Ismini Lourentzou joined Virginia Tech’s “Curious Conversations” to chat about artificial intelligence (AI) and machine learning related to personal assistants, as well as her student team’s recent experience with the Alexa Prize TaskBot Challenge 2.  About Lourentzou Lourentzou is an assistant professor in the Department of Computer Science and core faculty at the  Sanghani Center for Artificial Intelligence and Data […]

Sophia Stil is a master’s degree student in the Human-Computer Interaction Track in the Department of Science. She is advised by Eugenia Rho. The focus of Stil’s research is investigating the applications of AI in aiding neurodivergent STEM students in mentorship and career building.

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 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.

Ramaraja Ramanujan was a master’s degree student in the Department of Computer Science. He was advised by Edward Fox. Ramanujan’s research focuses on data analysis of geospatial and administrative data, conducting statistical verifications and simulations, and visual analytics.  

Siji Chen is a Ph.D. student in the Department of Computer Science. Her advisor is Chang-Tien Lu. Her research focuses on decentralized swarm robots control, graphical model, uncertainty analysis, and data mining.

Gurkirat Singh is a master’s degree student in the Department of Computer Science.  His advisor is Hoda Eldardiry. His research focuses on forecasting electricity consumption and anomaly detection on high frequency, complex multi-seasonality data of the Electric Reliability Council of Texas (ERCOT) power grid.

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).