{ "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json", "basics": { "name": "Bodapati Bharat Chandra", "label": "AI/ML Engineer", "image": "https://bharatchandra.me/bodapati-bharat-chandra.jpg", "email": "bc833498@gmail.com", "url": "https://bharatchandra.me", "summary": "AI/ML Engineer and final-year CSE student at GITAM University Hyderabad. Building production AI systems at BHEL, leading backend & ML at GARI rocketry team, and co-founding Easify. Specialized in FastAPI, PyTorch, real-time systems, and explainable AI.", "location": { "city": "Hyderabad", "countryCode": "IN", "region": "Telangana" }, "profiles": [ { "network": "GitHub", "username": "BharatChandra-sys", "url": "https://github.com/BharatChandra-sys" }, { "network": "LinkedIn", "username": "bharat-chandra-bodapati", "url": "https://www.linkedin.com/in/bharat-chandra-bodapati/" }, { "network": "ORCID", "username": "0009-0004-4734-1635", "url": "https://orcid.org/0009-0004-4734-1635" } ] }, "work": [ { "name": "BHEL — Bharat Heavy Electricals Limited", "position": "AI/ML Engineering Intern", "url": "https://bhel.com", "startDate": "2026-05", "summary": "Building production AI systems at one of India's largest public sector enterprises. Fully on-premise LLM deployment with zero external API dependency.", "highlights": [ "Built production-grade AI vendor compliance portal using FastAPI, Ollama, and PyMuPDF — runs fully on-premise", "Designed LLM-powered document extraction pipeline for tender analysis with no external API dependency", "Proposed turbine lifecycle optimisation system using LSTM autoencoders and physics-informed digital twin modelling for GM-level stakeholder review" ], "location": "Hyderabad, India" }, { "name": "Easify — Pooling Service Platform", "position": "Co-Founder", "url": "https://bharatchandra.me", "startDate": "2023", "summary": "Co-founded Easify, a smart pooling service platform connecting commuters for shared rides in Hyderabad.", "highlights": [ "Architecting and building the full-stack pooling platform with real-time ride matching", "Designed backend API, database schema, and payment integration with Razorpay", "Leading product strategy, user onboarding, and go-to-market for Hyderabad launch" ], "location": "Hyderabad, India" }, { "name": "GARI — GITAM Aerospace Rocketry Initiative", "position": "Backend & ML Lead", "url": "https://bharatchandra.me", "startDate": "2026-02", "summary": "Leading the backend and ML stack for GITAM's rocketry team competing in the IN-SPACe national competition.", "highlights": [ "Built CAN-7USAT rocket telemetry backend achieving sub-5ms end-to-end latency (target was 15ms)", "Engineered real-time WebSocket streaming pipeline for live ground station dashboards", "Developed GARI team website with React, canvas starfield, and SVG animations" ], "location": "GITAM University Hyderabad" }, { "name": "Elevate Labs", "position": "AI/ML Intern", "url": "", "startDate": "2026-04", "endDate": "2026-05", "summary": "Applied ML internship focused on preprocessing, model training, evaluation, and deployment-oriented backend integrations.", "highlights": [ "Applied ML: preprocessing, model training, evaluation and deployment-oriented backend integrations" ], "location": "Remote" } ], "education": [ { "institution": "GITAM University Hyderabad", "url": "https://gitam.edu", "area": "Computer Science & Engineering", "studyType": "Bachelor of Technology", "startDate": "2023", "endDate": "2027", "score": "", "courses": [] } ], "awards": [ { "title": "Winner - AI Day Hackathon", "date": "2026-03", "awarder": "GITAM University × Kodryx AI", "summary": "Won for MedVision AI — Explainable diabetic ulcer detection system with Grad-CAM and SHAP" }, { "title": "Winner - HackXplore", "date": "2026-04", "awarder": "IEEE-SSIT VJIT", "summary": "Won for FactCheck AI — Browser-based fake news analyzer with 90% accuracy" } ], "skills": [ { "name": "Languages & Frameworks", "level": "Expert", "keywords": [ "Python", "FastAPI", "PyTorch", "SQLAlchemy", "React", "TypeScript", "JavaScript" ] }, { "name": "ML & AI", "level": "Advanced", "keywords": [ "MLflow", "SHAP", "Grad-CAM", "Scikit-learn", "DVC", "Ollama", "LM Studio" ] }, { "name": "Infrastructure & DevOps", "level": "Advanced", "keywords": [ "Docker", "PostgreSQL", "WebSockets", "Prometheus", "Grafana", "Git" ] }, { "name": "Autonomous Systems", "level": "Advanced", "keywords": [ "ROS2", "Kalman Filtering", "Sensor Fusion", "Real-time Telemetry", "RBAC", "JWT Auth" ] } ], "languages": [ { "language": "English", "fluency": "Native speaker" }, { "language": "Hindi", "fluency": "Native speaker" }, { "language": "Telugu", "fluency": "Native speaker" } ], "interests": [ { "name": "Rocketry & Aerospace", "keywords": [ "Telemetry Systems", "Flight Control", "Sensor Fusion" ] }, { "name": "Explainable AI", "keywords": [ "Grad-CAM", "SHAP", "Model Interpretability" ] }, { "name": "Production Systems", "keywords": [ "FastAPI", "WebSockets", "Real-time Systems" ] } ], "projects": [ { "name": "CAN-7USAT Ground Control Station", "description": "Real-time ground control station for IN-SPACe Model Rocketry Competition 2026. Sub-5ms end-to-end latency, Kalman filter sensor fusion, 6-state flight state machine.", "highlights": [ "Achieved sub-5ms latency (target was 15ms)", "0% packet loss with 23/23 tests passing", "Real-time WebSocket broadcasting to React dashboard" ], "keywords": [ "Python", "FastAPI", "WebSockets", "Kalman Filter", "PostgreSQL" ], "startDate": "2026-02", "url": "https://github.com/BharatChandra-sys/CAN-7USAT-Ground-Control-Backend", "roles": [ "Backend Lead", "ML Engineer" ], "type": "application" }, { "name": "AUVBrain — Autonomous Underwater Vehicle", "description": "Full autonomous control stack for an underwater vehicle. Deterministic observe→decide→act agent loop with 4-DOF thruster control, offline LLM decision engine.", "highlights": [ "Agent loop p95 latency: 0.84ms", "Offline LLM with rules-based fallback", "ROS2 integration for sensor fusion" ], "keywords": [ "Python", "ROS2", "FastAPI", "Docker", "llama.cpp" ], "startDate": "2026-01", "url": "https://github.com/BharatChandra-sys/AUVBrain", "type": "application" }, { "name": "MedVision AI — Diabetic Ulcer Detection", "description": "Explainable AI system for diabetic ulcer risk detection. Grad-CAM heatmaps, SHAP values, MLflow tracking. Won AI Day Hackathon.", "highlights": [ "Won GITAM × Kodryx AI Hackathon (March 2026)", "Explainable with Grad-CAM and SHAP", "MLflow + DVC for experiment tracking" ], "keywords": [ "PyTorch", "Grad-CAM", "SHAP", "MLflow", "DVC", "FastAPI" ], "startDate": "2026-03", "url": "https://github.com/BharatChandra-sys/diabetic-ulcer-ai-system", "type": "application" } ], "meta": { "canonical": "https://bharatchandra.me/resume.json", "version": "v1.0.0", "lastModified": "2026-07-24T10:08:46.833Z" } }