Congratulations to Sanghani Center’s 2024 Summer and Fall Graduates

Virginia Tech’s 2024 Fall Commencement ceremonies take place today. The Graduate School Commencement Ceremony will be held in Cassell Coliseum at 2:30 p.m. and  live-streamed.

“Graduation is always bittersweet. We are proud of our graduates and what they have achieved. And we are excited to see where the future leads them. But we are also sad to see them leave us,”  said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science at Virginia Tech and director of the Sanghani Center for Artificial Intelligence and Data Analytics. “They deserve congratulations and we wish them all the best.”

The following Sanghani Center students are among those who are receiving degrees:

Ph.D.  Graduates

Bipasha Banerjee, advised by Edward Fox, has earned a Ph.D. in computer science. Her research explored ways to make scholarly documents more accessible. Her dissertation is titled “Improving Access to ETD Elements Through Chapter Categorization and Summarization.” Banerjee has joined the University Libraries at Virginia Tech in Blacksburg as a research faculty, where she is focused on making digital objects hosted at the Virginia Tech University Libraries more accessible by adding AI services to existing workflows.

Kylie Davidson, advised by Chris North, has earned a Ph.D. in computer science. Her research focuses on using virtual/augmented reality for day-to-day productivity tasks to investigate how immersive technologies can be used during sensemaking. The title of her dissertation is “Sensemaking in Immersive Space to Think: Exploring Evolution, Expertise, Familiarity, and Organizational Strategies.”

Mandar Sharma, advised by Naren Ramakrishnan, has earned a Ph.D. in computer science. His research focus is on AI/machine learning, specifically natural language generation and predictive modeling. The title of his dissertation is “Non-linguistic Notions in Language Modeling, Learning, Retention and Applications.” Sharma has joined Google AI, in Mountain View, California, as a senior software engineer.

Wenjia Song, advised by Danfeng (Daphne) Yao, has earned a Ph.D. in computer science. Her research focuses on applications of machine learning in medical predictions and cybersecurity. The title of her dissertation is “Data-driven Algorithms for Critical Detection Problems: From Healthcare to Cybersecurity Defenses.” Song will join Google, in New York City, as a software engineer.

Sijia Wang, advised by Lifu Huang, has earned a Ph.D. in computer science. Her research focuses on natural language processing and machine learning, particularly on information extraction using prompt-based methods with full or limited supervision. The title of her dissertation is “Towards Generalizable Information Extraction with Limited Supervision.” Wang has joined Amazon, in New York City, as an applied scientist.

Master’s degree Graduates

Pradyumna Upendra Dasu, advised by Edward Fox, has earned a master’s degree in computer science. His research focuses on advancing topic modeling techniques to enhance user experience, with a particular emphasis on their applications in digital libraries and improving the accessibility of Electronic Theses and Dissertations (ETDs). The title of his thesis is “Topic Modeling for Heterogeneous Digital Libraries: Tailored Approaches Using Large Language Models.” Dasu will continue his career path with Virginia Tech in Blacksburg, Virginia, transitioning to a full-time role as an application developer.

Harish Babu Manogaran, co-advised by A. Lynn Abbott and Anuj Karpatne, has earned a master’s degree in electrical and computer engineering. His research focuses on the application of interpretable artificial intelligence models for evolutionary trait identification from images. The title of his thesis is “Hierarchy Aligned Commonality Through Prototypical Networks: Discovering Evolutionary Traits over Tree-of-Life.” Manogaran will join a Palo Alto based startup as a machine learning engineer.

Gurkirat Singh, advised by Hoda Eldardiry, has earned a master’s degree in computer science. His research focuses on evaluating machine learning techniques for forecasting electricity load within the Electric Reliability Council of Texas (ERCOT) power grid. His thesis, titled “Comparative Analysis of Machine Learning Models for ERCOT’s Short-Term Load Forecasting,” explores innovative approaches to enhance load prediction accuracy.  Singh will be joining Citigroup in Houston, Texas, as a commodities trading analyst.