Computer Vision Engineer

Building perception systems for noisy, real-world imagery — from inspection research and imaging workflows to object detection, remote sensing, dataset engineering, and model evaluation.

Inspection R&D · object detection · dataset engineering · image processing · evaluation & experimentation

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See my work

Featured Project

Maritime Vessel Detection

Oriented Object Detection for Remote-Sensing Imagery

An audit-driven remote-sensing detection workflow built around DOTA v2.0, xView, and HRSC2016-MS. The work emphasizes annotation quality, parent-space coordinate handling, OBB conversion, tiling, curation, controlled augmentation, and multi-seed evaluation.

0.7067

mAP50-95

0.9567

Precision

0.8620

Recall

1280 px

Input

YOLO11m-OBB

Model

175+ hrs

Curation

Selected YOLO11m-OBB result from a curated 1280 px workflow with audit-driven data preparation and controlled experiments.

Workflow and stack

Computer Vision · Object Detection · Oriented Bounding Boxes · YOLO11m-OBB · Ultralytics · Satellite Imagery · Aerial Imagery · Dataset Curation · Annotation QA · Dataset Tiling · Mask <-> OBB Conversion · SAM-Assisted Labeling · Multi-Seed Evaluation · SvelteKit Demo · Deployment-Ready Inference

View Case Study Open Interactive Demo

Annotated Raspberry Pi board showing component, marking, board-text, symbol, and association detections.

Collaborative Project

PCB Inspection & Board Understanding

Technical walkthrough of computer vision workflows for PCB inspection and board understanding. Using representative board imagery and recreated examples, this article breaks the problem into component detection, marking recognition, OCR, reference-designator association, and automated bill-of-material extraction.

Automated Optical Inspection / Component Recognition / OCR / Bill-of-Materials Extraction

Read technical walkthrough

Experience

Computer vision research, inspection systems, dataset engineering, and customer-facing product work.

Oct 2022 - Oct 2024

Caspia Technologies

Research & Development Engineer
Gainesville, FL
Applied CV/R&D role focused on PCB and microelectronics inspection, AutoBOM and counterfeit-detection research, dataset engineering, and technical delivery.
- Contributed to AutoBOM and counterfeit-detection R&D programs that converted PCB imagery into structured component, marking, text, orientation, and inspection metadata through computer vision, OCR, classification, and visual-association workflows.
- Developed and supported PCB inspection subsystems including YOLO-based integrated-circuit detection, surface-mount component classification, board/component-marking recognition, OCR/orientation workflows, and component-to-reference-designator association.
- Expanded a PCB vendor-logo and marking dataset to ~7,000 instances across ~1,300 marking types and contributed to ~300,000 total manual annotations spanning components, markings, text, orientation, reference-designator relationships, and OCR-support metadata.
- Investigated counterfeit and defect-detection approaches under severe data scarcity, including synthetic-data augmentation experiments and image-based surface inspection workflows for microelectronic components.
- Authored an independent ~40-page multimodal inspection feasibility study covering SWIR, infrared, X-ray, and other sensing methods; helped justify acquisition of a high-end SWIR imaging system and established initial experimental PCB imaging workflows.
- Produced weekly technical presentations and monthly SBIR-style deliverables documenting model development, dataset status, technical risks, and project milestones; onboarded and coordinated junior engineers across Physical Assurance R&D workstreams.
- Served as NSF I-Corps Entrepreneurial Lead for a seven-week commercialization program, conducting 100+ stakeholder interviews across electronics manufacturing, inspection, procurement, recycling, and supply-chain security.
Computer Vision / Industrial Inspection / Object Detection / OCR & Text Analysis / Dataset Engineering / Hardware Assurance
May 2021 - Oct 2022

Florida Institute for Cybersecurity Research

Research Assistant
Gainesville, FL
Hardware-assurance research foundation in PCB inspection, image processing, dataset construction, and ML experimentation.
- Supported early hardware-assurance and PCB inspection research that later expanded into AutoBOM and counterfeit-detection workstreams, contributing across dataset construction, annotation, image processing, and machine-learning experimentation.
- Developed PCB image auto-scaling and resolution-estimation workflows using reference-object detection, PCB boundary detection, edge/contour analysis, and known physical-reference geometry to estimate image PPI under inconsistent capture conditions.
- Built the initial PCB vendor-logo and marking dataset, curating ~3,000 examples across ~800 marking types for downstream vendor-logo, standards-marking, and board-marking recognition.
- Produced ~70,000 PCB annotations across components, markings, and text-related metadata, including localization, orientation, and class labels.
- Explored GAN-based synthetic counterfeit/defect generation for hardware-assurance datasets, identifying scarce confirmed negative examples and high visual variability as primary limitations to usable augmentation.
Computer Vision / Image Processing / Hardware Assurance / Dataset Development / Visual Inspection / ML Experimentation
Jul 2018 - Aug 2021

Admiral

Account Development Representative → Customer Success Representative
Gainesville, FL
Earlier SaaS customer-facing experience in outbound sales, customer success, issue resolution, and account communication.
- Supported outbound sales, customer success, issue resolution, and account communication for a SaaS platform serving digital publishers.
- Built early experience translating customer needs and product issues between users and internal teams.
SaaS / Customer Success / Commercial Communication

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Skills

Tools used across model development, annotation, evaluation, and deployment.

Computer Vision Tasks

Object DetectionImage ProcessingOCR and Scene Text DetectionFeature Extraction & AssociationAnomaly DetectionImage SegmentationTraining & Inference Optimization

Models and Frameworks

PyTorchOpenCVUltralytics YOLOSAM-Assisted LabelingTesseract, EAST, and CRAFT

Data and Experimentation

Dataset CurationAnnotation QAOriented Bounding BoxesSegmentation MasksTiling PipelinesExperiment Design / Ablation TestingDomain-shift Analysis

Deployment and Engineering

PythonDockerFastAPSvelteKitONNX RuntimeGitLinux

Education / Technical Training

Formal business education and continuing technical study in computer vision and machine learning.

University of Florida · Gainesville, FL

B.S. Business Administration, Management; Minor in Entrepreneurship

May 2020

Business and commercialization background supporting technical delivery, customer discovery, and applied AI strategy.

Technical training

Computer Vision & ML

Computer Vision Specialization - University of Colorado Boulder
PyTorch for Deep Learning - DeepLearning.AI
Deep Learning Specialization - DeepLearning.AI
Machine Learning Specialization - Stanford/DeepLearning.AI
Mathematics for Machine Learning - Imperial College London
Python for Everybody - University of Michigan
Statistics with Python - University of Michigan

About

Applied computer vision for physical-world imagery.

I work on computer vision problems involving noisy, real-world imagery, with a background in PCB and microelectronics inspection, hardware assurance, dataset engineering, image processing, OCR, and applied ML research. Much of that work involved imperfect data, inconsistent imaging conditions, annotation quality, limited examples, and the need to evaluate practical tradeoffs rather than optimize against clean benchmark datasets.

I am especially interested in applied computer vision areas such as remote sensing, inspection, monitoring, object detection, and other perception-focused problems where data quality and evaluation matter as much as model selection. My broader background in business, customer discovery, and technical delivery also influences how I approach engineering work: with attention to the problem being solved, the constraints around it, and whether the resulting system is actually useful.

Contact

Open to applied vision, imaging, and machine-learning engineering roles.

Computer vision work grounded in real imagery

I am seeking Computer Vision Engineer, Applied ML Engineer, Machine Vision Engineer, Geospatial CV Engineer, and AI/Imaging Solutions roles. I am open to remote work and relocation, with particular interest in defense, aerospace, geospatial imagery, electronics inspection, drones, satellites, and other physical-world systems.

Based in Florida; Open to Remote and Relocation.
U.S. Citizen; Clearance Eligible.

Resume Concise professional experience and technical summary Full CV Full professional chronology, training, and background LinkedIn Professional profile and direct messages GitHub Code, experiments, and public repositories