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Virginia Tech’s 2023 Fall Commencement ceremonies take place today. The Graduate School Commencement Ceremony will be held in Cassell Coliseum at 1:30 p.m. and will be live-streamed.

“We celebrate our Summer and Fall graduates who have worked so hard to achieve their graduate degrees,” 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 all the congratulations coming their way and we wish them all the best as they embark on their new journeys.”

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

Ph.D. Graduates

Aman Ahuja, advised by Edward Fox, has earned a Ph.D. in computer science. His research focused on document understanding, search and retrieval, and question-answering to improve the accessibility of long PDF documents, such as books and dissertations. His dissertation, “Analyzing and Navigating Electronic Theses and Dissertations” was awarded the 2023 Innovative Student Thesis Award by the Networked Digital Library of Theses and Dissertations (NDLTD). Ahuja has joined DocuSign in Seattle, Washington, as an applied scientist.

Arka Daw, advised by Anuj Karpatne, has earned a Ph.D. in computer science. His research centers around the emerging field of science-guided machine learning, where machine learning models are integrated with scientific knowledge (or physics) to ensure better interpretability and generalizability while enforcing scientific consistency. The title of his dissertation is “Physics-informed Machine Learning with Uncertainty Quantification.”  Daw is joining Oak Ridge National Lab (ORNL) in Knoxville, Tennessee, as a Distinguished Staff Fellow.

Chris Grubb, advised by Leanna House, has earned a Ph.D. in statistics. His research focuses on developing a statistical learning method of population synthesis that allows for propagation of uncertainty from sample data into synthetic populations of agents. The title of his dissertation is “Inference for Populations: Uncertainty Propagation via Bayesian Population Synthesis.” Grubb has joined Virginia Tech’s Center for Biostatistics and Health Data Science in Roanoke, Virginia, as a research scientist.

Whitney Hayes, co-advised by Ashley Reichelmann and Naren Ramakrishnan, has earned a Ph.D. in sociology. Her research focus is on identity. The title of her dissertation is “Enhancing Identity Theory Measurement: A Case Study in Ways to Advance the Subfield.” Hayes also received a graduate certificate in urban computing offered through the Sanghani Center. She has joined Elevate, a climate action nonprofit based in Chicago, Illinois, and works remotely as a research analyst. 

Brian Keith, advised by Chris North, has earned a Ph.D. in computer science. His research focuses on how to represent, extract, and visualize information narratives to aid analysts in their narrative sensemaking process. The title of his dissertation is “Narrative Maps: A Computational Model to Support Analysts in Narrative Sensemaking.” Keith has joined the Catholic University of the North in Chile as an assistant professor in the Department of Computing and Systems Engineering. 

Shuo Lei, advised by Chang-Tien Lu, has earned a Ph.D. in computer science. Her research focuses on few-shot learning and domain adaptation. The title of her dissertation is “Learning with Limited Labeled Data: Techniques and Applications.” Lei has joined Sony Research in San Jose, California, as a research scientist.

Lei Zhang, advised by Chang-Tien Lu, has earned a Ph.D. in computer science. His research focuses on bi-level optimization, neural architecture search, and graph neural networks. The title of his dissertation is “Bilevel Optimization in the Deep Learning Era: Methods and Applications.”

Ming Zhu, co-advised by Daphne Yao and Ismini Lourentzou, has earned a Ph.D. in computer science. Her research focus is on Machine Learning and Natural Language Processing. The title of her dissertation is “Neural Sequence Modeling for Domain-Specific Language Processing: A Systematic Approach.” Zhu has joined ByteDance in Seattle, Washington, as a research scientist.

Master’s Degree Graduates

Nikhil Abhyankar, advised by Ruoxi Jia, has earned a master’s degree in electrical and computer engineering. His research focus is on machine learning privacy and security. The title of his master’s thesis is “Data Centric Defenses for Privacy Attacks.” Abhyankar has joined the Virginia Tech Department of Computer Science to pursue a Ph.D.

Humaid Desai, advised by Hoda Eldardiry, has earned a master’s degree in computer science. His research focuses on enhancing the efficiency and resource utilization of Federated Learning in resource-constrained and heterogeneous environments. The title of his master’s thesis is “REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments.” Desai is joining Ellucian in Reston, Virginia, as a software engineer.

Chongyu He, advised by Edward Fox, has earned a master’s degree in computer science. His research primarily revolves around the application of advanced deep learning techniques for cell organelle segmentation in high-resolution microscopy images. The title of He’s master’s thesis is “Deep Learning Approach for Cell Nuclear Pore Detection and Quantification over High Resolution 3D Data.”

Junho Oh, advised by Lynn Abbott, has earned a master’s degree in Computer Engineering. His research focus is machine learning. The title of Oh’s master’s thesis is “Estimation of Global Illumination using Cycle-Consistent Adversarial Networks.”

Akash Sonth, advised by Abhijit Sarkar and Lynn Abbott, has earned a master’s degree in computer engineering. His research focus is on the application of machine learning in driver safety and intelligent transportation. The title of his master’s thesis is “Enhancing Road Safety through Machine Learning for Prediction of Unsafe Driving Behaviors.”  Sonth has joined the Aspen Technology office located in Bedford, Massachusetts, as a data scientist.

Surendrabikram Thapa, co-advised by Anuj Karpatne and Abhijit Sarkar, has earned a master’s degree in computer science. His research focus is multimodal learning, computer vision, and natural language processing applications. The title of his master’s thesis is “Deidentification of Face Videos in Naturalistic Driving Scenarios.” Thapa also received a graduate certificate in data analytics offered by the Sanghani Center. He has joined the Virginia Tech Transportation Institute (VTTI) as a research faculty.

Lei Zhang was a master’s degree student in software engineering at Jinan University in China when his advisor told him about meeting Chang-Tien Lu from Virginia Tech and how he was doing research with algorithms on Twitter. While they were using different platforms — Zhang’s own work was on Weibo, the largest Chinese microblogging website — he was interested to hear  about Lu’s research.

When he decided to pursue a Ph.D., Zhang decided to apply to Virginia Tech’s Department of  Computer Science. As it turned out, Lu is now his advisor.

Zhang’s current research at the Discovery Analytics Center includes graph structure learning.

“Graph neural network models have shown that they can be widely used for urban computing, neuroscience, biology, and many other fields,” said Zhang. “However, the graph structure can be either non-existing or not optimal for specific objectives. Take a traffic network as an example. Graph structure learning techniques can construct a causal graph of traffic flow changes which is more informative than just the grid graph.”

Zhang has also integrated psychology and machine learning. He has designed a text classification model utilizing the DIAMONDS situation taxonomy from psychology. Zhang is also working on some neuroscience-inspired models such as spiking networks, oscillation networks, and echo state network.

“My research interests originated from my experience reading popular science books when I was younger,” said Zang. “Three topics I liked most are complexity science, psychology, and AI. While my own research did not start from the most relevant areas, it is getting closer and closer,” he said.

Zhang said working with “very smart” DAC students is an added plus to what he is learning from expert machine learning/data mining professors on campus.

Lu and another DAC student were among Zhang’s collaborators on a paper he presented at the 2018 IEEE International Conference on Big Data entitled “Situation-Based Interpretable Learning for Personality Prediction in Social Media.”

Another one of Zhang’s papers, “Acoustic differences between healthy and depressed people: a cross-situation study,” was published in the October 2019 issue of BMC Psychiatry.

He holds a bachelor’s degree in software engineering from Northeastern University, China, in addition to his master’s degree from Jinan University.  Projected to graduate in Spring 2021, Zang said his ideal position would be in an interdisciplinary research lab for AI and psychology/neuroscience.