Undergraduate Researcher | UC Merced
Location: Livermore, CA
Research Focus: Benchmarked U-Net vs. Neural Cellular Automata (NCA) for amodal segmentation on synthetic multi-view lab data, demonstrating that NCA achieved comparable IoU (0.46 vs. 0.25) while using 18% fewer parameters. Implemented a full model-to-amodal completion pipeline, converting 3D U-Net architectures into 3D convolutional video models and improving encoder-decoder RGB reconstruction across diverse comparisons.
Key Contributions: Led experimental design and analysis for model comparison, including model-to-amodal inference, RGB binarizing, and multi-modal training. Analyzed model generalization by comparing RLS-based estimators with data-driven predictors, informing ongoing work on hybrid ML + control pipelines for autonomous driving systems.
Location: Merced, CA
Research Focus: Developed an online Recursive Least Squares (RLS) estimator for real-time parameter identification in Adaptive Cruise Control (ACC) systems, achieving < 0.05 steady-state error across highway, suburban, and stop-and-go simulations.
Key Contributions: Designed and analyzed a model-to-amodal completion pipeline for test control algorithms under varying driving conditions, enhancing system reliability and adaptability. Implemented a full model-to-amodal completion pipeline, converting 3D U-Net architectures into 3D convolutional video models and improving short-horizon velocity forecasting by 18 percent. Analyzed model generalization by comparing RLS-based estimators with data-driven predictors, informing ongoing work on hybrid ML + control pipelines for autonomous driving systems.
Location: Merced, CA
Research Focus: Developed and analyzed computational simulations of the Susceptible-Infected-Recovered (SIR) model to study epidemiological trends for COVID-19.
Key Contributions: Implemented Kinetic Monte Carlo (KMC), a stochastic algorithm to effectively model and study stochastic disease transmission patterns while implementing an agent-based framework within the simulations. Designed and implemented bash scripts that influenced parameter sensitivity and functionality of the KMC algorithm. Processed and analyzed data utilizing NumPy, while ensuring visual comprehension utilizing Matplotlib.
Research Focus: Brief description of additional research work, including any independent studies or collaborative projects.
Key Contributions: What you accomplished and learned from this experience.