My research focuses on Machine Learning, with a particular emphasis on efficient deep learning, computer vision, the intersection of vision and language, and large language models.
I earned my bachelor’s degree in Computer Science (Honors Program) from HCMUT, Vietnam. After graduation, I worked as a research data scientist at Zalo R&D and then research assistant at Texas Tech University.
You can reach me at chaupham [at] bu [dot] edu.
|Oct 2023||Our paper on growing neural networks was accepted at WACV 2024.|
|Sep 2023||Our paper introducing a new research topic on channel-adaptive imaging models was accepted at NeurIPS 2023.|
|Sep 2023||Our paper on Deep Distance Sensitivity Oracles was accepted at Complex Networks 2023.|
|May 2023||I join TikTok Applied Machine Learning team as a Research Scientist Intern.|
|Sep 2021||I start my first semester at Boston University!|
selected publications* denotes equal contribution
- preprintLet Models Speak Ciphers: Multiagent Debate through Embeddingspreprint
- WACVMixtureGrowth: Growing Neural Networks by Recombining Learned ParametersIn IEEE Winter Conference on Applications of Computer Vision (WACV) 2024
- NeurIPSCHAMMI: A benchmark for channel-adaptive models in microscopy imagingIn Advances in Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks 2023
- IEEE BigdataGraph Adversarial Attacks and Defense: An Empirical Study on Citation GraphIn 2020 IEEE International Conference on Big Data (Big Data) 2020
- IEEE BigdataRoad Damage Detection and Classification with Detectron2 and Faster R-CNNIn 2020 IEEE International Conference on Big Data (Big Data) 2020