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kamaladhi/README.md

Hi, I'm Jeevakamal K R 👋

AI & Data Science undergraduate at Amrita Vishwa Vidyapeetham (B.Tech, 2023–2027). I build systems at the intersection of physics, machine learning, and real-world deployment — from physics-informed neural networks to production healthcare AI.

🏆 Best Paper Award — SISCON Conference, Dec 2025


💼 Experience

AI/ML Engineering Intern — UVS Cube Infotech, Madurai Mar 2026 – May 2026 · Completed ✅

Built and deployed two production AI systems for the MyBeat live healthcare platform:


🤖 MyBeat Care AI Chatbot

  • Built a hybrid RAG pipeline — FAISS (dense) + BM25 (sparse) + PubMedBERT reranking for accurate medical query resolution
  • Integrated FHIR R4 / ABDM standards for real-time patient history injection into LLM prompts
  • Engineered a deterministic severity scoring engine (0–100) with red-flag symptom detection
  • Implemented Triple-Gate output safety — guarantees zero diagnostic statements in all responses

Stack: FastAPI · FAISS · BM25 · PubMedBERT · Llama-3.1 · Redis · Docker · NGINX · GitHub Actions


🎙️ MyBeat Voice Assistant

  • Built end-to-end voice pipeline: Whisper ASRLlama-3.1 NLU (Groq) → pyttsx3 TTS with Gemini failover
  • Dual-layer NLU — keyword pattern matching (fast/offline) + Llama-3.1 for complex sentences; supports 8 intents (BOOKING, RECOMMENDATION, LAB_BOOKING, MANUAL_HANDOFF etc.)
  • Built a 3-Stage Cascade Recommendation Engine for doctor ranking:
    • Stage 1 (60%) — Content: Distance · Experience · Fee · Language
    • Stage 2 (25%) — Feedback: Ratings · Repeat visits · Booking conversion
    • Stage 3 (15%) — Trust: Verified credentials · Urgent availability · Insurance match
  • Implemented voice-to-UI control — returns structured JSON uiActions (NAVIGATE, AUTO_FILL, HIGHLIGHT_RECOMMENDATION) for hands-free app navigation
  • OpenWakeWord (ONNX) for always-on "Hey MyBeat" hands-free activation
  • Secured all endpoints with JWT Bearer Token (HS256) authentication

Stack: FastAPI · Whisper · Llama-3.1 · OpenWakeWord · pyttsx3 · PyJWT · Docker · NGINX · GitHub Actions CI/CD · IIS Reverse Proxy


🔬 What I've been building

  • Physics-Informed Neural Networks (PINNs) for EV range prediction under real traffic
  • Federated learning pipelines for power infrastructure defect detection
  • Edge ML deployment on Raspberry Pi and NVIDIA Jetson
  • Tamil NLP — fine-tuning LLaMA 3.1 with LoRA for low-resource translation

🛠️ Skills

ML / AI: PyTorch · PINNs · Federated Learning · LSTMs · Attention · YOLOv8 · LoRA / QLoRA · RAG · LLMs
Voice AI: OpenWakeWord · Whisper · pyttsx3
HPC: CUDA · OpenMP · C++ · Parallel & Heterogeneous Computing
Full Stack: Python · React · FastAPI · Flask · REST APIs · MySQL · HTML5 · CSS3
Hardware / IoT: Raspberry Pi · Arduino · Blynk IoT
MLOps: MLflow · Weights & Biases · Docker · NGINX · Redis · Git · GitHub Actions
Languages: Python · C++ · JavaScript · Java (basics) · MATLAB · Scala (basics)


📌 Featured Projects

Project Description Tech
Snake Rescue Robot 🎥 YOLOv8 human detection on servo robot — Best Paper Award YOLOv8, RPi, Arduino
EV Range Prediction (PINN) Physics-constrained LSTM, <5% RMSE, W&B tracked PyTorch, SUMO, MLflow
HPC Satellite Benchmark Serial vs OpenMP vs CUDA on 405k satellite images C++, CUDA, OpenMP
FedRetinaNet Federated object detection, mAP@50 of 0.91 Python, RetinaNet
Tamil NLP (LLaMA) LLaMA 3.1 8B fine-tuned for Tamil↔English translation Unsloth, LoRA, 4-bit
Urban Microgrid Digital Twin Predictive cyber-physical resilience framework CNN-BiLSTM, FastAPI

📄 Publications


🏅 Certifications

  • Physics-Informed Neural Networks — Udemy (May 2025)
  • Google AI Essentials (Jul 2024)
  • Foundations of Cybersecurity — Google (Mar 2024)

📫 Connect

LinkedIn Email GitHub Stats

Pinned Loading

  1. EV-Range-prediction-using-PINNS-under-real-traffic-condition EV-Range-prediction-using-PINNS-under-real-traffic-condition Public

    This project implements a Physics-Informed Neural Network (PINN) for electric vehicle range prediction under real traffic conditions. By embedding physical constraints and traffic-aware dynamics in…

    Jupyter Notebook 2

  2. A-Predictive-Cyber-Physical-Digital-Twin-for-Urban-Microgrid-Resilience. A-Predictive-Cyber-Physical-Digital-Twin-for-Urban-Microgrid-Resilience. Public

    An intelligent digital twin framework for urban microgrids that leverages cyber-physical integration and predictive analytics to improve system resilience, reliability, and adaptive energy manageme…

    Python 1 1

  3. FedRetinaNet-Insulator-Defect-Detection FedRetinaNet-Insulator-Defect-Detection Public

    FedRetinaNet is a federated learning-based object detection framework built on RetinaNet for insulator defect detection. It enables multiple clients to collaboratively train a high-performance dete…

    Jupyter Notebook 1 1

  4. Heterogeneous-Satellite-Imaging-Benchmark Heterogeneous-Satellite-Imaging-Benchmark Public

    Experimental performance study of heterogeneous parallel computing strategies for satellite image filtering (SAT-6 dataset), featuring cache-optimized tiling, dynamic scheduling, and CUDA-based NLM…

    C++ 1 3

  5. Efficient-English-Tamil-Translation-using-Unsloth-Optimized-Transformer Efficient-English-Tamil-Translation-using-Unsloth-Optimized-Transformer Public

    English→Tamil translation model built using an Unsloth-optimized transformer with LoRA and 4-bit quantization. Developed as part of our Text Analytics semester project, including our own implementa…

    Jupyter Notebook 1 1

  6. Restaurent-Managment-System-Using-Jack-language Restaurent-Managment-System-Using-Jack-language Public

    This is a simple and a Basic project which was developed using Jack Language provided by NAND2Tetris.

    1