Computer Vision Scientist - Consultant Resume - Hire IT People

SUMMARY:

Seasoned computer vision and machine learning scientist with outstanding success in building industrial strength commercial products that have been deployed around the globe. Experienced in transforming ideas into solutions and using deep learning to solve problems in the real world. Experience includes using convolutional neural nets (CNNs) for image classification and object recognition, machine learning for nuclear threat detection, in - image advertising, social media monetization, video scene recognition, content-based image retrieval (CBIR) systems, image feature extraction, biometrics, optical character recognition (OCR), and license plate recognition (LPR). Product-centered industry professional with the ability to convey complex ideas to customers and other non-specialists. Up-to-date on the latest developments published in scientific journals. Exceptional ability to interact and collaborate with other scientists and engineers for a seamless transition from prototype to the final product.

PROFESSIONAL EXPERIENCE:

Confidential

Computer Vision Scientist - Consultant

Responsibilities:

Performing R&D in computer vision and machine learning.
Applied semantic segmentation to process video from in-patrol cameras.
Object recognition using convolutional neural networks.
Researched license plate recognition, make and model recognition, and other technologies to incorporate into our product.
Implemented algorithms in C++ under Linux.
Extensively used the Caffe framework and NVIDIA DIGITS.

Confidential

Computer Vision Scientist - Consultant

Responsibilities:

Designed and implemented algorithms for detecting hazmat placards and bolt seals on cargo containers using deep learning (convolutional neural nets).
Implemented a CNN + SVM anomaly detector.
Implemented convolutional neural nets to determine cargo container door direction. This made the company the leader by far in performance for this service in the industry.
Provided solutions to increase the cargo container identifier OCR accuracy to meet client requirements and product specifications.
Implemented algorithms in C++ under Windows.
Extensively used the Caffe framework and NVIDIA DIGITS.

Confidential

Sr. Computer Vision Scientist

Responsibilities:

Led and managed research and development efforts for the computer vision team.
Patented a computer vision and deep learning framework in C++.
Implemented deep learning capabilities for image classification, video scene recognition, in-image advertising, and automatic image hashtagging for social media monetization.
Implemented Visual Search for garment e-commerce platform.
Implemented an automated video tagging system.
Designed and developed algorithms to detect improvised explosive devices (IEDs) for route clearance.
Participated in meetings to showcase product developments efforts to investors.

Confidential

Sr. Imaging Scientist

Responsibilities:

Developed algorithms and software to enhance nuclear threat detection capabilities of the muon tomography system using Support Vector Machines (SVM).
Developed in Python and C++ tools for data visualization that helped determine errors in the capture system.
Actively performed data analysis for system performance enhancement.

Confidential

Senior Software Engineer

Responsibilities:

Provided algorithm development for the Digital Pathology capabilities.
Implemented algorithms for automatic camera gains adjustment.
Designed algorithms to perform tissue segmentation on glass slides using morphological operators.
Implemented focus point localization algorithm to improve auto-focus capabilities on brain tissue.

Confidential

Imaging Scientist

Responsibilities:

Performed research and development to solve problems across the entire Security & Transportation Technology business unit.
Designed and implemented a C++ computer vision library that is being used in all product lines.
Designed and implemented the "Next Generation" OCR engine for recognizing license plates, cargo container and chassis' IDs.
Next Generation OCR engine allowed for 95% accuracy, enabled products to meet contractual rates, and contracts to be closed.
Implemented the Easy Match product for the VACIS XPL scanner which provides contraband-detection capabilities. Method based on nonlinear image registration of X-Ray images. Patent is pending for this product.

Confidential

Software Engineer

Responsibilities:

Performed research and developed computer vision solutions to solve law enforcement and biometric problems, such as in visual information retrieval of scars marks and tattoos (SMTs), iris segmentation and iris detection from a distance.
Headed the company's Law Enforcement software certification efforts with the California Department of Justice (CALDOJ).
Led company's certification efforts with the Federal Bureau of Investigations (FBI) of different hardware devices. (Fingerprint scanners and printers.)
Actively engaged in software design, development, testing, and trouble-shooting of the Law Enforcement software product.

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