AI engineer with hands-on ML experience and a strong sensor-fusion focus: SDR / RF (HackRF, Airspy, RTL-SDR, Whisper-on-signal), BLE behavioural analysis, wearable health-sensor pipelines, multi-face computer vision, and real-time inference on noisy, adversarial data. Comfortable owning experimental ML work end-to-end — from research and benchmarking through to production deployment in Linux / Docker environments.
Technical Skills
Languages
Python (primary) · JavaScript / TypeScript · SQL · Kotlin / Java (Android) · Familiarity with C / C++ and Go
MediaPipe-based gesture / hand / face tracking pipelines · Servo control (FEETECH ST-3215-C047) on InMoov i2 robotic hand · SO-ARM101 robot arm with MuJoCo simulation + imitation learning · 3D printing for drones, cinewhoops, payload grabbers, perching legs
Multi-layer software-defined-radio intelligence stack: captures RF across UHF/VHF/HF/marine/aviation bands, demodulates in real time (WFM/NFM/AM/SSB), transcribes voice traffic with faster-whisper on AMD ROCm, extracts entities (callsigns, locations) and archives everything into a searchable SQLite/FTS5 database. The DSP core was extracted into a standalone library (rfai-dsp) with anti-alias decimation, phase-continuous VFO mixing and an abstract SDR backend.
Android BLE scanner with device fingerprinting, GATT explorer and Claude AI analysis
Advanced Android BLE scanner: device fingerprinting, GATT explorer, signal traces over time, behavioural pattern detection (proximity, dwell, repeat encounters), and built-in Claude AI analysis of captured BLE data.
Real-time computer-vision pipeline for smart-glasses use cases: MediaPipe Face Mesh (468 landmarks), ArcFace recognition, multi-face tracking at 30fps with a persistent identity library — all in-browser. Ships custom-trained 'Folkus' demographic models (2.3 MB INT8 ONNX, running via ONNX Runtime Web) that beat commercial APIs: gender 92.1%, age 5.37y MAE, ethnicity 72.2% across 7 groups. Camera glasses stream to a host computer that recognises faces and feeds AI context back via phone.
Heart rate, HRV and SpO₂ from a webcam — 100% in-browser rPPG
Browser-based remote photoplethysmography pipeline extracting heart rate, HRV, SpO₂ and stress indicators from regular webcam video. No wearable required — pure signal processing on a noisy real-world input.
Stack: JavaScript · rPPG · Signal processing · Browser ML
On-device voice-AI stack — TTS, STT and round-trip evaluation
Local voice stack for the qalarc AI-OS: TTS, STT, voice-cloning experiments and a round-trip evaluation harness covering radio-protocol-style edge cases.
