Python libraries (pandas, trimesh, plotly, meshlab, PyTorch Geometric) plus 3D and simulation workflows: mesh autoencoders, SDF, and FEM data.
Core Expertise
Computer Vision
Object detection, instance segmentation, industrial image understanding, field-condition evaluation, and visual inspection workflows.
Data-Centric AI
Dataset design, annotation strategy, class balancing, failure-case analysis, and iterative model improvement.
AI Systems
End-to-end pipelines, workflow integration, production-oriented design, validation logic, and deployment planning.
Multimodal AI
Vision-language workflows: semantic retrieval, document/PDF understanding, and structured extraction from mixed media.
Deployment
CoreML, Swift/iOS integration, on-device inference, model export, and mobile visualization prototypes.
Scientific ML
FEM surrogate modeling, 3D deformation learning, mesh autoencoders, implicit representations, and RL for process modeling.
Skills
PyTorch, TensorFlow, and scikit-learn for model development, plus computer vision: detection, segmentation, industrial imagery, preprocessing, and evaluation.
Frameworks
Docker and Podman environments, conda, Linux, Git, Jenkins, Jupyter, n8n automation, Hermes-based local model workflows, multimodal RAG, and document/PDF understanding.
MLOps & Workflow Tools
OOP and languages including C#.NET, C++, MATLAB, and Python; deployment with CoreML, Swift/iOS, on-device inference, and model export.
Programming & Deployment
AI-assisted engineering workflows for prototyping, coding, debugging, and research acceleration with modern editor and agent tooling.