Charles Nimo
Software Developer | Graduate Student | Founder
“Be the change you want to see in the world!”
LET ME INTRODUCE MYSELF
Hi, my name is Charles and I am currently a graduate computer science student at The University of Texas at Austin with interests in Machine Learning, Computer Vision, and Trustworthy AI.
I am a member of the AI Health Lab @ UT Austin, directed by Prof. Ying Ding. My current research is focused on developing and applying machine learning techniques for medical problems.
Prior to my graduate studies, I have been involved in a start up, and have worked and interned as a software engineer at Intel and Dell. Click the link below to learn more about what I’ve worked on – Take a look around and if you find something that interests you, feel free to reach out!
Download my resumé.
- Machine Learning
- Trustworthy AI
- Computer Vision
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Master's of Science in Computer Science, 2023
The University of Texas at Austin
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Bachelor's of Science in Electrical and Computer Engineering, 2017
Virginia Commonwealth University
Skills
Experience
- Worked with the Mathematical Modeling team in the Data Platforms group to improve their data processing and visualization tools that they use to gain insights on vast amounts of data to render smart solutions for Intel Customers.
- Used machine learning techniques to make predictions and determine optimal configurations for a given simulation model system.
- Designed and developed several server-side RESTful API’s using the Spring Framework in Java for Dell’s OpenManage Enterprise solutions
- Worked to migrate an existing architecture to microservices which led to several performance enhancements in a number of areas including memory footprint, CPU load, thread utilization, data loss, and overall system responsiveness.
- Worked as member of two-person team on a Vertically Integrated Project for Unmanned Aerial Vehicle (UAV) research
- Published and presented associated paper at 2017 AIAA SciTech Exposition in Dallas, TX
- Implemented real-time tracking of UAV during flight on maps for both online and offline use in second year of research.
