It was a week (May 10-18) of commencement ceremonies held across Virginia Tech campuses as graduates gathered with family and friends to celebrate graduation. Included in the Class of 2025 are 1,900 graduate degree recipients. 

“The Sanghani Center congratulates all university graduates and we are especially proud of those in our center,”  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. “We appreciate their hard work and dedication to research that can ultimately contribute to a better world for all of us. We wish them continued success as this chapter ends and they move on to the next.”

Included in the Sanghani Center Class of 2025 graduates are:

Ph.D. Graduates

Vasanth Reddy Baddam, co-advised by Hoda Eldardiry and Almuatazbellah Boker, has earned a Ph.D. in computer science. His research focuses on artificial intelligence, reinforcement learning, and control systems. The title of his dissertation is “Efficient Reinforcement Learning for Control.”

Si Chen, advised by Ruoxi Jia, has earned a Ph.D. in electrical and computer engineering. Her research focuses primarily on artificial intelligence (AI) safety, with an emphasis on understanding and mitigating risks such as model inversion, privacy leakage, and large language models (LLMs) jailbreak vulnerabilities. The title of her dissertation is “Evolving Threats and Defenses in Machine Learning Focus on Model Inversion and Beyond.” Chen is joining Salesforce in Palo Alto, California, as a machine learning research engineer. 

M. Maruf, advised by Anuj Karpatne, has earned a Ph.D. in computer science. His research focuses on knowledge-guided machine learning, with an emphasis on graph representation learning, generative models, and multimodal vision-language models for scientific discovery. The title of his dissertation is "Learning without Expert Labels for Multimodal Data,” for which he garnered the Outstanding Ph.D. Research Award from the Virginia Tech Department of Computer Science. Maruf is joining Amazon Artificial General Intelligence (AGI), in Seattle, Washington, as an applied scientist.

Yanshen Sun, advised by Chang-Tien Lu, has earned a Ph.D. in computer science. Her research focus is on anomaly detection in traffic networks. The title of her dissertation is “Toward Robust and Generalizable Spatiotemporal Modeling for Tasks beyond Forecasting and Classification.”  Sun is joining Meta in Menlo Park, California, as a research scientist.

Afrina Tabassum, co-advised by Hoda Eldardiry and Ismini Lourentzou, has earned a Ph.D. in computer science. Her research focuses on machine learning, particularly designing novel representation learning objectives for multi-modal data. The title of her dissertation is "Bridging Multimodal Learning and Planning for Intelligent Task Assistance." Tabassum is joining Amazon in Seattle, Washington, as an applied scientist.

Yi Zeng, advised by Ruoxi Jia, has earned a Ph.D. in electrical and computer engineering. His research focus is on the general robustness and security of machine learning. The title of his dissertation is “Understanding and Mitigating Data-Centric Vulnerabilities in Modern AI Systems.” Zeng was a 2022-2023 inaugural Amazon Fellow. 

Master’s Degree Graduates

Ahmed Aredah, advised by Hoda Eldardiry, has earned a master of engineering degree. His research focus is on implementing large-scale energy consumption and emission prediction simulators like NeTrainSim and ShipNetSim; human-in-the-loop simulators; autonomous vehicles; and the applications of artificial intelligence in traffic state predictions. The title of his thesis is “Developing a Large-Scale Multi-Modal Modeling and Optimization Framework for Freight Transport Network Analysis.” Aredah simultaneously earned a Ph.D. in civil engineering, advised by Hesham Rakha, with Eldardiry serving on his dissertation committee.

Mounika Abbineni, advised by Sara Hooshangi, has earned a master's degree in computer science. Her research focus is on computer science education. The title of her thesis is “Mixed Methods Study of How Computer Science Students Make Technical Elective Choices.” 

Tyler Buxton, advised by Sara Hooshangi, has earned a master’s degree in computer science. His research focuses on computer science education. The title of his thesis is “Gitit: An Interactive Online Platform for Teaching Command Line Based Skills Through Visualizations.”  Buxton is joining FedEx as a software engineer.

Sindhura Kommu, advised by Xuan Wang, has earned a master's degree in computer science. Her research focus is on the domain of multimodal foundation models for biomedical applications. The title of her thesis is “Towards Network-Guided Large-Scale Foundation Models on Single-Cell Transcriptomics.”

Aishwarya Kumaran, advised by Naren Ramakrishnan, has earned a master's degree in computer science. Her research focuses on enhancing mathematical reasoning by large language models (LLMs). The title of her thesis is “Backward Reasoning in LLMs: A Strategy for Identifying Irrelevant Context in Mathematical Word Problems.” Kumaran is joining Qualcomm in San Diego, California, as a software engineer.

Faizan Manzoor, advised by Ming Jin, has earned a master's degree in electrical and computer engineering. His research focuses on developing a machine learning based intrusion detection system that leverages in-context learning capabilities of large language models for the cyber security of substations. The title of his thesis is “Detecting Zero-Day Attacks in IEC-61850 based Digital Substations via In-Context Learning.” Manzoor is joining Mitsubishi Electric Power Product Inc. in Warrendale, Pennsylvania, as a systems studies engineer.

Andrew Neeser, advised by Naren Ramakrishnan, has earned a master's degree in computer science. His research focuses on enhancing the performance of Retrieval-Augmented Generation (RAG), exploring novel methods to optimize their efficiency and accuracy. The title of his thesis is "Quote: Question-Oriented Text Embedding." Neeser is joining The Washington Post in Washington, D.C., as an applied machine learning scientist.

Priya Pitre, co-advised by Naren Ramakrishnan and Xuan Wang, has earned a master's degree in computer science. Her research focuses on optimizing multi-agent discussions in large-language models (LLMs), especially in the context of real-world data. The title of her thesis is "Toward Deliberative AI: Multi-Agent LLMs for Real-World Reasoning.” Pitre will be returning to Virginia Tech to pursue a Ph.D. in computer science.

Aanish Pradhan, advised by Anuj Karpatne, earned a master’s degree in computer science. His research focuses on physics-guided machine learning for lake and reservoir ecological modeling. The title of his thesis is “Training Physics-Guided Neural Networks with Multiple Constraints: An Application in Lake Ecology Modeling.”

Anushka Sivakumar, advised by Chris Thomas, has earned a master’s degree in computer science. Her research focuses on a robust and lightweight steering mechanism for multimodal vision language models gaining inference time control over the model's output semantics. The title of her thesis is "Model Control Through Lightweight Activation Steering For Vision Language Models." 

Gaurav Shah, advised by Sara Hooshangi, has earned a master of science degree in computer science. His research focus is on applying machine learning techniques for causal inference. The title of his thesis is “Evaluating the Effects of Financial Deregulation on Bank Risk using Double Machine Learning.”

Priya Shanmugasundaram, advised by Ming Jin, has earned a master's degree in electrical and computer engineering. Her research focuses on reinforcement learning and natural language processing. She worked on improving reasoning of multimodal large language models. She is joining Adobe in San Jose, California, as a machine learning engineer. 

Sophia Stil, advised by Eugenia Rho, has earned a master’s degree in computer science in the Human-Computer Interaction Track. The focus of her research is investigating the applications of artificial intelligence in aiding neurodivergent STEM students in mentorship and career building. The title of her thesis is “The Applications of AI for Autistic STEM Student Mentorship.”

Jonathan Tyler, co-advised by A. Lynn Abbott and Abhijit Sarkar, has earned a master's degree in computer engineering. His research, focusing on the application of deep-learning models to the problem of analyzing video data, can potentially be used for problems ranging from health monitoring to biometric authentication tasks. The title of his thesis is "Extraction of Blood Volume Pulse Morphology from Facial Videos using an LSTM-Based Temporal Encoder-Decoder Model." 

James Weichert, advised by Hoda Eldardiry, has earned a master's degree in computer science. His research focuses on artificial intelligence (AI) ethics, computer science education, and policy. The title of his thesis is "AI Education for the AI Generation: A Study of Computer Science Student Attitudes Towards AI Ethics and Implications for CS Curricula." In the fall, Weichert will be joining the University of Washington Paul G. Allen School of Computer Science and Engineering as an assistant teaching professor.

Andrew Zhang, advised by Chris Thomas, was in the accelerated BS/MS program and has earned a master’s degree in computer science. His research focus is on discrete diffusion models. The title of his thesis is “Discrete Diffusion for Text Infilling.” Zhang is joining AmazonWeb Services in Seattle, Washington, as a machine learning engineer.