Applied AI research · Medical imaging · Computer vision · Real-time inference · High-performance systems
See our work
Research-grade pipelines for medical imaging and biosignals.
✓ Imaging & signal analysis: chest X-ray, ECG, and multi-modal workflows
✓ External validation: distribution shift, robustness, and interpretability
✓ Reproducible protocols: from training to evaluation
Built to hold up under scrutiny, not just on curated benchmarks.
Vision systems for detection, segmentation, tracking, and 3D understanding.
✓ Object detection & segmentation: YOLO, SAM, and custom architectures
✓ 3D reconstruction and geometry-aware pipelines
✓ Multi-modal perception: video, depth, and sensor fusion
From controlled experiments to deployable prototypes.
Low-latency audio pipelines and real-time AI systems.
✓ Streaming ASR/TTS and live translation workflows
✓ Tool-using AI workflows for real-world tasks
✓ Optimized inference for consumer-grade GPUs
Designed for latency, continuity, and practical use.
Making advanced models run efficiently on limited hardware.
✓ GPU memory optimization and throughput tuning
✓ Quantization & accelerated inference: INT8/INT4, GGUF, TensorRT
✓ Edge deployment: Jetson, embedded devices, and on-device AI
Because research matters more when it actually runs.
Open-source chest X-ray classification system with rigorous evaluation under distribution shift.
✓ DenseNet121 · independent models per pathology
✓ Explicit Split / Valid / Test protocol + external validation (PadChest)
✓ Grad-CAM validated against CheXlocalize
Open-source research project for 12-lead ECG classification, combining signal modeling, external evaluation, and explainability analysis.
✓ 12-lead ECG classification with explainability analysis
✓ Noise preprocessing and signal quality filtering
✓ Part of the XAND open-source medical AI research line
Simultaneous translator for YouTube, audiobooks, and live streams. Optimized for consumer hardware.
✓ Target latency 2–3 s end-to-end
✓ GPU-optimized pipeline (RTX 4060 Ti 16 GB)
✓ Quality + performance balance as design constraint
R&D project on multimodal sign language ↔ speech translation using computer vision and language models.
✓ Sequential hand and gesture modeling
✓ Vision + language + speech synthesis integration
✓ Focused on accessibility and inclusive communication