I am a Software Engineer and AI/ML Engineer pursuing a B.Tech in Computer Science and Engineering at Guru Nanak Institutions Technical Campus (GNITC, 2023–2027), passionate about building scalable software platforms, intelligent AI applications, and autonomous multi-agent systems.

• 🎓 Selected for Premier Cohorts: Trainee at IIT Patna Vishlesan i-Hub (Machine Learning & Agentic Systems) and shortlisted for Amazon ML Summer School 2026 (Top 23% nationwide from 134,421+ applicants).
• 🚀 15+ Production & Open-Source Projects: Spanning Agentic AI (LangGraph, ChromaDB, Gemini, OpenAI), Computer Vision (YOLOv8, OpenCV), and Full-Stack Systems (React, Next.js, Node.js, FastAPI, PostgreSQL, MongoDB).
• 💼 Professional Internship Experience: Proven industry delivery at IBM SkillsBuild (Deep Learning NLP) and Viswam.AI / Swecha (Multilingual Speech AI & LLM integration).
• 💡 Engineering Philosophy: Delivering scalable, resilient full-stack architectures and low-latency AI pipelines designed for real-world production.

Core Languages
AI / ML & Agentic AI
Backend & Distributed APIs
Frontend & UI Architecture
Databases & Cloud Storage
DevOps, Cloud & Tools

Every project below is developed, tested, and available publicly across my GitHub repositories.

• The Problem: Traditional online exam proctoring relies either on invasive human observers or rigid rule engines that produce false positives and fail to provide constructive student growth.
• The Architecture: Engineered a modular multi-agent platform separating real-time surveillance (Proctor Agent), diagnostic evaluation (Tutor Agent), and administrative reporting (Communication Agent).
• Key Innovations:
  • Live computer vision pipeline performing simultaneous head pose estimation, pupil gaze tracking, multi-face presence detection, and background speech audio transcription.
  • Automatically synthesizes post-exam diagnostic performance reports with personalized remediation roadmaps using Google Gemini & OpenAI LLMs.
• Tech Stack: Python, OpenCV, Streamlit, Google Gemini API, OpenAI, SpeechRecognition, Plotly, Multi-Agent Architecture.

• The Problem: Engineering organizations spend hundreds of hours manually de-duplicating bug tickets, analyzing crash stack traces, and determining root causes across massive codebases.
• The Architecture: RAG-powered multi-agent triage system trained and indexed on historical defect datasets from Apache, Eclipse, and Mozilla.
• Key Innovations:
  • Semantic vector search with ChromaDB to instantly identify duplicate issues and retrieve historical resolution patterns.
  • Autonomous agents parse stack traces, isolate fault-inducing code components, and generate verified code remediation patches.
• Tech Stack: Python, ChromaDB, Google Gemini, FastAPI, Streamlit, RAG, Multi-Agent Systems.

• The Problem: Tech professionals and graduates lack objective, data-backed visibility into market skill deficiencies, leading to misaligned career trajectories and early burnout.
• The Architecture: Full-stack intelligent platform featuring an asynchronous FastAPI backend, MongoDB Atlas persistence, and a high-performance Next.js 14 frontend.
• Key Innovations:
  • Algorithmic resume extraction paired with Google Gemini to identify competitive skill gaps and predict burnout risk trends.
  • Generates milestone-driven, dynamic step-by-step career roadmaps with curated technical learning modules.
• Tech Stack: Next.js 14, TypeScript, FastAPI, MongoDB Atlas, Google Gemini API, Tailwind CSS.

• The Problem: Rapidly congesting commercial drone airspaces create severe risks of mid-air collisions with other UAVs, birds, and unauthorized airspace incursions.
• The Architecture: Real-time edge computer vision safety pipeline combining YOLOv8 object detection with 3D trajectory calculation algorithms.
• Key Innovations:
  • Synthetic flight path generation and predictive vector tracking for early mid-air collision warning.
  • Dynamic geofence breach monitoring with an interactive, telemetry-rich Streamlit situational awareness dashboard.
• Tech Stack: Python, YOLOv8, OpenCV, Streamlit, Spatial Geometry, Real-Time Telemetry.

• The Problem: Trackside railway maintenance crews face deadly hazard conditions due to delayed communication and lack of synchronized train positioning.
• The Architecture: AI-assisted geospatial railway digital twin pairing real-time train movement telemetry with live GPS coordinates of track workers.
• Key Innovations:
  • Deterministic Safety Engine triggering proximity alerts and progressive audible warnings before trains enter active worker sectors.
  • Central Operations Command Center providing safety intelligence, grounded incident analytics, and full system observability.
• Tech Stack: Python, Geospatial AI, Real-Time Safety Engine, Digital Twin Architecture, Streamlit.

• The Problem: Customer support teams require instant, accurate operational retrieval without exposing sensitive company policy data to external public LLM APIs.
• The Architecture: Containerized enterprise offline RAG assistant built on LangGraph cyclical state machines and ChromaDB vector databases.
• Key Innovations:
  • Fully containerized via Docker for air-gapped, zero-leakage local deployment.
  • High-throughput asynchronous query handling via FastAPI with multi-turn conversation memory.
• Tech Stack: LangGraph, ChromaDB, FastAPI, Docker, Python, RAG Architecture.

• The Pipeline: Automated web extraction and ETL pipeline that extracts raw multi-category catalog data, executes schema validation, cleans dirty records, and loads into a 3NF normalized SQLite database.
• Analytics: Features comprehensive SQL indexing and Pandas benchmarks delivering granular category analytics, inventory distributions, and pricing models.
• Tech Stack: Python, BeautifulSoup4 / Scrapy, SQLite, Pandas, SQL Analytics.

• The Pipeline: Industry-standard, leakage-free data science pipeline designed as an end-to-end predictive assessment.
• Key Innovations:
  • Implements strict isolation between training and validation folds to eliminate target leakage.
  • Evaluates Logistic Regression, Random Forest, and Gradient Boosting classifiers; handles class imbalance via cost-sensitive learning and grid-search hyperparameter tuning.
• Tech Stack: Jupyter Notebook, Python, Scikit-Learn, Pandas, NumPy, Seaborn.

• The Problem: Rigid bus ticket cancellation policies lead to high user dissatisfaction, lost revenue for operators, and empty seats on popular travel routes.
• The Architecture: High-conversion booking platform introducing Flexi Tickets with integrated ReBook and ReSell options.
• Key Innovations:
  • Interactive seat layout selector, instant digital confirmation, and a secondary ticket exchange mechanism that minimizes financial loss for passengers.
• Tech Stack: React.js, TypeScript, Tailwind CSS, Modern UI/UX, System Design.

🏆 Formally appreciated and commended by APSRTC and TTD Transport Officials

• The Problem: Tens of thousands of pilgrims traveling between Tirumala and Tirupati face chaotic physical queues, paper ticket wastage, and ticketing fraud.
• The Architecture: Full-stack web ticketing system implementing paperless dynamic QR generation, role-based portals for commuters and conductors, and real-time validation.
• Key Innovations:
  • Contactless digital payments, anti-counterfeit QR pass verification, and automated passenger queue load balancing.
• Tech Stack: Node.js, Express.js, MongoDB, JavaScript, HTML5/CSS3, QR Code Engine.

• The Problem: Fast-moving engineering teams struggle to maintain unified visibility across requirements, code sprints, and deployment milestones.
• The Architecture: Full-stack MERN application providing end-to-end SDLC lifecycle management with dynamic drag-and-drop Kanban boards.
• Key Innovations:
  • Granular role-based permissions, automated activity audit logging, and team velocity metric dashboards.
• Tech Stack: React, Node.js, Express.js, MongoDB, TypeScript, Tailwind CSS.

• The Problem: Cross-lingual verbal communication barriers in public utilities and multi-regional workspaces.
• The Architecture: Real-time web engine capturing microphone audio streams, transcribing speech to text, performing contextual neural translation via Google Gemini, and synthesizing natural speech playback.
• Key Innovations: Supports 50+ languages with live editable transcripts, recording controls, and audio export capabilities. Built during the Viswam.AI internship.
• Tech Stack: Python, Google Gemini API, Streamlit, SpeechRecognition, gTTS, Audio Processing.

• The Problem: Rampant proliferation of misinformation across digital social media channels.
• The Architecture: Deep recurrent neural network using Bidirectional LSTM and word embeddings trained on multi-thousand news corpora, deployed live on Hugging Face Spaces.
• Key Metrics: Achieved ~95% validation accuracy through rigorous text cleaning, stopword filtration, tokenization, and sequence padding. Built during the IBM SkillsBuild internship.
• Tech Stack: Python, TensorFlow/Keras, LSTM, NLTK, Streamlit, Hugging Face Spaces.

• The Problem: Static portfolios fail to demonstrate real-time telemetry, terminal interaction, and responsive frontend UI architecture.
• The Architecture: High-performance interactive portfolio engineered with responsive layouts, dynamic project filtering, dark/light theme switching, and direct social dispatch.
• Tech Stack: HTML5, CSS3, JavaScript, GitHub Pages, Responsive Design.

• 🌟 Shortlisted for Amazon ML Summer School 2026: Shortlisted among 31,821 candidates from 134,421+ applicants nationwide (Top 23%).
• 🎓 Selected for IIT Patna Vishlesan I-Hub: Premier advanced cohort in Machine Learning, RAG, and Multi-Agent Systems.
• 🚀 Campus Ambassador – E-Cell, IIT Bombay: Represented Asia's premier entrepreneurship body on campus, organizing hackathons and startup awareness drives.
• 💡 Infosys Springboard Virtual Internship 7.0: Selected for specialized software engineering training.
• 🏅 Elite NPTEL Certification in Java Programming: 12-week intensive certification with Elite honors from IIT Kharagpur.
• ⭐ Top 25 Creator – VibeCode Creator Program: Recognized among the top creators for technical content and system development.
• 👏 Official Commendation from APSRTC & TTD Officials: Recognized for Govinda Marg's innovative queue reduction and digital bus ticketing architecture.

I am actively seeking Software Engineering (SWE), AI/ML Engineering, and Full-Stack / Backend internships and full-time opportunities.

Designed and custom-engineered with precision by Rakesh Babu Gajula • © 2026