Core Software Engineer | AI & ML Student
Bridging the gap between Physical Hardware, High-Performance Systems, and Neural Networks.

Currently building ScentLib, the global binary standard for digital olfaction. I transform electrical signals into molecular intelligence.

Core & Systems

AI & Data

Frontend & UI

The "VLC for Smells" – An Open-Source Ecosystem for Digital Olfaction.

• ScentLib Core: High-performance binary codec (.scent) and Python SDK.
• ScentPredictor: Graph Neural Networks (GNN) for molecular-to-odor prediction.
• Hardware: ESP32-based acquisition (ScentBox) & microfluidic synthesis (ScentOutput).

Explore ScentLib

• Binary Data Optimization: Packing 64-bit floats into float16 and custom binary streams for high-performance IoT.
• Molecular Graph Learning: Researching Graph Neural Networks (GNNs) for olfactory perceptual alignment.
• Embedded Performance: Real-time signal processing on ESP32, including Kalman filters and ADC noise reduction.