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Skills

  • MS Office
  • Business analysis
  • Cross-functional team leadership
  • Firewalls, VPNs and security products
  • Anomaly detection using unsupervised learning
  • Business operations
  • Team management
  • Process improvement
  • Anomaly detection in video surveillance
  • Customer proposals

Work Experiences

  • Oversaw the delivery of program project by framework team, which resulted in method.
  • Achieved early recognition rates of 62%.
  • Defined enterprise processes and best practices, as well as application-specific enterprise processes.
  • Involved in all phases of the system development life cycle from requirements analysis to system implementation.
  • Was in charge of the organization's computer systems and intranet development and maintenance.
  • Achieved 80% improvement through optimized network streaming protocols.
  • Transported SAP to 18 months customer locations.
  • Created and maintained a network infrastructure that included Windows, Linux, and virtualization.
  • Analyzed large datasets of video footage to improve anomaly detection, achieving early recognition rates of 38%.
  • Resolved issues with LAN, WAN, and voice system operational components.

Summaries

  • Creative and collaborative Computer Vision Engineer.
  • Computer Vision Engineer focused on enhancing model explainability through Grad-CAM visualizations. Improved stakeholder confidence by showcasing transparent, interpretable AI outputs crucial to key decision-making processes.
  • Adept Computer Vision Engineer with strong background in object detection and deep learning. Delivered a 68% increase in model accuracy and drove successful implementation of vision-based features in Miscellaneous.
  • Computer Vision Engineer with 17 years of successful vendor management and cross-functional collaboration experience.
  • Created advanced face recognition systems.
  • Creative and collaborative Computer Vision Engineer with experience in building performance-optimized machine learning pipelines. Cut model training time by 27% and achieved a 20% increase in development productivity.
  • Adept at leveraging deep learning techniques.
  • Computer Vision Engineer with expertise in edge computing.
  • Achieved 56% improvement in model iteration speed.
  • Accomplished Computer Vision Engineer proficient in human pose estimation and anomaly detection. Boosted detection accuracy by 50% and contributed to early recognition efforts in diverse real-time environments.

Accomplishments

  • Developed a landmark-based facial tracking system, reducing tracking drift and improving feature accuracy by 32% in AR applications.
  • Used Microsoft Excel to develop inventory tracking spreadsheets.
  • Collaborated with team of 9 in the development of program.
  • Improved the accuracy of facial recognition models for standard by 29%, enhancing software reliability in security applications.
  • Engineered an ML-driven image colorization system capable of reducing manual correction efforts by 72%.
  • Resolved product issue through consumer testing.
  • Integrated CUDA-based hardware acceleration for large-scale image processing, improving computational speed by 23%.
  • Collaborated with stakeholders in product design to implement computer vision features that improved end-user satisfaction ratings by 73%.
  • Designed modular computer vision pipelines for different imaging types, reducing integration time across projects by 60%.
  • Implemented automated defect detection within Miscellaneous using OpenCV, reducing quality inspection time by 36%.

Affiliations

  • Certification holder, NVIDIA Deep Learning Institute, CUDA Programming and GPU Acceleration, 2022
  • Member, Computer Vision and Pattern Recognition (CVPR) community, focusing on traffic sign detection models, 2019
  • Certification in Cloud Machine Learning Engineering from framework, 2019
  • International Association of Administrative Professionals
  • Society of Human Resource Management
  • American Marketing Association
  • Peer reviewer, Journal of Machine Learning Research (JMLR), specializing in novel image recognition models, 2015
  • Lecturer, IEEE Conference on Computer Vision Systems, focusing on advancements in vision systems for vehicular applications, 2018
  • Attendee, NeurIPS (Neural Information Processing Systems), focusing on advancements in edge case object detection, 2016
  • Volunteer instructor, process Deep Learning Bootcamp, teaching image preprocessing and augmentation, 2016

Certifications

  • NVIDIA Deep Learning Institute for Computer Vision Specialists Certification – Asana, 2021
  • Google Certified Professional Cloud Architect
  • Project Management Professional (PMP)
  • Certified Robotics Vision Engineer - Northwind, 2022
  • TensorFlow Developer Certificate - HubSpot, 2021
  • Certified Data Scientist in AI Specialization - Northwind, 2024
  • Certified Autonomous Vehicle Developer (CAVD) - Ironclad Systems, 2015
  • Certified AI Vision Engineer - Vantage, 2021
  • Edge AI and ML with Computer Vision Certification - Salesforce, 2016
  • Certified AI & Machine Learning Professional (CAIML) - Meridian

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