Saikumar Reddy Naidu

Developed an AI-powered chest X-ray analyzer using Google's MedGemma foundation model that auto-detects modality and generates detailed clinician- and patient-friendly radiology reports via a GPU-backed cloud environment.

TrialMatchAI is an AI-powered system that matches patients to suitable clinical trials. It analyzes patient data—such as age, diagnoses, and lab results—and compares it with active trials from ClinicalTrials.gov using machine learning and semantic search. The platform ranks trials by predicted eligibility and provides explainable reports to support physician decisions. By automating trial matching, it helps speed up enrollment and connect patients with potentially life-saving treatments faster.

Designed an IoT irrigation system using sensors, solenoid valves, and wireless communication to optimize water flow based on real-time soil moisture. This is a unique project where we use Solenoid valves integrated with sensors data to turn ON/OFF the water supply rather than turning OFF the motor directly.

Developed a system that tracks real-time global availability of critical part numbers by aggregating data from open market sources (e.g., TrustedParts, FindChips) and combining it with internal demand signals. The platform computes a Demand Pressure Index to guide procurement decisions such as buy, hold, delay, or expedite, enabling proactive and data-driven supply planning.

Built a secure attendance system that verifies physical presence by matching student and faculty GPS locations with a time-based passcode. Attendance is recorded only when both are co-located, preventing proxy and remote check-ins common in traditional and online systems.

Building real-time data pipelines that ingest sensor-driven medical device streams for early-risk detection and patient monitoring.

Migrated on-prem datasets to cloud, built automated ETL pipelines, reduced run times by 40% through optimization.