Having the opportunity to apply state-of-the-art machine learning models to bioinformatics problems as an undergraduate motivated M. Maruf to take a deep dive into machine learning and deep learning as a Ph.D. student in computer science at Virginia Tech which he chose because of its exemplary research and top-notch facilities.  “Dr. Anuj Karpatne’s unique view towards solving real-world […]

Aneesh Jain is a master’s degree student in the Department of Computer Science. His advisor is Chandan Reddy. Jain’s work is in the domain of deep learning for software engineering, researching models for tasks like code translation, code summarization, and code generation.

Yi Zeng is a Ph.D. student in the Bradley Department of Electrical and Computer Engineering. His advisor is Ruoxi Jia. In his research, Zeng is particularly interested in machine learning’s general robustness and security. Currently, he is looking into general robust inference for deep learning models against adversarial and backdoor attacks.

With privacy a growing concern, Si Chen, a Ph.D. student in the Bradley Department of Electrical and Computer Engineering is using machine learning to study potential attacks and defenses against machine learning models.  She was attracted to this area of research because it is important and practical in real-world settings. “For example,” said Chen, “if a […]

Working toward a Ph.D. in computer science, Muntasir Wahed is delving into self-supervised learning, adversarial training, and out-of-distribution detection. “Suppose we train a machine learning classifier to help medical diagnosis of a disease X given an X-ray,” Wahed said. “We collect a large dataset of X-rays for both positive and negative samples of the disease X. However, after […]

Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song: Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR 2021: 8239-8247