SAMARTH GUPTA

EXPERIENCE

INFOCENTRIC

Focused on backend performance engineering and distributed systems architecture, driving a 72% reduction in end-to-end service latency and designing event-driven microservices pipelines for scalable, fault-tolerant data processing.

  • Used JFR and .NET Trace to profile backend services under load, identifying CPU bottlenecks and concurrency hotspots across thread execution paths and shared-state contention points.
  • Improved parallel execution and reduced contention through multithreading and JVM garbage collection tuning, reducing end-to-end latency from 2 minutes to 33 seconds (72% improvement) while improving system stability under high concurrency.
  • Architected an event-driven microservices pipeline in .NET, orchestrating Docker containerised connector, parser, chunking, and analysis services via Redis-backed asynchronous job queues, enabling scalable and fault-tolerant data processing.
  • Leveraged Snowflake to build scalable data pipelines and query layered datasets, and developed interactive R Shiny dashboards to transform analytical outputs into stakeholder-facing visualisations for reporting and decision support.
.NET Docker Redis JFR Snowflake R Shiny JVM

MONASH UNIVERSITY

Working alongside clinical researchers with no software background, I took vague, high-level goals and turned them into a fully designed, production-grade application. That meant asking the right questions, understanding what they actually needed versus what they thought they needed, and making every design decision with the end user in mind.

  • Translated non-technical clinical requirements into a full system design for Respio, a cross-platform Flutter application for continuous respiratory monitoring, making architectural and UX decisions that aligned with how researchers and patients would actually use the product.
  • Architected and developed the real-time data ingestion layer, streaming physiological sensor data over Bluetooth Low Energy (BLE) at 500 Hz with minimal latency and no data loss across extended monitoring sessions.
  • Engineered a scalable cloud-backed data architecture using Firebase Authentication and Cloud Firestore to securely manage user identities and persist structured respiratory recordings.
  • Developed a document generation pipeline that converts recorded physiological signals into structured PDF health reports with statistical summaries and waveform visualisations, designed to be readable by clinicians without any technical background.
Flutter Dart BLE Firebase Cloud Firestore