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Sungwon In 

Sungwon In is a Ph.D. student in the Department of Computer Science.  He is advised by Chris North. His research is focused on human-computer interaction, data visualization, and VR/AR.  

Chongyu He

Chongyu He was a master’s degree student in the Department of Computer Science.  He was advised by Edward Fox. His research primarily revolves around the application of advanced deep learning techniques for cell organelle segmentation in high-resolution microscopy images. By refining automatic analysis methods, he aims to enhance the accuracy and efficiency in interpreting intricate […]

Amazon-Virginia Tech Initiative announces support for two Amazon Fellows and five faculty-led projects for 2023-24 academic year

The Amazon–Virginia Tech Initiative for Efficient and Robust Machine Learning will support two Amazon Fellows and five innovative research projects led by Virginia Tech faculty in the 2023-24 academic year that further the initiative’s mission of advancing innovation in machine learning.  The initiative, launched in 2022, is funded by Amazon, housed in the College of Engineering, and directed […]

Manish Bansal

Manish Bansal is an associate professor; Grado Early Career Faculty Fellow; Operations Research Program Area lead with the Grado Department of Industrial and Systems Engineering at Virginia Tech; and core faculty at the Sanghani Center. He earned a bachelor’s degree in electrical engineering from the National Institute of Technology in India, and a master’s degree […]

Daniel Palamarchuk

Daniel Palamarchuk was a master’s degree student in the Department of Computer Science. He was advised by Chris North. His research focuses on visualizing temporal text, document, and topic data using pre-transformer embedding methods.

Tahmina Sultana Priya

Tahmina Sultana Priya is a Ph.D. student in the Department of Computer Science.  She is advised by Danfeng (Daphne) Yao. Her research focuses on leveraging artificial intelligence in the healthcare sector to identify patient subgroups; predict treatment responses; and provide personalized medicines by integrating demographics, genomics, disease, and image data to overcome one-size-fits-all strategies.

Andrew Zhang

Andrew Zhang is a student in the accelerated BS/MS program in the Department of Computer Science.  His advisor is Chris Thomas.  He has completed the BS requirements of the program and is now a master’s degree student. His research focus is on multimodal learning.    

Jianpeng Chen

Jianpeng Chen is a Ph.D. student in the Department of Computer Science.  He is advised by Dawei Zhou. Chen’s current research interests lie generally in data mining and machine learning with a particular focus on graph learning and its application for 3D molecular modeling.      

Trevor Ashby

Trevor Ashby is a master’s degree student in the Department of Computer Science. He is advised by Lifu Huang. His research focuses on making conversational agents more capable and expressive. He is exploring this through leveraging a knowledge base to inform response generation; improving the flexibility and expressibility of audio synthesis; and improving model understanding.

Cho-Ting (Amanda) Lee

Cho-Ting (Amanda) Lee was a master’s degree student in the Department of Computer Science. Her advisor was Naren Ramakrishnan. Her research interests are in data mining and machine learning, with a focus on trade data analytics and anomaly detection.