Protein Experiment Control & Data System

A hands-on project on control and Data system integration with tech stack of

  • Python (FastAPI, aiokafka)

  • Kafka

  • Chart.js

  • Docker

  • Machine Learning (PyTorch / simple model)

  • Neo4j (still an issue)

Features

  • Simulated experimental protein signals (angle, intensity) as process variables

  • Integrated EPICS-style PVs to mimic hardware-level control interfaces

  • Built a Kafka-based streaming pipeline for real-time data flow

  • Applied a machine learning model for anomaly detection on incoming signals

  • Designed a FastAPI + WebSocket service to process and distribute data

  • Implemented a live dashboard for real-time monitoring and visualization

Code