Undergraduate Researcher | UC Merced
Presenters: Axel Muñiz Tello, Melanie Gomez-Bustos, Wesley Hur, Eddie Lizarzaburu
This research investigates the application of computer vision techniques to synthetic data for training models aimed at automating laboratory processes. By integrating simulation-based datasets with machine learning methods, we seek to enhance the reliability and scalability of automated experimental workflows. The project provided hands-on experience in data science, computational modeling, and algorithmic design, while fostering collaboration with domain experts. Through this work, we demonstrate the potential of synthetic training data to accelerate innovation in automated scientific research environments.
Presenters: Axel Muñiz Tello
This research explores disease transmission dynamics using Kinetic Monte Carlo (KMC) simulations within an agent-based SIR framework. By modeling populations on lattice structures with both restricted and unrestricted movement, it examines how spatial structure and randomness influence infection and recovery patterns. The study highlights how spatial constraints and stochastic effects shape epidemic behavior, offering insights for improving future disease control strategies.