Andrew King

Andrew King

resume

WORK HISTORY

2021

Senior Machine Learning Engineer

NextGen Federal

April 2021 – Present

Spearheading deep learning initiatives and the application of generative AI across diverse Air Force Weather contracts, which include the Global Synthetic Weather Radar (GSWR), the Commercial Weather Data Pilot for GSWR Lightning, and Contrail Formation Modeling.

Driving the research, development, and implementation of advanced machine learning models, inclusive of generative AI and diverse deep learning architectures such as CNNs, FCNs, GANs, and diffusion models.

Demonstrated expertise in applying models to diverse data modalities, with a particular emphasis on computer vision and natural language processing, to achieve superior results.

2019

Machine Learning Research Engineer

Leidos

Oct 2019 – April 2021

Acted as machine learning algorithm lead for a project in the geospatial intelligence domain. Utilized a variety of deep learning techniques such as sparse convolutional neural networks and LSTMs.

Acted as principal investigator for a machine learning research project in the radio frequency (RF) domain. Explored the use of region-based convolutional neural networks for signal detection and estimation.

Awarded the Leidos Innovation Center Award for Technical Excellence in the first quarter of 2020.

2018

Machine Learning Developer / Data Scientist

Ellucian

May 2018 – Oct 2019

Led machine learning research at Ellucian, delivering proofs-of-concept and deploying product enhancements in the higher education administrative space.

Collaborated with architects and developers to define, deploy, and refine the cloud services-based machine learning architecture at Ellucian.

Presented deep learning and computer vision research at a variety of workshops and venues to educate customers and fellow data scientists.

2017

Deep Learning, Graduate Research Assistant

University of Georgia – Visual and Parallel Computing Laboratory

May 2017 – May 2018

Conducted research as student lead on a deep learning project in conjunction with the Department of Marine Sciences. Exploring fully convolutional semantic segmentation architectures using underwater survey images from the Florida Keys for the purpose of mapping and tracking the coral reef.

Research was published in two CVPR papers and led to a top-1 classification accuracy of 88%, outperforming all previous models for this task.

2016

Lead Programmer, Graduate Research Assistant

University of Georgia – Virtual Environments Laboratory

August 2016 – May 2018

Used Unity and computer vision techniques such as photogrammetry to develop virtual environments that assisted research projects in medicine, advertising, and psychology.

2016

Lead Web Developer

Southern Virginia University

2013-2016

Developed a new, fully-responsive website for Southern Virginia University in an open-source content management system. Managed the design and implementation of the site, substantially decreasing development costs and saving the university thousands in yearly licensing and maintenance fees.

Mobile traffic increased from 29% to over 50% within six months after the launch of the new responsive site, a sign of a strong user experience for mobile users.

Assisted in growing a robust intern program, managing and training new web development interns to sustain in-house development.

2013

Communications Assistant

Southern Virginia University

2012-2013

Managed all content on the Southern Virginia University website and made regular changes to keep the site up to date.

2011

Apple Product Professional

CityMac Apple Store

2011

Conducted hardware and software repairs on Apple products as a technician and support professional.

2011

Assistant to the Office Manager

Sawtooth Software

2005-2007, 2010-2011

Worked as a receptionist, directing phone calls, answering questions, filing invoices, and performing other customer-service related tasks.

EDUCATION HISTORY

2018

University Of Georgia – 3.94 GPA

Artificial Intelligence – M.S.

Attained a master’s degree in Artificial Intelligence. Thesis explored fully convolutional deep learning architectures for semantic segmentation of image data. Coursework included a variety of topics including natural language processing, computer vision, deep learning, and advanced data analytics.

2016

Southern Virginia University – 3.87

Computer Science, Business Management – B.A.

Completed a bachelor’s degree with majors in both computer science and business management. Graduated with 162 credits in June 2016. Maintained a computer science major GPA of 4.0. Served as president and founder of the Southern Virginia University Robotics Club and as the chair of the Southern Virginia University ACM student chapter.

2013

University of Virginia – 4.0 GPA

Modern Hebrew

Completed 12 credits at the University of Virginia, studying Modern Hebrew in the Summer Language Institute intensive language program and received perfect marks.

DEVELOPMENT PROFICIENCIES

Python – Expert

Java – Experienced

C# – Experienced

C++ – Proficient

HTML5/CSS3/Javascript – Experienced

Flask – Proficient

PHP – Proficient

Pytorch – Experienced

Keras – Proficient

Apache Spark – Proficient

SciKit-learn – Experienced

statsmodels – Proficient

Pandas – Experienced

HuggingFace Transformers – Proficient

Dask – Proficient

SciKit-image – Experienced

OpenCV – Experienced

Weka – Experienced

LaTeX – Experienced

PROJECT PORTFOLIO HIGHLIGHTS

Scopi

A stereoscopic camera application for Android and iOS. With it, users take two perspective-offset photos that are automatically registered (aligned), cropped, and stitched using OpenCV (C++ interface) to create a stereoscopic photograph for viewing in VR.

Adrix

A vicuna based LLM model integrated with a diffusion model for interactive image generation and conversational assistant capabilities all in one, accessible from the web via simple Quart based webserver and UI.

Deep Segments

A tool for generating ground truth images for use in deep learning semantic segmentation models. It provides a simple and fast method for researchers by leveraging unsupervised clustering of an oversegmented image.

Brew Counts

Developed an in-lab yeast analysis computer vision software to automatically determine and track yeast health metrics in conjunction with Grimm Artisanal Ales. Organized ground truth data collection and achieved 97% cell count accuracy and 95% health classification accuracy.

OTHER INTERESTS

Music

Classically-trained singer who has performed in a variety of productions including with the Port Angeles Light Opera and the Roanoke Symphony Orchestra. Completed 33 university-level credits in music.