Davin Fausta Supriyadi
Mobile Developer Intern at PT. BPR Arto Moro & Applied Computer Vision Researcher.
Davin Fausta Supriyadi is a mobile, backend, and AI/ML engineer from Semarang, currently interning as a Mobile Developer at PT. BPR Arto Moro.
Edge AI & Perception
YOLOv11 & uncertainty estimation on NVIDIA Jetson Orin NX boards
Robotics Telemetry
ROS1 Noetic sensor fusion with LiDAR, GPS, and IMU point cloud pipelines
Native Mobile
Offline-first Flutter & Kotlin apps with SQLCipher zero-trust storage
System Architecture
FastAPI, Supabase PostgreSQL, and scalable microservices infrastructure
Engineering Ethos
“I believe reliable systems are built from the sensor to the screen. Good architecture does not hide behind mockups or buzzwords; it makes edge constraints clear, measures uncertainty honestly, and ships software that works under real-world conditions.”
Currently interning as a Mobile Developer at PT. BPR Arto Moro in Semarang, building internal applications with Flutter and Golang. Computer Engineering Technology graduate from Politeknik Negeri Semarang with research spanning edge YOLOv11 perception to autonomous vehicle telemetry.
Cumulative GPA
Politeknik Negeri Semarang · Informatics Engineering
Edge Compute Budget
Real-time model inference on NVIDIA Jetson Orin NX
Permissions in Runa
Enforced biometric & AES-256-GCM zero-trust security
Telemetry Fidelity
Deterministic LiDAR & IMU point cloud message dispatch
Work & Research
Mobile Developer Intern (Maganghub)
Sep 2026 - PresentBuilt new features in internal applications.
- Developed and implemented new features for internal applications using Flutter and Dart.
- Collaborated with backend teams to integrate REST endpoints in Golang.
Research Assistant - Autonomous Vehicle Perception System
Feb 2026 - Aug 2026Undergraduate thesis research supporting object detection for road safety scenarios using a custom 28-class dataset.
- Researched a YOLOv11-based autonomous vehicle perception system on a custom 28-class object dataset.
- Developed and evaluated YOLOv11 architecture modifications using an ASPP-based triple detection head, Feature Pyramid Network (FPN), and Path Aggregation Network (PANet).
- Applied Monte Carlo Dropout for prediction uncertainty estimation and analyzed mAP, precision, recall, model size, and inference latency against real-time requirements.
- Deployed inference to an NVIDIA Jetson Orin NX for edge evaluation.
Engineering Intern - Smart Mechatronics
Aug 2025 - Dec 2025Built operator tooling for an autonomous electric vehicle research platform.
- Built a real-time interactive dashboard for an autonomous electric vehicle, integrating ROS1 Noetic sensor streams (LiDAR, GPS, IMU) into a Flutter interface.
- Designed a data pipeline connecting live sensor feeds to the UI, enabling real-time vehicle status monitoring and visualization.
- Integrated the dashboard with the autonomous vehicle system to dispatch user-selected navigation goal points within the research test area.
- Researched end-to-end autonomous driving models on the nuScenes dataset, applying multimodal camera-LiDAR fusion through Bird's Eye View (BEV) representation.