Dang Nguyen

CS Ph.D. Student at UCLA


Dang Nguyen is a first-year CS Ph.D. student at the University of California, Los Angeles, where he is advised by Professor Baharan Mirzasoleiman. His researches are centered on developing efficient and robust machine-learning algorithms for large-scale datasets and architectures. Specifically, he is working on improving the training efficiency of large language models and enhancing their robustness. Additionally, he is interested in exploring Generative AI and Multimodal Learning, with a particular emphasis on improving data quality. Through his works, he aims to advance the capabilities of machine learning systems in handling complex and diverse data while ensuring their reliability and performance.

Before joining UCLA, he was an AI Resident at VinAI, a leading AI research-based company in Vietnam. Prior to that, he received his BS degree, summa cum laude, in Information Networking for Innovation and Design from Toyo University. Going further back in time, he was a graduate of High School for Gifted Students (Hanoi University of Science) and a Maths Olympian (silver medal, IMO 2015).


Jun 17, 2024 I join Cisco as a PhD research intern.
Mar 3, 2024 Our paper Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift is accepted to DMLR @ ICLR 2024.
Jan 17, 2024 One paper is accepted at ICLR 2024.
Sep 25, 2023 I start my Ph.D. in Computer Science at UCLA.
Jun 4, 2023 Our paper On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks is recognized as one of the top 3% of all papers accepted at ICASSP 2023.