Hi, I’m Kayvon Crenshaw, a UIUC student applying CS and math to build scalable software and AI-powered tools. My work at NASA Langley and NASA Ames involved backend systems for LLM-based RAG workloads, GUI tooling for semantic matching, and performance optimizations that cut latency and streamline data workflows. I enjoy turning complex models into reliable, user-friendly software that helps researchers and engineers move their missions forward. I’m currently pursuing a Bachelor’s in Computer Science and Mathematics, and I’m eager to contribute to cross-disciplinary teams, continue learning, and deliver robust software, tooling, and research contributions that drive real-world impact.

Kayvon Crenshaw

Hi, I’m Kayvon Crenshaw, a UIUC student applying CS and math to build scalable software and AI-powered tools. My work at NASA Langley and NASA Ames involved backend systems for LLM-based RAG workloads, GUI tooling for semantic matching, and performance optimizations that cut latency and streamline data workflows. I enjoy turning complex models into reliable, user-friendly software that helps researchers and engineers move their missions forward. I’m currently pursuing a Bachelor’s in Computer Science and Mathematics, and I’m eager to contribute to cross-disciplinary teams, continue learning, and deliver robust software, tooling, and research contributions that drive real-world impact.

Available to hire

Hi, I’m Kayvon Crenshaw, a UIUC student applying CS and math to build scalable software and AI-powered tools. My work at NASA Langley and NASA Ames involved backend systems for LLM-based RAG workloads, GUI tooling for semantic matching, and performance optimizations that cut latency and streamline data workflows. I enjoy turning complex models into reliable, user-friendly software that helps researchers and engineers move their missions forward.

I’m currently pursuing a Bachelor’s in Computer Science and Mathematics, and I’m eager to contribute to cross-disciplinary teams, continue learning, and deliver robust software, tooling, and research contributions that drive real-world impact.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Software Engineer Intern at NASA Langley Research Center
December 31, 2024 - July 24, 2025
Developed the backend of an LLM agent-based RAG system using Flask, exposing modular RESTful endpoints for archival search retrieval, summarization, and prompt-chained responses. Reduced response latency by 5% and enabled external API access for integration with UI and automation pipelines. Integrated logging middleware to track endpoint response times for performance benchmarking. Implemented Redis caching to serve frequent semantic queries, reducing redundant LLM calls and improving throughput during batch queries.
Software Engineer Intern at NASA AMES Research Center
August 31, 2024 - July 24, 2025
Evaluated Large Language Models for Long-Duration Spaceflight Assistance and Data Standardization. Designed a GUI using PyQt5 for employing LLMs for semantic file matching, leveraging a Pydantic parser to standardize output and improve data validation. Streamlined data curation saving about 10 minutes for NASA researchers compared to manual methods. Developed an LLM-metric evaluator to compare fine-tuned and pre-trained models in biohealth sciences, improving semantic matching consistency by 12%.
Machine Learning Intern (REU @ UIUC) at University of Illinois
July 31, 2023 - July 24, 2025
Designed a Mask-RCNN for detecting, tracking, and locating farm animals in an environment through video feed. Led a cross-disciplinary team of 20 Animal/Crop sciences researchers to set up a remote data pipeline using rsync and SSH for automating labeled video uploads.
Software Engineer Researcher Intern at University of Illinois
July 31, 2022 - July 24, 2025
Investigated object detection via simulated LiDAR point clouds within Autoware.AI for Autonomous Vehicles. Implemented multi-object vehicle tracking in ROS (Melodic) by integrating 2D camera tracking via OpenCV’s CSRT tracker with 3D LiDAR detections. Improved car detection frame-rate accuracy tracking continuity by 15%.
Software Engineer Researcher Intern (RailTech @ UIUC) at University of Illinois
July 31, 2021 - July 24, 2025
Designed and deployed a Dash-based web app to visualize live railroad track data. Integrated Selenium to pull telemetry onboard sensors to automate real-time data extraction. Reduced latency from batches to less than 5 seconds through background scheduling.
Undergraduate Software Engineer Researcher at University of Illinois
May 31, 2021 - July 24, 2025
Explored UAV Emergency Responses Using Deep Reinforcement Learning algorithms. Collaborated with a team to evaluate temporal prediction models (LSTM and VAR) for trajectory forecasting to achieve fast emergency response predictions.
Software Engineer Intern at NASA Langley Research Center
December 1, 2024 - December 1, 2024
Developed the backend of an LLM agent-based RAG system using Flask, exposing modular RESTful endpoints for archival search retrieval, summarization, and prompt-chained responses; reduced response latency by 5% and enabled external API access for UI and automation pipelines; integrated logging middleware for performance benchmarking; implemented Redis caching to serve frequent semantic queries and improve throughput during batch queries.
Software Engineer Intern at NASA Ames Research Center
August 1, 2024 - August 1, 2024
Evaluating Large Language Models for Long-Duration Spaceflight Assistance and Data Standardization; designed a GUI using PyQt5 for employing LLMs for semantic file matching, leveraging a Pydantic parser to standardize output and improve data validation; streamlined data curation saving about 10 minutes for NASA researchers; developed an LLM-metric evaluator to compare fine-tuned and pre-trained models in biohealth sciences, improving semantic matching consistency by 12%.
Machine Learning Intern (REU) at University of Illinois at Urbana-Champaign
July 1, 2023 - July 1, 2023
Designed a Mask-RCNN for detecting, tracking, and locating farm animals in an environment through video feed; led a cross-disciplinary team of 20 Animal/Crop sciences researchers to set up a remote data pipeline using rsync and SSH for automating labeled video uploads.
Software Engineer Researcher Intern at University of Illinois Champaign
July 1, 2022 - July 1, 2022
Investigated object detection via simulated LiDAR point clouds within Autoware.AI for Autonomous Vehicles; implemented multi-object vehicle tracking in ROS (Melodic) by integrating 2D camera tracking via OpenCV’s CSRT tracker with 3D LiDAR detections; improved car detection frame-rate and tracking continuity by 15%.
Software Engineer Researcher Intern (RailTech @ UIUC) at University of Illinois Champaign
July 1, 2021 - July 1, 2021
Designed and deployed a Dash-based web app to visualize live railroad track data; integrated Selenium to pull telemetry onboard sensors to automate real-time data extraction; reduced latency from batches to under 5 seconds through background scheduling.
Undergraduate Software Engineer Researcher at University of Illinois Champaign
May 1, 2021 - May 1, 2021
Explored UAV Emergency Responses Using Deep Reinforcement Learning algorithms; collaborated with a team to evaluate temporal prediction models (LSTM and VAR) for trajectory forecasting to achieve fast emergency response predictions.

Education

Bachelor of Computer Science and Mathematics at University of Illinois Urbana Champaign
January 1, 2021 - December 31, 2025
Bachelor of Computer Science and Mathematics at University of Illinois Urbana Champaign
January 11, 2030 - December 1, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Government, Software & Internet, Life Sciences, Agriculture & Mining, Transportation & Logistics, Education