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harinathreddy0999/README.md

Hi there, I'm Harinath Reddy Yelampalle πŸ‘‹

Harinath Reddy Yelampalle

πŸš€ Visionary AI/ML Engineer & Research-Focused Data Scientist | Architecting Next-Gen Healthcare AI, Advanced GenAI, LLM Orchestration & Principled MLOps πŸš€

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πŸ‘¨β€πŸ’» About Me

I am an AI/ML Specialist and Data Scientist, leveraging over 5.5 years of dedicated experience in architecting, developing, and deploying transformative AI solutions. My core passion lies at the confluence of Artificial Intelligence, Computational Neuroscience (e.g., Twin Brain concepts), and Healthcare. I focus on leveraging Advanced Predictive Analytics, Multimodal NLP, Generative AI (GenAI), and Explainable AI (XAI) to pioneer innovations that enhance patient outcomes, optimize clinical workflows, drive biomedical discovery, and promote health equity.

  • πŸŽ“ Holds a Master of Science in Business Analytics from Lewis University, specializing in advanced AI applications.
  • πŸ’‘ Expertise in the full AI/ML lifecycle: from complex data acquisition and advanced feature engineering (including representation learning and dimensionality reduction) to sophisticated model development (Python, Scikit-learn, TensorFlow, PyTorch, JAX) and resilient, scalable deployment using MLOps best practices on Microsoft Azure, AWS, and GCP.
  • πŸš€ Deeply immersed in the cutting-edge of LLMs (e.g., Gemini, Claude 3 series, Grok, GPT-4/5, DeepSeek, Mixtral, Llama series), Retrieval Augmented Generation (RAG) & Advanced RAG techniques, Fine-tuning strategies (PEFT, LoRA, QLoRA), LangChain & LlamaIndex for complex agentic workflows, and building sophisticated Multi-Agent Systems (CrewAI, AutoGen, custom frameworks).
  • 🧠 Exploring and contributing to theoretical AI concepts, including Neuro-Symbolic AI, Causal Inference in ML, and the development of Digital Twins in healthcare.
  • 🎯 Proven ability to translate highly complex technical concepts into strategic, actionable insights for clinical, research, and business stakeholders.
  • 🌱 Committed to pioneering Responsible AI by rigorously implementing AI Ethics, fairness, transparency (SHAP, LIME), privacy-preserving ML (Federated Learning, Differential Privacy), and robust model governance.

πŸ’Ό Work Experience

AI/ML Engineer

Centene Corporation Β· Contract Β· St Louis, Missouri, United States (Remote) Jan 2024 - Apr 2025 (1 yr 4 mos)

  • Leveraged AI/ML for predictive modeling of patient outcomes, focusing on maternal/infant health and reducing readmissions. (Tools: Python, XGBoost)
  • Deployed AI to address social determinants of health (NEST Program), improving health equity through NLP & geospatial risk mapping. (Tools: Python, SpaCy, BERT, SQL)
  • Developed AI models for fraud detection, decreasing fraudulent activities. (Tools: Python, Azure Security Center)
  • Contributed to NLP automation of claims processing. (Tech: Transformer models like BERT, GPT)
  • Implemented MLOps practices on Azure for CI/CD of machine learning models. (Tools: Azure ML, Docker, Kubernetes)
  • Collaborated with cross-functional teams to translate AI-driven insights into actionable clinical and operational improvements.

Data Scientist

Wipro Β· Contract Β· Hyderabad, Telangana, India (Hybrid) Jun 2019 - Jun 2023 (4 yrs 1 mo)

  • Led the development and implementation of AI-powered claims management solutions for key healthcare insurance clients.
  • Conducted comprehensive exploratory data analysis (EDA) and advanced feature engineering on large-scale healthcare datasets.
  • Built and validated machine learning models using Python, Scikit-learn, and TensorFlow to predict patient risk, optimize resource allocation, and improve claims processing efficiency.
  • Developed and deployed NLP models for automated healthcare document processing, information extraction, and claims validation.
  • Designed and orchestrated end-to-end data pipelines using SQL, Azure Data Factory, and Databricks for robust healthcare data integration, transformation, and analysis.
  • Collaborated closely with engineering and product teams to integrate AI models into existing healthcare platforms and new applications.
  • Championed and ensured AI solutions complied with Responsible AI principles, focusing on patient data privacy, security, and ethical considerations.

πŸ› οΈ My Tech Arsenal

My comprehensive toolkit for pioneering AI solutions:

Core Programming, Data Science & Scientific Computing:

Python SQL Java Julia Pandas Numpy SciPy scikit-learn Seaborn Matplotlib Plotly

Machine Learning, Deep Learning & Reinforcement Learning:

TensorFlow PyTorch JAX Keras XGBoost LightGBM CatBoost Ray RLlib Reinforcement Learning AutoML

Natural Language Processing (NLP) & Speech Technologies:

spaCy NLTK HuggingFace Transformers OpenAI Whisper Speech Technologies

Generative AI, LLMs & Agentic Frameworks:

OpenAI API Google Gemini Anthropic Claude xAI Grok DeepSeek Mistral AI LangChain LlamaIndex CrewAI AutoGen Prompt Engineering & Finetuning GitHub Copilot

Cloud Platforms & Services:

Microsoft Azure AWS GCP

MLOps, Deployment & CI/CD:

MLflow Kubeflow DVC Docker Kubernetes FastAPI Flask TFX GitHub Actions Jenkins Domino Data Lab

Databases, Vector Stores & Data Pipelines:

MongoDB PostgreSQL Pinecone ChromaDB Weaviate FAISS Google BigQuery Amazon Redshift Snowflake Azure Data Factory Databricks Apache Kafka Apache Spark Apache Airflow

Web Frameworks, Visualization & Other Tools:

Git Streamlit Gradio Jupyter


✨ Featured Projects & Research Areas

Here are a few selected projects and areas of active research. (Please check my pinned repositories for more examples!)

🩺 Advanced Chronic Disease Monitoring & Prognosis

Chronic Disease Monitoring

Developing sophisticated AI systems for real-time monitoring and prognosis of chronic diseases (e.g., diabetes, cardiovascular conditions) using multimodal data (EHR, IoT sensors, imaging). Employs deep learning for time-series forecasting, survival analysis, and early detection of adverse events.
Key Tech: Python, TensorFlow/PyTorch, LSTM/Transformers for Time Series, Survival Models, XAI (SHAP, Grad-CAM)
View Project

πŸ€– GenAI-Powered Clinical Data Analysis & Insights Agent

AI Data Analysis Agent

Architected an autonomous AI agent using LLMs and RAG to perform complex data analysis on clinical datasets. The agent interprets natural language queries, performs statistical analysis, generates hypotheses, visualizes data, and synthesizes insights for research and clinical decision support.
Key Tech: Python, LangChain/LlamaIndex, CrewAI, OpenAI GPT/Gemini, Pandas, Vector DBs (Pinecone/Chroma)
View Project

🍽️ AI-Driven Personalized Nutrition & Meal Planning (PantryPal AI)

AI Meal Planner

Leading the conceptualization and development of AI for PantryPal AI: a hyper-local, seasonal meal planning app focusing on advanced food waste reduction. Leverages LLMs for personalized meal plans based on dietary needs, health goals, pantry inventory, and local store savings. Includes predictive spoilage models.
Key Tech: Python, GenAI APIs (Gemini/GPT), Streamlit/FastAPI, Predictive Modeling, Pantry Inventory Management UX
View Project

πŸ’‘ LumiNIC-Q: AI-Assistant for Neonatal Intensive Care Quality Improvement

LumiNIC-Q Project

LumiNIC-Q is an AI-driven decision support system designed to enhance the quality of care in Neonatal Intensive Care Units (NICUs). It analyzes real-time physiological data, clinical notes, and lab results to predict potential complications (e.g., sepsis, IVH), optimize treatment protocols, and provide actionable insights to clinicians for improved neonatal outcomes.
Key Tech: Python, PyTorch, Deep Reinforcement Learning, NLP (BioBERT, ClinicalBERT), Time Series Analysis, Explainable AI (XAI), FHIR/OMOP data standards.
View Project


πŸ–ΌοΈ AI Innovations & Visualizations Gallery

This section is dedicated to showcasing visual outputs, architectural diagrams, and conceptual representations of AI projects and research. (Remember to replace the placeholder src attributes below with direct links to your own high-quality images!)


View Details -->
AI Model Architectures
(e.g., Custom CNNs, Transformer Visualizations)
AI Model Architecture Example
View Details
Data Visualizations & Insights
(e.g., Complex Data Dashboards, t-SNE plots)
Data Visualization Example
View Details
GenAI Creations & Outputs
(e.g., AI-generated images, text summaries)
GenAI Output Sample
View Details
Interactive Demo Screenshot
(Description)
Demo Screenshot
View Details
Research Poster Snippet
(Description)
Research Poster Snippet
View Details

πŸ… Certifications & Advanced Training

SuperHuman AI Certification
AWS Prompt Engineering Certification
AWS Generative AI with LLMs
DeepLearning.AI Hugging Face Certification
DeepLearning.AI CrewAI Certification
DeepLearning.AI AutoGen Certification
DeepLearning.AI LangChain Certification
DeepLearning.AI LangChain Chat with Your Data
DeepLearning.AI Gradio Certification
IBM Data Analytics Certification


πŸ“Š GitHub Stats

Harinath's GitHub Stats

Top Languages

GitHub Streak


🀝 Let's Connect, Innovate & Collaborate!

I'm passionate about pushing the boundaries of AI, especially in healthcare and "Twin Brain" research. Always open to discussing novel ideas, collaborating on impactful projects, or exploring pioneering opportunities.


πŸ˜„ Fun Fact

⚑️ My AI models occasionally try to convince me that the optimal solution to a complex problem is simply "more data... or a good cup of coffee." Often, they're not wrong about the coffee! πŸ˜‚


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