Anh Tran

OverviewAI-generated summary

Anh Tran's research focuses on the application of machine learning and artificial intelligence techniques to various scientific and engineering challenges. Tran has published work on improving generative adversarial networks (GANs) through hypernetworks, as seen in the publication 'HyperInverter: Improving StyleGAN Inversion via Hypernetwork.' Further contributions include research into open-vocabulary 3D instance segmentation using 2D mask guidance, detailed in 'Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidance.'

Tran's work also extends to the domain of autonomous driving, with a survey paper titled 'Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey.' The researcher has also investigated adversarial attacks in machine learning, specifically in the context of clean-label backdoor attacks, as presented in 'COMBAT: Alternated Training for Effective Clean-Label Backdoor Attacks.' Additionally, Tran has been involved in research concerning unsupervised learning for single-view 3D object reconstruction and the use of machine learning for identifying endocrine-disrupting potential from single-cell data.

With a h-index of 16 and over 1,600 citations across 111 publications, Tran's scholarly output demonstrates significant engagement in the field. The researcher has also secured federal funding, including an NSF I-Corps grant for $50,000 focused on developing servomotor actuators through advances in metallic additive manufacturing. Key collaborators include Minh Quan Tran, Minh Trần, Taisei Hanyu, and Alan Mantooth, all from the University of Arkansas at Fayetteville, with whom Tran has co-authored multiple publications.

Metrics

• h-index: 17
• Publications: 107
• Citations: 1,669