Virginia Tech’s Fall 2025 Commencement today (Dec. 19) includes a Graduate School ceremony celebrating students receiving their master’s and doctoral degrees. A Graduate Recognition Ceremony and Reception was held on Monday, Dec. 14, at Academic Building One in Alexandria for those earning grad degrees in the Washington, D.C. area and online.

“We are very proud of our Sanghani Center graduates. They have worked diligently on research aimed at meeting world challenges with innovative solutions and have presented their work at prestigious conferences. Many of them have also spent summers as interns in nationally recognized companies and labs where they have gained real-world experience,” 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 salute all of their accomplishments and wish them continued success as they go on to fulfill their career goals.”

The following are among Sanghani Center’s Ph.D. graduates:

Sareh Ahmadi, advised by Edward Fox, earned a Ph.D. in computer science. Her research focuses on human-centered artificial intelligence, with an emphasis on machine learning, multimodal large language (LLM)–based systems, and agentic artificial intelligence (AI). Her work involved designing, building, and evaluating LLM-based chatbot systems. She conducted user studies and analyses of episodic future thinking cue texts to support health behavior change, particularly in areas such as obesity and diabetes. The title of her dissertation is “Natural Language Processing for Behavior Change and Health Improvement.” 

Fatimah Alotaibi, advised by Dawei Zhou, earned Ph.D. in computer science. Her research advances artificial intelligence reasoning in open and dynamic environments, focusing on the development of robust reasoning systems under distribution shift and domain evolution for applications such as scientific discovery and question-answering systems. The title of her dissertation is “Towards Logical Reasoning in Open and Dynamic Environments.”

Blessy Antony, co-advised by Anuj Karpatne and T. M. Murali, earned a Ph.D. in computer science. Her research interests include using computational methods such as natural language processing and classical machine learning to solve impactful problems in systems biology and bioinformatics. The title of her dissertation is "Discovering Viral Hosts, Mutations, and Diseases using Machine Learning."

Osama Bajaber , co-advised by Bo Ji and Peng Gao, earned a Ph.D. in computer science. His research focuses on developing secure, scalable, and intelligent primitives embedded within the network infrastructure to enhance its security and robustness. The title of his dissertation is “Towards Zero Trust Network Security via Programmable Data Planes.” Bajaber is joining King Abdulaziz University in Saudi Arabia as an assistant professor.

Satvik Chekuri, advised by Edward A. Fox, earned a Ph.D. in computer science.  His research focuses on developing knowledge graphs for scholarly documents -- particularly Electronic Theses and Dissertations (ETDs) -- to support downstream tasks such as question answering, semantic querying, and recommendation, using techniques from information retrieval (IR), natural language processing (NLP), deep learning, and large language models (LLMs). The title of his dissertation is “Scholarly Information System for Long Documents and their Elements: Structured Representation and Exploration using Knowledge Graphs and LLMs.” Chekuri is joining AT&T Labs in Bedminster, New Jersey, as a machine learning engineer.

Badhan Das, advised by Lenwood Heath, earned a Ph.D. in computer science.  Her research includes computational biology and bioinformatics, genomics, algorithms, and graph theory, with a particular interest in addressing open questions in bioinformatics. The title of her dissertation is "Graph-Based Computational Approaches for Modeling Viral Evolution." She will be joining New York University in New York City as a postdoctoral associate in the Department of Biology's Center for Bioinformatics and Systems Biology.

Jesse Harden, advised by Chris North, earned a Ph.D. in computer science. His research focuses on effective use and benefits of spatializing computational notebooks, especially with large displays, for data science. The title of his dissertation is "Design and Evaluation of Spatialized 2D Computational Notebooks for Data Science."  Harden joined Radford University in Radford, Virginia, this fall as a tenure-track assistant professor. 

Sungwon In, advised by Chris North, has earned a Ph.D. in computer science. His research focuses on human-computer interaction, data visualization, and virtual reality/augmented reality (VR/AR). The title of In's dissertation is “ICoN: Immersive Computational Notebook for Data Science.”

Sumin Kang, advised by Manish Bansal, earned a Ph.D. in industrial and systems engineering. His research interest is in optimization with uncertainty, especially with applications to network optimization problems and their vulnerability analysis. The title of his dissertation is "Algorithms for Distributionally Risk-Receptive and Robust Stochastic Integer Programs and Interdiction Problems.” Kang has joined University of Groningen in Groningen, the Netherlands, as a postdoctoral researcher.

Yoonjin Kim, advised by Lenwood Heath, earned a Ph.D. in computer science. Her research focuses on algorithms, machine learning, and bioinformatics. The title of her dissertation is “Computational Analysis and Network-based Modeling of Cross-Species Transmissions.” Kim is joining Intel in Santa Clara, California.

Amarachi Blessing Madu, advised by Ismini Lourentzou, earned a Ph.D. in computer science. Her research focuses on the application of artificial intelligence and natural language processing in healthcare. Her dissertation, titled “Towards Interpretable AI for Longitudinal Disease Monitoring and Clinical Reporting from Chest X-Rays,”  develops interpretable AI frameworks for longitudinal disease monitoring and clinically grounded radiology report generation.

Seonghun Park, advised by Manish Bansal, has earned a Ph.D. in industrial and systems engineering. His research is focused on distributionally robust stochastic programming and combinatorial optimization. The title of his dissertation is "Distributionally Ambiguous Stackelberg Combinatorial Games for Submodular Optimization and Camera View-Frame Placement."  Park is joining Hyundai Motor Group in Seoul, South Korea, as senior research scientist.

Tanmoy Sarkar Pias, advised by Danfeng (Daphne) Yao, earned a Ph.D. in computer science. His research focuses on improving the trustworthiness of machine learning-based systems used in healthcare. The title of his dissertation is "Methodologies for Systematic Evaluation and Targeted Mitigation of Deficiencies in Critical Machine Learning Models." Pias has joined Stanford University in Palo Alto, California, as a postdoctoral scholar, where he is currently working on multi-modal vision foundation models for cancer detection.

Ibrahim Tahmid, co-advised by Doug Bowman and Chris North, earned a Ph.D. in computer science.  His research interest lies in leveraging eye-tracking data to develop intelligent analytic tools in the immersive space that adapt to analysts’ evolving intents. His goal is to enhance human-AI collaboration in cognitively heavy sensemaking tasks with smart recommendations and adaptive annotations. The title of his dissertation is "Toward AI-Mediated Immersive Sensemaking with Gaze-Aware Semantic Interaction." 

Shengzhe Xu, advised by Naren Ramakrishnan, earned a Ph.D. in computer science. His main research interest lies in deep generative models. He focuses on generating multivariable time-series data and applying the approaches to the areas of network security and financial analysis. The title of his dissertation is “New Approaches to Synthetic Tabular Data Generation.”  Xu has joined Amazon Web Services (AWS) AI as an applied scientist.

The following are Master’s Degree Graduates: 

Gayatri Bhatambarekar, co-advised by Abhijit Sarkar and Na Meng, earned a master's degree in computer science. Her research focuses on systematically evaluating the accuracy of multimodal large language models (LLMs) in inferring nutritional content from meal photographs, and identifying the minimal amount of supplementary information needed to improve their predictions. The title of her thesis is “Conversational Multimodal LLMs for Food Nutritional Information Retrieval: A Systematic Evaluation.” Bhatambarekar has joined the Virginia Tech Transportation Institute in Blacksburg, Virginia, as a full stack developer.  

Taufiq Daryanto, advised by Eugenia Rho, earned a master's degree in computer science. His research interest is at the intersection of natural language processing and human-computer interaction, where he focuses on building human-centered artificial intelligence systems. The title of his thesis is "Towards Human-AI Teaming for Skill Development from Dyadic Interview Practice to Triadic Programming Collaboration."  He is a founding engineer at Stealth Startup, in San Francisco, California. 

Chenyu Mao, advised by Edward Fox, earned a master's degree in computer science. His research focus is on modeling -- classifying Electronic Theses and Dissertations (ETDs) into different topics -- and object direction (extracting from ETDs). The title of his thesis is "Enhancing Layout Understanding via Human-in-the-Loop: A User Study on PDF-to-HTML Conversion for Long Documents."  Mao has joined ByteDance in Shanghai, China, as a software development engineer.

Lowell Weissman, advised by A. Lynn Abbott, earned a master's degree in electrical and computer engineering. His research studied complexity scaling laws, which are simple relationships between deep model performance and fundamental measures of problem complexity. The title of his thesis and corresponding NeurIPS 2025 paper is "Complexity Scaling Laws for Neural Models using Combinatorial Optimization." Lowell has joined Scale AI in Washington, D.C., as a machine learning engineer.


Matthew Zheng, advised by Pinar Yanardag, earned a master's degree in computer science. His research is in generative modeling in computer vision, focusing on text-to-image and text-to-video diffusion models. The title of his thesis is “Discovering and Personalizing Artistic Styles with Generative Models.”  Zeng has joined JPMorgan Chase as a data scientist.

Tong Zhou, advised by Lifu Huang, earned a master’s degree in computer science. His research focuses on video understanding. The title of his thesis is “GlitchAgent: Detecting Video Game Glitches from Gameplay Videos.” Zhou is pursuing a Ph.D. at the University of Houston in Texas.