Buse Carik

Buse Carik is a Ph.D. student in the Department of Computer Science.  She is advised by Eugenia Rho.

Carik’s research focuses on exploring and improving the interaction between humans and AI through computational social science, leveraging advanced techniques in natural language processing and human-computer interaction to understand and enhance the social implications of AI-mediated systems.


Lance Wilhelm

Lance T. Wilhelm is a Ph.D. student in the Department of Computer Science.  His advisor is Eugenia Rho.
His research focuses on how AI-mediated systems can help human interaction and more specifically, on how to build novel systems with large language models.

Chenyu Mao

Chenyu Mao is a master’s degree student in the Department of Computer Science. His advisor is Edward Fox.
Mao’s research focus is on modeling (classifying Electronic Theses and Dissertations (ETDs) into different topics) and object direction (extracting from ETDs).

Eugenia Rho

Eugenia Rho is an assistant professor in the Department of Computer Science, where she leads the SAIL (Society + AI & Language) lab, and is an affiliate faculty member at the Sanghani Center.

Prior to joining Virginia Tech, she was a postdoctoral scholar at the Natural Language Processing group in the Department of Computer Science at Stanford University. She earned her Ph.D. in informatics from the University of California, Irvine.

Her research focuses on exploring the intersection of Natural Language Processing (NLP) and Human-Computer Interaction (HCI), and she is particularly interested in how AI-mediated systems impact interactions across people and machines.


Mridul Khurana

Mridul Khurana is a Ph.D. student in the Department of Computer Science.  His advisor is Anuj Karpatne.
Khurana’s research centers around generative artificial intelligence and using science guidance to assist biologists in studying the evolution of different animal species over time. From computer vision models he extracts genome-like sequences using images to study the evolutionary traits of species and generate ancestral images.

Sindhura Kommu

Sindhura Kommu is a master’s degree student in the Department of Computer Science. She is advised by Xuan Yang.
Her research interests lie in the domain of multimodal ML for healthcare applications and her current work focuses on multi-omics Large Language Models for bio-medicine.

 


Abhijit Sarkar

Abhijit Sarkar is a senior research associate within the Division of Data and Analytics at the Virginia Tech Transportation Institute (VTTI) and affiliate faculty at the Sanghani Center.  At present, he leads the Computer Vision and Machine Learning team at VTTI. His research mainly focuses in the intersection of artificial intelligence and transportation research with an emphasis to computer vision. This includes safety and operations of automated driving systems; driver distraction and attention monitoring; intersection safety; unmanned aerial vehicles; multimodal sensor processing using naturalistic driving data; and AI application in driver health monitoring.

He received his doctoral degree from the Bradley Department of Electrical and Computer Engineering at Virginia Tech in 2017 with a focus in computer vision and remote health monitoring. Prior to that, he received a master’s degree in electrical engineering from the Indian Institute of Technology, Kharagpur, India; and a bachelor’s  degree in electrical engineering from Jadavpur University, India.

Sarkar’s research has been funded by multiple federal and state agencies including National Science Foundation (NSF); Federal Motor Carrier Safety Administrations (FMCSA), Federal Highway Administration (FHWA); National Highway Traffic Safety Administration (NHTSA); National Cooperative Highway Research Program (NCHRP); National Surface Transportation Safety Center for Excellence (NSTSCE); U.S. Department of Transportation University Transportation Center (UTC); and multiple private companies.


Hanwen Liu

Hanwen Liu is a Ph.D. student in the Department of Computer Science. He is advised by Xuan Wang.
Liu’s research is focused on establishing multi-modal translation models between EEG signals and human language.

Mian Zhang

Mian Zhang is a Ph.D. student in the Department of Computer Science, advised by Lifu Huang.
Zhang’s research interest is natural language processing, particularly focused on dialogue systems.

Pradyumna Upendra Dasu

Pradyumna Upendra Dasu is a master’s degree student in the Department of Computer Science.  He is advised by Edward Fox.
His primary research delves into the intricate dynamics of user experience associated with topic modeling, particularly emphasizing its application and implications for Electronic Theses and Dissertations (ETDs) as well as a broader spectrum of documents. Through this, he aims both to refine topic modeling techniques and to enhance the overall user interaction and understanding of ETDs and other textual content.