or select preset profiles to observe real-time scoring.
Explainable AI (XAI) breakdown decomposing the net anomaly score into individual Shapley feature contributions relative to the baseline expected risk ($\mathbb{E}[f(x)] = 22\%$).
Explore how macroeconomic inflation shocks and Federal Reserve interest rate shifts drive sector rotation across all 11 S&P 500 sectors, augmented with Tabular GANs to model tail-risk regimes.
Predictive outperformance probabilities across all 11 S&P 500 sectors generated by Extra Trees classifiers under the active macroeconomic regime.
High-precision facial geometry extraction via a 468-point 3D landmark mesh, feeding 22 calibrated anthropometric ratios into a fine-tuned deep convolutional neural network (VGG-16 architecture).
Real-time geometric ratios and continuous regression output running directly in-browser with WebGL GPU acceleration.
Interactive demonstration of an autonomous enterprise agent utilizing the Model Context Protocol (FastMCP) for multi-tool planning and execution. Select an operational mission below to trigger the reasoning and dispatch loop.
Follow the agent's internal thought stream, real-time FastMCP JSON protocol dispatch, observation ingestion, and final structured output.
Interactive demonstration of multi-dimensional customer segmentation combining PCA dimensionality reduction with K-Means clustering to identify high-value cohorts and optimize targeting.
Select any cluster in the scatter plot to inspect its financial profile, latent Dirichlet allocation (LDA) review topics, and targeted campaign recommendations.
High balance preservation, low credit risk, high interest in wealth management and municipal bonds.
Key engineering, modeling, and generative AI initiatives delivering quantifiable business and operational impact.
Spearheaded the development of a municipal AI agent utilizing the Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and complex Data APIs. Integrated this agent as a major feature upgrade to flagship Mainet software, significantly accelerating critical data accessibility for government officials.
Directed the end-to-end architecture of an automated, multi-lingual tutorial video generation pipeline using Python and the ElevenLabs API, completely eliminating manual voiceover work and streamlining product rollouts across languages.
Engineered a sophisticated data parsing and recovery solution to salvage 400,000+ unstructured files recovered from an AWS incident. Developed custom pattern-matching algorithms to restore original directory structure and metadata, averting critical data loss.
Designed and implemented an AI-driven vulnerability testing suite by integrating OWASP ZAP with Gemini AI, enabling automated discovery of security flaws alongside intelligent, autonomous generation of remediation code patches.
Predicted S&P 500 sector performance across 50, 100, and 200-day horizons. Generated synthetic economic data via Tabular GANs and SMOTE to resolve severe class imbalance (+20% robustness). Identified macroeconomic drivers (CPI) via causal inference.
Built customer persona clustering (K-means, DBSCAN, PCA) combined with NLP topic modeling (LDA/TF-IDF) on user feedback to drive +30% ad campaign ROI. Deployed Isolation Forests and One-Class SVMs to boost rare loan default forecasting by 25%.
Engineered an end-to-end real-time BMI prediction pipeline utilizing a VGG-16 CNN deep learning architecture. Served the model in production via a Flask API processing live video input feeds with OpenCV optimization.
Interactive AI chatbot embedded directly in this website! Features dual-engine architecture: an instant in-browser semantic knowledge engine with optional direct Google Gemini Live LLM integration.
Track record of building data-driven systems across enterprise technology, banking, and academic research.
Strong foundation in applied data science, computer science, and quantitative economics.
Whether you are seeking a Data Scientist / ML Engineer for agentic AI architectures, predictive models, or end-to-end data pipelines, let's talk.