Mark Sturdevant
TEB- Supervisor at Dassault Falcon Jet
New York City Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolMark Sturdevant is an operations and technical leader with 11 years of experience managing rapid-response teams in the aviation sector and hands-on engineering work in cloud-based AI projects. As TEB Supervisor at Dassault Falcon Jet he leads AOG/rapid-response efforts out of the NYC metro area, bringing field-tested decision-making and team coordination to high-stakes situations. Complementing his aviation career, Mark has contributed full-stack and DevOps improvements to notable IBM open-source projects—integrating Watson services, modernizing Python apps, and enabling cloud deployments—demonstrating a rare blend of operational leadership and practical software engineering. He leverages an Aviation Management background from Vaughn College to connect systems thinking with user-focused automation, and his work often bridges frontline logistics with cloud-native tooling.
11 years of coding experience
3 years of employment as a software developer
Aviation Management, Aviation Management at Vaughn College of Aeronautics and TechnologyRiverside School of Aeronautics
Github Skills (30)
opencv10
javascript10
python10
ibm-cloud10
video-processing10
environment-variables10
flask-ask10
api10
computer-vision10
jupyter-notebook10
nodejs10
flask10
chatbot10
testing9
expressjs9
Programming languages (15)
Github contributions (5)
IBM/watson-banking-chatbot
May 2017 - Dec 2021
A chatbot for banking that uses the Watson Assistant, Discovery, Natural Language Understanding and Tone Analyzer services.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:86 commits, 65 PRs, 80 pushes in 4 years 8 months
Contributions summary:Mark primarily contributed to improving the application's functionality and infrastructure. Their work involved adding a deployment tracker to monitor deployments, indicating a focus on DevOps and deployment automation. Furthermore, they integrated Discovery passage retrieval to replace the previous Retrieve and Rank (RnR) functionality, enhancing the chatbot's ability to find answers. They also updated the dependencies and refactored the code for linting and consistent coding style.
natural-language-understandingibm-developer-technology-cognitivebankinglanguage-understandingwatson-assistant
IBM/powerai-counting-cars
Apr 2018 - Jan 2023
Run a Jupyter Notebook to detect, track, and count cars in a video using Maximo Visual Insights (formerly PowerAI Vision) and OpenCV
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:4 reviews, 33 commits, 34 PRs in 4 years 9 months
Contributions summary:Mark contributed to a Jupyter Notebook designed for car detection, tracking, and counting in videos. Their work involved integrating PowerAI Vision for object detection with OpenCV for video processing and tracking. The commits indicate the user focused on implementing a car counting system by defining tracking areas, identifying existing objects, and adding lane counters, resulting in a working example notebook.
pythonvisionjupyter-notebooknotebookcars
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