Senior engineering leader responsible for creation and execution of multi-year strategy for 800-person software engineering organization encompassing five distinct technical domains: AI/ML applications, simulation and training solutions, cloud-based logistics systems, and embedded support devices. Includes planing and overseeing execution of multi-million dollar annual budget for key software innovation projects and product advancements both domestically and internationally. Lead core team responsible for the organization-wide transition to modern CI/CD ecosystem and the adoption of standardized software metrics and design practice while measuring and monitoring impact.

-Lead Software Architect, Autonomous Vehicle Platform-Oversaw software system architecture for a fully autonomous vehicle platform. Responsible for delivery of: sensing/safeguarding solution, algorithm development, machine job performance, detailed controller and subsystem interfaces, user experience, data ingress pipelines, and full system integration. Vehicle solution successfully complete proof of concept stage and began transition to production development.-Autonomy and Automation Leadership Staff Member-Provided technical guidance on software and hardware initiatives including product roadmaps, sensor component selection, and common software architectures for cross application use. Identified critical long-term technologies to be targeted for R&D, partnership, or acquisition. Given the significant shift autonomy represented to the company, I worked closely with business leadership to adopt new solution paradigms and business models.Helped plan and execute three-year growth strategy increasing engineering staff from 15 to 75 while expanding from two product lines to ten. Expansion required new sub-team hierarchy, redefined code ownership, new engineering practices, communication workflows, and driving effective developer discipline. Continually mentored junior and senior engineers. Most importantly, fostered an inclusive collaborative culture where each team member was empowered to question, challenge, and grow. Served as a leading member of technical recruiting team and employee retention committee member for the broader John Deere software engineering division.

-Automation and Autonomy Organization Technical Leader-Provide technical advisement to various product teams in the areas of: sensing modality selection, algorithmic solutions, machine learning approaches, software pipelines, systems architecture, robust system design, data collection, and verification methodology. Advisement also includes program level objectives: program scope, schedule, budget, risk identification, and team member assignment.I guided team growth and structure planning, expanding from a single to multiple engineering teams. Formed and lead a committee of developers to review and improve organization’s common architecture planning, technical communication methods, and software integration processes.Most importantly, I continually mentored and cross trained junior and senior engineers. Watching these individuals grow and in turn build a stronger team was one of the real joys of this role.-Lead Engineer/Technical Lead-Responsible for complete product delivery of deep learning-based image classification (semantic segmentation) system. System is deployed to combine harvesters leveraging a low power embedded edge-compute platform. I coordinate a diverse set of interdisciplinary teams including: Perception and Machine Learning, Core Software, Data Logging, Reprogramming, Hardware Engineering, Product Verification/Validation, DevOps, and Factory Integration. Developed field testing, data collection, and verification plans. Regularly communicated progress, risks, and issue mitigation plans to leadership. I led the redesign of a bespoke camera solution, specifically illumination and reflection design to ensure camera met image quality requirements. Additionally, I developed an advanced camera verification process implemented with our camera supplier.The final product represents the first deep learning-based product for John Deere. Most notably, the product received a CES Honors Award in the category of Robotics!

-Lead Software Engineer-Responsible for software delivery of an embedded image classification product leveraging deep learning based semantic segmentation. Responsible for entire software system including feature planning, software architecture and integration, computer vision algorithm implementation, deep learning integration, data ingestion, and automated verification.I developed and successfully executed a plan to transition nearly all software development in-house. Internalizing these capabilities required expanding my technical depth as well as growing additional talent inside of my organization. In support of system development, I routinely conducted analysis of sensor data and performance logs to optimize algorithmic efficiency and drive performance verification.-Senior Developer for Automation and Autonomy Organization-As the senior most software developer in our larger org my technical leadership role grew quite rapidly. I contributed to the design of a new common software architecture used across multiple computer vision and automation applications. Provided technical leadership for our larger organization encompassing a core architecture team and several automation/computer vision product teams. Continually guided code and system architecture reviews. Helped plan SIL and HIL quality verification activities for both our common software architecture and several customer applications.Regularly engaged with our management on the topics of team and project structuring and growth, new employee recruitment, talent development, and actively mentored several interns and junior engineers.

Worked on the Machine Automation team developing advanced perception based automation products. Products range from autonomous vehicles to advanced sensing systems for automation. Primary Contributions:Technical advisor to our Sugar Cane Harvesting group. Responsible for ensuring the timely completion of a stereo vision based yield monitoring system. I helped to resolve robustness and quality shortcomings discovered shortly before product release. My role was multi-faceted, I coordinated a diverse team of engineers advising on technical and software delivery matters, performed data analysis, and general engineering design work.I worked extensively on our first-generation grain quality classification system. This system provides real time pixel-wise classification of grain material as it is harvested in the field. My role focused on the development and verification of the machine learning based image classification system at the core of the product. I redesigned a prototype ML training pipeline to improve throughput and refactored our ML model to improve inference execution on a low-cost embedded compute platform. I also conducted data analysis and experimentation to improve classification performance.Expanded the Perception Verification System to be an application-agnostic verification framework. The framework was leveraged across our organization to create specific verification systems for each product we developed. These verification systems are used to process large data sets for verification, analysis, testing, and development. This framework ultimately allowed engineering teams to guarantee customer performance and system robustness.Developed a stand-alone low cost cellular-connected perception data logging system including hardware selection, software system design, and supplier production design.I continued to act as an Agile Guide, helping to foster the adoption of relevant and effective software development processes and practices.

Member of the Automation Solutions team focused on developing perceptions system for autonomous vehicles. I was part of a distributed team with members at the National Robotics Engineering Center (NREC) at Carnegie Mellon. Worked with various sensing technologies including computer vision (monocular and stereo), LIDAR, and radar. Helped evaluate and improve sensor fusion algorithms and artificial intelligence/machine learning solutions.My primary technical contribution was the design and implementation of a Perception Verification System. The verification system facilitated the use of large data sets to rapidly verify the safety performance of the perception safety systems of multiple autonomous vehicle platforms. Additionally, it provided multi-faceted data visualization utilities improving analytics capabilities.Shortly after joining the team I identified numerous opportunities for team improvement and was placed into a Scrum Master role. I was able to successfully guide or our team to implementing a number of valuable practices including:Automated build systemsCode reviewsUnit test frameworksStandardized, robust, and repeatable release processStatic code analysis

There is not much like getting paid to build robots and teach students. Working out of the mobile robotics lab I spent most of my time developing fully autonomous and teleoperated robotic systems for demonstration and research.As a teaching assistant I taught a first semester programming lab to new students, assisted with CS101, and senior undergraduate robotics and artificial intelligence courses. Typically I covering a topic or two, graded far too many freshmen term papers, and generally made myself available to students to support them anyway that I could. I found teaching and helping other to learn to be very rewarding. Probably why I continue to mentor young students today.

I spent my summer between undergrad and grad school at Oxford University in the Astrophysics Department. I conducted research focusing on image analysis, classification, and artificial neural networks using a massive data set of telescope images of galaxies from the GalaxyZoo project. I developed an artificial neural network based image classifier that could accurately classify vast portions of our data set. This included a classification confidence factor for each data point. The major new contributions in this research were two fold: (1) development of an expert system using data on scales previously unavailable, (2) incorporating classification confidence based on multiple human classifications. At time of completion this was the most accurate classifier of telescope images of galaxies ever developed. This work was designed to help improve data pipelines for future telescope surveys. Final results were presented at the American Astronomical Society Conference in 2010 under the title “Training Artificial Neural Networks with Fuzzy Logic."

My second software dev role saw me step away from the corporate world and dive into grant-based work in academia. I was part of the team that helped the GalaxyZoo citizen science project mature into Zooniverse.org. I was part of an international team with remote members located at Oxford University. Our work was funded by a NASA grant (ROSES NNX09AD34G).If there was ever a way to jump into the web development scene this was it. I extended my SQL skill set, worked extensively with PHP, and deepened my love for Python. My primary contribution was redesigning the login system (backend and frontend). We utilized a hybrid software suite with a custom built site paired with a standard forum service. Each had separate login systems with differing user accounts and encryption algorithms. I unified the two login and encryption systems to share common accounts. The process was 99% automated requiring no user intervention successfully integrating ~225,000 user accounts.The other neat aspect of this job was working with some of the world's brightest astronomers, astrophysicists, and planetary scientists. The site we developed gathered data for these researchers. Understanding the scientific purpose and nuances of the data being gathered was critical to our success.

My first software development position. This was the role that indoctrinated me to quality focused development. Quality and correctness were paramount. The software I developed was used daily to make immediate business decision with significant financial impact. I was a member of the Logistics department. We were responsible for everything from raw materials purchasing all the way to selecting shipping locations for each product. An amazing 'first' role, I was spoiled having a fantastic manager, and it was here that I learned what a small well-aligned group of very talented people could accomplish. Most of my work focused around creating and supporting report generation utilities. I developed a large number of Microsoft .net applications, SAS reports, and became quite a SQL expert. I also worked on some specialized projects: I created an International Shipping System and served as a liaison between Logistics, IT, and suppliers. I spent several months developing a Dynamic Shipment Efficiency Modeling System. This was used to accurately model shipment handling for all of our 'non-beer' goods (shirts, hats, etc.). As a result we were able to restructure our business model and infrastructure resulting in several million dollars in savings.