Hi, I am 👋

Raghu Ram
Komara

Healthcare AI Research
Software Engineer

I build healthcare AI systems, privacy-preserving machine learning pipelines, and cloud-native clinical software that support biomedical research, clinical data workflows, and real-world healthcare applications.

Contact Me View Portfolio
🏆
WITS 2025 Research Presenter Privacy-Preserving Healthcare AI
Raghu Ram Komara
🎓
M.S. AI & Business Analytics USF · GPA 3.83/4.0

About Me

Building Research Software
for Healthcare AI

I am a Software Engineer and AI Researcher pursuing an M.S. in Artificial Intelligence and Business Analytics at the University of South Florida. My work combines healthcare-focused application development, federated learning, backend engineering, cloud-native systems, and reproducible research workflows for biomedical and clinical data environments.

3.83 Graduate GPA at USF
100–150 Students Mentored in Python Analytics
5+ AI / ML / Research Projects
1 Research Paper Presented at WITS 2025
Software Engineer Accenture · Hyderabad

Developed scalable backend applications, REST APIs, and microservices using Python and JavaScript across enterprise environments. Worked on PostgreSQL/MySQL schema optimization, Snowflake analytics workflows, AWS infrastructure, and CI/CD pipelines.

PythonJavaScriptREST APIsPostgreSQLMySQLSnowflakeAWSJenkins
M.S. Student · AI & Analytics University of South Florida · Tampa

Started graduate study in Artificial Intelligence and Business Analytics with coursework in machine learning, deep learning, cloud solutions architecture, big data, advanced database systems, and analytics application development.

Machine LearningDeep LearningCloud ArchitectureBig DataDatabase Systems
Graduate Research Assistant University of South Florida

Developing privacy-preserving healthcare AI systems using Python, PyTorch, Flower, Docker, Linux-based environments, and GPU-enabled infrastructure. Research focuses on federated learning, anomaly-aware aggregation, adaptive clipping, and robust AI workflows for decentralized medical data.

Federated LearningPyTorchFlowerDockerHealthcare AIResearch Computing
Full Stack Engineer USF · Client: Evara Health

Designed and developed mobile and web-based healthcare applications using React Native, FastAPI, REST APIs, Docker, Azure cloud infrastructure, and Azure Cognitive Services to support real-time patient-provider communication workflows.

React NativeFastAPIREST APIsDockerAzureHealthcare Applications
Graduate Teaching Assistant University of South Florida · Tampa

Mentored 100–150 students in Python for Business Analytics, supporting data analysis, debugging, SQL, Excel, and analytical workflow development. Guided responsible use of AI-assisted development tools including Claude and GitHub Copilot.

PythonSQLExcelAI-Assisted DevAnalytics
AI Engineer Intern PODS Enterprises, LLC · Tampa

Building production-ready LLM workflows and agentic AI software using Claude Enterprise, LangChain, and LangGraph. Developing RAG systems with vector search, reranking, and grounding for reliable AI-assisted information retrieval and route optimization.

LangChainLangGraphRAGAgentic AIClaude Enterprise
Download Resume Hire Me

My Specialties

Where I Create Impact

I specialize in building software systems that connect healthcare research, machine learning models, clinical workflows, and cloud-native engineering into reliable applications.

🏥
Healthcare AI

Healthcare AI & Clinical Data Systems

Building healthcare-focused applications and clinical data workflows that support patient-provider communication, biomedical research, AI-assisted analysis, and secure software delivery.

Healthcare AI Clinical Data HIPAA-Conscious FastAPI Azure
View related projects →
🔐
Privacy ML

Federated Learning & Privacy-Preserving AI

Developing distributed federated learning pipelines for decentralized healthcare data using PyTorch, Flower, anomaly-aware aggregation, and adaptive clipping techniques.

Federated Learning PyTorch Flower Adaptive Clipping Byzantine Robustness
View research →
🔬
Research Software

Research Software Engineering

Designing reproducible research workflows, ML experimentation environments, data preprocessing pipelines, model evaluation scripts, and visualization tools for healthcare and oncology-related datasets.

Python Docker Linux GPU Infrastructure Reproducible Research
View experience →
⚙️
Full-Stack

Backend Engineering & API Development

Developing REST APIs, microservices, backend integrations, asynchronous workflows, and secure data exchange systems across healthcare, research, and enterprise environments.

REST APIs Microservices FastAPI Flask Distributed Systems
View portfolio →
📊
Data Systems

Database Design & Analytics Workflows

Designing optimized PostgreSQL and MySQL schemas, improving query performance, modeling data for analytics workflows, and supporting downstream Snowflake-based data environments.

PostgreSQL MySQL Snowflake Query Optimization Data Modeling
View work history →
☁️
Cloud & DevOps

Cloud-Native Deployment & DevOps

Containerizing applications, deploying cloud-based systems, managing CI/CD pipelines, and building reliable development environments using Docker, AWS, Azure, Jenkins, and GitHub Actions.

Docker AWS Azure Jenkins GitHub Actions CI/CD
View technical work →

My Portfolio

What I've Built

A focused set of projects across healthcare AI, federated learning, clinical NLP, cybersecurity, backend systems, and applied machine learning.

🛡️
Research · Cybersecurity

AI Cybersecurity SOC Agent

Built a real-time GenAI-enabled cybersecurity platform using FastAPI, Elastic Stack, and LLM-based workflows to process streaming security logs, support threat detection, and enable scalable monitoring.

FastAPI Elastic Stack LLM Workflows Streaming Logs
View Repo →
🏥
Healthcare · Clinical Communication

MedLingo — Clinical Communication Platform

Designed and developed a healthcare communication platform for Evara Health using React Native, FastAPI, REST APIs, Docker, Azure cloud infrastructure, and Azure Cognitive Services for speech recognition and neural machine translation.

React Native FastAPI Azure Cognitive Services Docker
View Repo →
⚕️
Healthcare · Active Build

ClinicOS — Clinical Workflow Platform

Building an AI-powered clinical workflow platform for small and mid-sized clinics, with role-based workflows, patient intake, clinical note generation, treatment summaries, and secure backend architecture.

Next.js FastAPI Supabase PostgreSQL
View Repo →
🧬
Research · Clinical NLP

Radiology Report to Structured JSON

Built an NLP pipeline using Hugging Face Transformers and LoRA fine-tuning to convert unstructured radiology reports into structured JSON outputs for improved extraction reliability and downstream usability.

Hugging Face LoRA NLP Structured JSON
View Repo →
🔐
Research · Federated Learning

FL-IDS — Federated Intrusion Detection

Developed a federated intrusion detection system using Docker-based orchestration to detect cyber threats across distributed environments without sharing raw data.

Federated Learning Docker Intrusion Detection Privacy-Preserving ML
View Repo →

Work History

Professional Experience

🤖

AI Engineer Intern

PODS Enterprises, LLC · Tampa, FL
Jun 2026 — Present
  • Developing Python-based AI software using Claude Enterprise, LangChain, and LangGraph to build production-ready LLM workflows with tool calling, structured outputs, error handling, and workflow orchestration.
  • Built retrieval-augmented generation (RAG) systems integrating operational data sources through document ingestion, embeddings, vector search, reranking, grounding, and evaluation to deliver reliable AI-assisted information retrieval.
  • Designed agentic AI software for route optimization by implementing planning workflows, state management, memory, and tool orchestration to automate operational decision-making and resource allocation.
LangChain LangGraph RAG Agentic AI Claude Enterprise Python
🔬

Graduate Research Assistant

University of South Florida · Tampa, FL
May 2025 — Present
  • Developed research software and distributed machine learning pipelines using Python, PyTorch, Flower, and Docker to support machine learning analyses of healthcare, medical imaging, and oncology-related datasets.
  • Built software tools for data preprocessing, integration, feature engineering, model evaluation, visualization, and experiment tracking, enabling reproducible computational workflows for biomedical AI research.
  • Maintained structured healthcare and medical imaging datasets by developing preprocessing, validation, and data organization workflows suitable for scalable machine learning experimentation and transparent research.
  • Integrated machine learning frameworks, experiment tracking platforms (MLflow, Weights & Biases), and visualization tools to support reproducible research, software validation, and analysis of experimental results.
  • Authored technical documentation, computational workflows, and literature reviews while supporting researchers and students in utilizing research software, reproducing experiments, and adopting AI-assisted development practices.
  • Co-authored healthcare AI research on privacy-preserving federated learning by designing distributed experimentation environments and contributing to research presented at WITS 2025, with manuscript preparation underway for IEEE Journal of Biomedical and Health Informatics (J-BHI).
Federated Learning PyTorch Flower Docker MLflow Healthcare AI Research Computing
👨‍🏫

Graduate Teaching Assistant

University of South Florida · Tampa, FL
Jan 2026 — May 2026
  • Mentored 100–150 students in Python for Business Analytics, supporting data analysis, debugging, SQL, Excel, and analytical workflow development.
  • Guided students in responsible use of AI-assisted development tools, including Claude and GitHub Copilot, for Python analytics, workflow automation, and output validation.
  • Collaborated with faculty to support technical troubleshooting and improve analytics-focused learning environments.
Python SQL Excel AI-Assisted Development Analytics
🏥

Full Stack Engineer

University of South Florida · Client: Evara Health · Tampa, FL
Oct 2025 — Jan 2026
  • Designed and developed mobile and web-based healthcare applications using React Native, Python, FastAPI, and REST APIs to support real-time patient-provider communication and clinical workflows.
  • Developed secure backend services and API integrations connecting healthcare applications with structured clinical data workflows, ensuring reliable processing, data integrity, and scalable application performance.
  • Integrated Azure Cognitive Services and deployed Docker-based applications on Azure, supporting AI-powered transcription, multilingual communication, integration testing, and HIPAA-conscious software delivery.
React Native FastAPI REST APIs Docker Azure Healthcare Applications
🏢

Software Engineer

Accenture · Hyderabad, India
Jan 2023 — Aug 2024
  • Developed scalable enterprise web applications and backend services using React.js, TypeScript, Node.js, Python, FastAPI, and REST APIs to support secure, distributed business applications.
  • Designed and optimized PostgreSQL and MySQL data models using indexing, normalization, query optimization, and data validation techniques to improve application performance, reliability, and data integrity.
  • Built backend APIs, integration services, and server-side automation supporting secure data exchange, workflow automation, cross-system communication, testing, and application maintenance.
  • Applied structured software engineering practices throughout the SDLC, including requirements analysis, system design, code reviews, testing, CI/CD, release management, Agile delivery, and production support using AWS, Git, Jenkins, and automated deployment pipelines.
React.js TypeScript Python FastAPI PostgreSQL MySQL AWS Jenkins

Academic Work

Research & Publications

My research focuses on privacy-preserving healthcare AI, federated learning, adversarial robustness, and reliable machine learning workflows for decentralized medical data.

✓ Presented · WITS 2025

Distinguishing Medical Diversity from Byzantine Attacks: Client-Adaptive Anomaly Detection for Healthcare Federated Learning

Workshop on Information Technology and Systems · Nashville, USA · 2025

Research-in-progress paper on distinguishing legitimate medical data diversity from Byzantine attacks in healthcare federated learning using client-adaptive anomaly detection.

Federated Learning Byzantine Robustness Healthcare AI Anomaly Detection PyTorch
⏳ In Progress · 2026

Extended Results: Client-Adaptive Federated Learning for Privacy-Preserving Healthcare AI

Target: IEEE Journal of Biomedical and Health Informatics

Extending the WITS 2025 research with broader healthcare dataset evaluations, additional adversarial scenarios, and enhanced robustness analysis for multi-institutional federated learning systems.

Federated Learning Healthcare AI Robust ML Privacy-Preserving AI

Contact Me

Let's Build Healthcare AI Systems That Matter

I am open to Research Software Engineer, AI/ML Engineer, Healthcare Software Engineer, and backend/cloud engineering roles where I can build reliable software systems for research, clinical data workflows, and AI-driven applications.

✉
Email raghuramkomara2929@gmail.com
→
☏
Phone (813) 568-3363
→
LinkedIn /in/raghu-ram-komara
→
GitHub raghuramkomara2906
→

MedLingo — Demo

▶

Video demo coming soon.

Drop your YouTube or Loom link and I will embed it here.

Project Preview

Drop project preview images in images/projects/ — filenames shown on each slot.

WITS 2025 — Paper Draft

⬇ Download PDF