Artificial Intelligence Intern
Lockheed Martin
Applied 3 temporal deep learning models (STGCN, GAT, TGN) in Python to analyze aircraft trajectory data,
conducting experiments with labeling, Docker and Podman containerization, CI/CD, and agile development.
Created an Genesis AI assistant to automate the process of software engineers retrieving UCI message entity
translations for internal customers through Python scripting, web scraping, and Gitlab API, saving ~$27,000 per employee by
eliminating request processing and boosting engineer efficiency by 300% with a 1:1 replacement for query processes.
Developed a Python WebSocket communication layer to interface with a C++ Open Mission Systems (OMS) server,
enabling CAL compatibility and facilitating seamless integration with next-generation avionics platforms.
May 2025 - Present
Computer Vision Research Assistant
University of Michigan Robotics Department
Led autonomous robotic development for 100+ vision-controlled robots in 2 courses, impacting 40 graduate students.
Applied mathematical operations to Python, OpenCV, and computer vision algorithms to facilitate distance learning.
Enhanced the Jetson Nano’s stereo vision implementation within the MBot ecosystem through ORB SLAM.
January 2024 - May 2024
Computational Linear Algebra Instructional Aide
University of Michigan College of Engineering
Executed matrix and vector operations and linear transformations to optimize LiDAR data interpretations in robotic navigation tasks.
Taught 200 students the application of ML concepts, including linear regression, to develop predictive models for robotic systems, enhancing pattern recognition and decision-making processes.
Explained feedback control algorithms for dynamical systems, such as balancing a Segway robot, leveraging linear algebra and Julia programming for improved system stability and performance.
January 2024 - Present
Data Science Intern
Berry Consultants, LLC
Analyzed the optimal length of time a novel gene therapy would keep hemophilia patients at a safe level of clotting through the R programming language.
Worked with a team of 3 data scientists to investigate the relationship between biomarkers of the gut biome and clinical outcomes for an innovative treatment for C-difficile infections.
Assisted in the FDA approval of 2 treatments by developing plots of drug efficiency and safety alongside PhD Statisticians.
June 2022 - August 2022