Personal portfolio website showcasing my work as a Data Engineer specializing in Python, SQL, AWS, and API Development.
🔗 Live Site: snaidu20.github.io
I'm a Data Engineer working in healthcare, focused on making complex clinical and device data reliable, accessible, and useful for better decisions. Currently working at Upsilonsoft LLC (Client: Bristol Myers Squibb) on IoT-enabled patient vitals streaming and early-risk detection systems.
Tech Stack: Python | SQL | AWS | API
AI & Medical Imaging • 2026
- Developed an AI-powered chest X-ray analyzer using Google's MedGemma foundation model
- Auto-detects imaging modality and generates detailed radiology reports
- Reports are tailored for both clinicians and patients
- Deployed via GPU-backed cloud environments for real-time inference
- Tech Stack: Google MedGemma, Medical Imaging, AI/ML, Radiology, Cloud GPU
- 💻 GitHub & Demo Video
AI & Healthcare • 2025
- AI-powered system that matches patients to suitable clinical trials
- Analyzes patient data (age, diagnoses, lab results) against active trials from ClinicalTrials.gov
- Uses machine learning and semantic search to rank trials by predicted eligibility
- Provides explainable reports to support physician decision-making
- Automates trial matching to speed up enrollment and connect patients with life-saving treatments
- Tech Stack: AI/ML, NLP, Semantic Search, Healthcare
- 💻 GitHub
Published Research • 2020
- Designed IoT irrigation system using sensors and wireless communication
- Optimized water flow based on real-time soil moisture data
- Unique approach using Solenoid valves integrated with sensor data to control water supply directly (turning ON/OFF water supply rather than motor)
- Tech Stack: Arduino, Sensors, IoT
- 📄 Read Publication
Supply Chain Analytics • 2026
- Developed system tracking real-time global availability of critical part numbers
- Aggregates data from open market sources (TrustedParts, FindChips)
- Combines with internal demand signals to compute Demand Pressure Index
- Guides procurement decisions: buy, hold, delay, or expedite
- Enables proactive and data-driven supply planning
- Tech Stack: Power BI, Python, Analytics, API
- 📊 Dashboard | 💻 GitHub
Web App Development • Security • 2022
- Secure attendance system verifying physical presence through GPS
- Matches student and faculty locations with time-based passcode
- Prevents proxy and remote check-ins
- Tech Stack: GPS, Mobile Development, Security, Authentication
- 🎥 Demo & Docs | 💻 GitHub
Healthcare IoT • Bristol Myers Squibb
- Building real-time data pipelines for medical device streams
- Early-risk detection and patient monitoring
- Tech Stack: AWS, Medical IoT, Real-time, Healthcare
Cloud Migration • Progress Solutions
- Migrated on-prem datasets to cloud (AWS S3/Azure)
- Built automated ETL pipelines
- Reduced pipeline run times by 40%
- Tech Stack: AWS S3, PySpark, ETL, Azure
- Languages: Python, SQL, Scala, PySpark
- ETL: Informatica, Collibra, Custom Pipelines
- Big Data: Apache Spark, EMR
- AWS: S3, EMR, Lambda, Glue
- Azure: Blob Storage, Data Lake
- Certifications: AWS Certified Data Engineer - Associate
- Hardware: Arduino, Raspberry Pi
- Medical IoT: Patient Vitals Monitoring, Sensor Integration
- Real-time Streaming: Healthcare Device Data Pipelines
- BI Tools: Power BI, Excel
- Data Governance: Informatica, Collibra
- Analytics: Predictive Modeling, Statistical Analysis
May 2025 – Present
- Analyze large-scale patient & IoT-healthcare data for clinical workflow improvements
- Build data pipelines ingesting sensor-driven medical device streams
- Collaborate on connected health system initiatives with device telemetry
- Develop automated insights for smarter diagnostics and patient-care decisions
Jun 2024 – May 2025
- Migrated multiple on-prem datasets into cloud data lake (AWS S3/Azure)
- Built automated ETL pipelines using Python, SQL, and PySpark
- Reduced pipeline run times by 40% through optimization
- Implemented schema evolution and metadata tracking
Apr 2021 – Jul 2022
- Designed dashboards showing system health and workflow bottlenecks
- Developed predictive model for identifying overload conditions
- Implemented automation reducing processing time by 30%
- Integrated data signals from multiple internal systems
Florida Atlantic University | 2024
- Internet of Things, Artificial Intelligence, Deep Learning
- NLP, AI in Healthcare, Information Theory
- Systems & Network Administration
Anna University | 2020
- Wireless Communication, Antenna & Wave Propagation
- Microcontrollers, Embedded Systems, Signal Processing
- ☁️ AWS Certified Data Engineer - Associate
- 📊 PMP - Project Management Professional
- 📈 Power BI (Pragmatic Works)
- 🤖 AI Foundations: Thinking Machines (LinkedIn Learning)
- 💰 Financial Modeling & Forecasting (LinkedIn Learning)
- 📊 Career Essentials in Business Analysis (Microsoft & LinkedIn)
- 🔌 2 Published IoT Research Projects
- 📊 40% Pipeline Runtime Optimization
- ☁️ AWS Certified Data Engineer
- 🎓 6 Professional Certifications
- 📧 Email: snaidu2022@fau.edu
- 📱 Phone: +1 912-306-7209
- 💼 LinkedIn: linkedin.com/in/reddysaiu
- 📍 Location: Winder, Georgia, US
This portfolio is built with:
- Frontend: HTML5, CSS3 (Vanilla)
- Hosting: GitHub Pages
- Design: Custom responsive design with modern CSS
- Features: Smooth scrolling, responsive navigation, project showcase
© 2026 Saikumar Reddy Naidu. All Rights Reserved.
Last Updated: April 2026