AI/ML researcher, published author, and builder. I create systems at the intersection of machine learning and human health.
I'm a Computer Science student at Carnegie Mellon University (SCS, Class of 2029), originally from San Diego. I'm deeply passionate about using AI and machine learning to solve real-world problems — particularly in healthcare and accessibility.
I've published research on autism detection via neural networks at AMIA 2024 and co-authored a paper at ACM CHI 2024 on robotics and autism inclusion. I've worked across labs at UCSD, University of Hawaii, and Ohio State University.
At CMU, I lead development in ScottyLabs and continue pushing forward on AI-driven research tools. When I'm not coding, you'll find me at math competitions or exploring computational biology.
Leading a team of 10+ developers building the GSA Student Housing platform — helping CMU students find comprehensive off-campus housing information. Responsible for task delegation, architecture decisions, and full-stack development.
Built an LSTM-based machine learning pipeline to detect autism through behavioral video analysis of children. Published as 1st author at AMIA 2024, comparing sequence-based neural network architectures for autism-related behavior classification.
Created datasets to analyze ableism in research & social media. Built LLM-powered ableist text detection systems using prompt engineering. Co-authored the ACM CHI 2024 paper on robots and autism inclusion.
Presented Li-ion battery anode synthesis at UCSD Student Research Conference. Applied ML and data science to optimize Atomic Packing Factors. Built computational models for Magnetic Self-Assembly Simulation.
Assessed the impact of structural racism on neurocognition as part of an NIH-funded research project under Prof. Victoria Castillo.
Analyzed genetic causes of autism and neurological disorders using bioinformatic tools. Presented findings at the CureScience symposium.
LSTM-based neural network for detecting autism through behavioral video analysis. Compared multiple sequence-based architectures to find optimal classification performance. Published at AMIA 2024.
Created datasets and detection mechanisms to identify ableist text in social media and research papers using large language models and prompt engineering techniques.
Led development of a comprehensive platform for CMU students to discover off-campus housing listings. Built with a team of 10+ developers through ScottyLabs.
Used ML and data science to find optimal Atomic Packing Factors for battery materials. Built a Magnetic Self-Assembly computational simulation model published on the web.
Full-stack application integrating Flask/OpenAlex backend with React frontend for graph-theoretic analysis of research fields — including k-truss decomposition, Jaccard similarity, and agent-based simulations.
Analyzed possible genetic causes of autism and neurological disorders using bioinformatic tools as part of the CureScience Scholars program at UCSD.
Compared LSTM, GRU, and Transformer architectures for behavioral video classification in autism detection.
Association of Computing Machinery — explored the readiness and potential of robotic systems for fostering autism inclusion.
Math research at Stanford University Math Camp, 2024
Harvard-MIT Mathematics Tournament, Guts Round
Placed in the top 50 nationally, 2023
National Merit Scholarship Program, 2024–2025
Southern California Science Olympiad at Caltech, 2023
Coca-Cola Scholar Semifinalist, 2024–2025
I'm always looking for new opportunities and collaborations.