Dr. Gregory G. Vilensky

Applied Mathematician & Computational Physicist

Executive Profile

I specialize in transforming complex mathematical physics and artificial intelligence into secure, high-precision software solutions for the medical and MedTech industries. Backed by an international career in advanced research and development, I design next-generation technologies that enhance clinical capabilities and improve patient outcomes. My work focuses on three core pillars: building secure, completely offline AI assistants for clinical decision support, developing high-resolution 3D medical imaging and automated organ mapping tools, and creating advanced software simulations for non-invasive therapies like therapeutic ultrasound (HIFU). I bridge the gap between breakthrough scientific innovation and reliable, market-ready medical technology.

Key Technical Deliverables

Generative AI & RAG Engineering

  • Architected end-to-end pipelines powered by LLMs, transformers, and vector databases to build expert clinical decision support systems (CDSS).
  • Engineered entirely to run locally on low-overhead hardware. To protect corporate IP weights and enforce strict privacy, the core model execution loop operates exclusively offline under a zero-trust architecture.
3D imaging and CT reconstructions
Fig 1. Clinical AI environment with 3D visualization.

Medical Ultrasound & Therapeutics (HIFU)

  • Designed non-invasive modeling platforms for high-intensity focused ultrasound ablation targeting deep tumors without damaging surrounding tissue matrix elements.
  • Solved non-linear sound propagation anomalies and acoustic dispersion profiles across highly heterogeneous soft anatomical structures.
⚡ View Mathematical Framework
∂θ { 2∂X P − ∂θ ( BP2 + ∫₀∞ (Pr(τ) / τ) dτ ) } = Δ⊥ P,
∂θ Pr + ∂τ Pr = σ(τ) ∂θ P, Δ⊥ ≡ ∂2/∂y2 + ∂2/∂z2.

Field equations for calculation anomalous acoustic absorption using fractional dynamics and memory-dependent structural parameters.

Clinical Devices Overview
Fig 1. Real-world medical hardware configurations employing automated acoustic modeling.

Advanced Computer Vision & 3D Imaging

  • Building highly GPU-optimized heterogeneous C++ libraries for autosegmentation, 3D reconstruction, and automatic internal organ geometry correction using CT/MRI scans.
  • Deployed specialized neural network architectures including U-Net and SegResNet variations for automated volumetric analysis.
3D imaging and CT reconstructions
Fig 2. 3D mapping and CT reconstructions.

Project Inquiries