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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.

A national pandemic that forced the closing of physical offices has not stopped graduate students at the Discovery Analytics Center from working remote internships at companies, research laboratories, and other institutions across the country. For many students, summer internships help further their own research as they gain real world experience.

Following is a list of DAC students and the work they are doing for the next few months:

Chidubem Arachie, a Ph.D. student in computer science, is a research intern at Google Research in Mountain View California. He is working on generative modeling for 3D shapes. His advisor is Bert Huang.

John Aromando, a Ph.D. student in computer science, is an intern at Graf Research in Blacksburg, working on utilizing natural language processing to support the software verification process. His advisor is Edward Fox.

Hongjie Chen, a Ph.D. student in computer science, is a data science research intern at Adobe in San Jose, California. He is on the Cloud Technology Team, researching cloud resource allocation strategy. His advisor is Hoda Eldardiry.

Nurendra Choudhary, a Ph.D. student in computer science, is an applied science intern with the Amazon Search Team in Palo Alto, California. He is working on representation learning of products by leveraging the heterogeneous relations between them. His advisor is Chandan Reddy.

Chen Gao, a Ph.D. student in electrical and computer engineering, is a research intern at Google in Mountain View, California. He is working on improvements to the portrait mode on the Google Pixel phone. His advisor is Jia-Bin Huang.

Akshita Jha, a Ph.D. student in computer science, is a research intern in the Interdigital AI Lab in Palo Alto, California. Her work involves building interpretable natural language processing models. Her advisor is Chandan Reddy.

Prerna Juneja, a Ph.D. student in computer science, is an intern at the Information Science Institute at the University of Southern California with Emilio Ferrara, assistant research professor and associate director of Applied Data Science in the Department of Computer Science. She is investigating the spread of COVID-19 related conspiracy theories on Twitter. Her advisor is Tanushree Mitra.

You Lu, a Ph.D. student in computer science, is a research intern at NEC Labs America in Princeton, New Jersey, working on sequence labeling for signals in fibers. His advisor is Bert Huang.

Shruti Phadke, a Ph.D. student in computer science, is doing a research internship with James Pennebaker, a professor in the Department of Psychology at the University of Texas at Austin. She is studying online communities, their social processes, and behaviors. Her advisor is Tanushree Mitra.

Aarathi Raghuraman, a master’s degree student in computer science, is an intern at GlaxoSmithKline (GSK), working with the Digital, Data, and Analytics team to maximize process yield in upstream biopharm manufacturing. She is advised by Lenwood Heath.

Esther Robb, a master’s degree student in electrical and computer engineering, is a research intern at Google working with a team in San Francisco on reinforcement learning. Her advisor is Jia-Bin Huang.

Mandar Sharma, a master’s student in computer science, is working as a machine learning intern with Toyota Motors North America, specifically the Toyota Racing Development (TRD) branch, to help NASCAR drivers make better decisions when they are racing. His advisor is Naren Ramakrishnan.

Aarohi Sumant, a master’s student in computer science, is an intern at Amazon. She is working with the Kindle Marketing Team to develop machine learning techniques for book recommendations based on cross user activities as well as single-user activities on different Amazon platforms. Her advisor is Edward Fox.

Afrina Tabassum, a Ph.D. student in computer science is a data science intern in the Data Science for The Public Good (DSPG) program at the Biocomplexity Institute’s Social and Decision Analytics Division (SDAD) at the University of Virginia. She is working on projects that address state, federal, and local government challenges around critical social issues relevant in the world today. Her advisor is Hoda Eldardiry.

Mia Taylor, a senior undergrad in computer science, is interning at Amazon Web Services in the Route 53 (DNS) service. Her advisor is Hoda Eldardiry.

Sirui Yao, a Ph.D. student in computer science, is an intern at Google, working on tag prediction for recommender systems through learning items and tags embeddings. Her advisor is Bert Huang.

Shengzhe Xu, a Ph.D. student in computer science, is interning at Facebook Ads Core ML, working on attention-based time sequential embedding aggregation. Xu’s advisor is Naren Ramakrishnan.

Ming Zhu, a Ph.D. student in computer science, is interning at Amazon. She is an applied scientist intern for Amazon Alexa AI, working on conversational query representation learning. Zhu’s advisor is Chandan Reddy.

Yuliang Zou, a Ph.D. student in electrical and computer engineering, is working on learning with less/weaker annotations at Google. His advisor is Jia-Bin Huang.

A number of graduate students at the Discovery Analytics Center have opted for internships and jobs at companies and national laboratories across the country this summer as a way of both benefiting their own research and gaining real world experience.

Following is a list of where they are for the next few months:

Aman Ahuja, a Ph.D. student in computer science, is an applied scientist intern at Amazon in Palo Alto, California. He is on the Amazon Search Team, researching product search techniques. His advisor is Chandan Reddy.

Tyler Chang, a Ph.D. student in computer science, has begun a six-month appointment at Argonne National Laboratory in Chicago, Illinois. He is one of 70 graduate students who received an appointment from the U.S. Department of Energy (DOE) Office of Science Graduate Student Research (SCGSR) to work on his thesis. The goal is to produce a portable multi-objective optimization software which Argonne could utilize in the future. Chang’s advisor is Layne Watson.

Jinwoo Choi, a Ph.D. student in electrical and computer engineering, is a research intern at NEC Labs America, San Jose, California, working on domain adaptation for video. Choi’s advisor is  Jia-Bin Huang.

Chen Gao, a Ph.D. student in electrical and computer engineering, is a research intern on a video completion project at Facebook in Seattle, Washington. He is working on an algorithm that synthesizes missing regions of videos. His advisor is Jia-Bin Huang.

Liuqing Li, a Ph.D. student in computer science, is on the Content Science team at Yahoo! Research in Sunnyvale, California, working on document recommendation through reinforcement learning. His advisor is Edward Fox.

Sneha Mehta, a Ph.D. student in computer science, is a data science intern at the Netflix headquarters in Los Gatos, California. She is researching novel methods to improve machine translation for subtitles. Her advisor is Naren Ramakrishnan.

Shruti Phadke, a Ph.D. student in computer science, is an intern at the Oak Ridge National Laboratory in Oak Ridge, Tennessee. She is working on developing scalable machine learning and Natural Language Processing (NLP) algorithms to detect public sentiment in news and social media. Her advisor is Tanushree Mitra.

Esther Robb, a master’s degree student in electrical and computer engineering, is a research intern at Google in Mountainview, California, where she is working on facial recognition. Her advisor is Jia-Bin Huang.

Alexander Rodriguez, a Ph.D. student in computer science, is a research intern at WalmartLabs in Sunnyvale, California. His advisor is B. Aditya Prakash.

Dhruv Sharma, a master’s student in computer science, is working at Kitware, Inc., in Carborro, North Carolina. As a research and development intern, Sharma’s work includes some medical image processing/machine learning tasks; mining EHR data for prediction of risk, procedure outcome, or other events; and analyzing training needs of healthcare providers. He is advised by Chandan Reddy.

Tian Shi, a Ph.D. student in computer science, is an intern at Pacific Northwest National Laboratory in Richland, Washington, where he is working on machine comprehension and question-answering on clinical notes in the healthcare domain. His advisor is Chandan Reddy.

Shih-Yang Su, a Ph.D. student in electrical and computer engineering, is a research intern at Borealis AI in Vancouver, Canada, working on graph convolution for structural prediction. His advisor is Jia-Bin Huang.

Deepika Rama Subramanian, a master’s student in computer science, is a mobility intern at Lam Research, Fremont, California, working on designing and developing an end-to-end mobile application for field engineers at Lam Research. Her advisor is Tanushree Mitra.

Anika Tabassum, a Ph.D. student in computer science, is a research intern at the Oak Ridge National Laboratory in Oak Ridge, Tennessee, where she will be applying data mining and visualization skills in two U.S. Department of Energy (DOE) projects: “Reynolds Landing Research” and “North American Energy Resilience Model.” Her advisor is B. Aditya Prakash.

Sai Sindhura Tipirneni, a master’s student in computer science, is working in the Quantum Computing Lab at Oak Ridge National Laboratory in Oak Ridge, Tennessee. Her advisor is Chandan Reddy.

Ping Wang, a Ph.D. student in computer science, is an intern at Pacific Northwest National Laboratory in Richland, Washington, where she is working on question answering on electronic medical records using Natural Language Processing (NLP) techniques. Wang’s advisor is Chandan Reddy.

Sirui Yao, a Ph.D. student in computer science, is a research intern at Google AI in New York City, where she is studying noise and bias in dynamic recommender systems. Her advisor is Bert Huang.

Ming Zhu, a Ph.D. student in computer science, is at Amazon in Seattle, Washington. She is an applied scientist intern for Amazon Comprehend Medical, working on Natural Language Processing on medical corpora using deep learning. Zhu’s advisor is Chandan Reddy.

Yuliang Zou, a Ph.D. student in electrical and computer engineering, is a research intern at NEC Labs America in San Jose, California, where he is working on unsupervised scene structure learning. His advisor is Jia-Bin Huang.

Ming Zhu learned about machine reading comprehension — making computers understand sophisticated natural language and be able to answer questions about what was read — while taking a graduate course at Carnegie Mellon University.

“After building a state-of-the-art Neural Question Answering (QA) model from scratch based on a research paper, my confidence grew in believing I could be a part of this future technology and pushed me further to focus my Ph.D. research in this area,” said Zhu.

Her interest in QA led Zhu, who holds a bachelor of engineering degree from the University of Science and Technology of China, to Chandan Reddy who is now her advisor at the Discovery Analytics Center’s National Capital Region location.

“Currently I am working on QA models with clinical notes as context. Clinical notes are a huge treasure of information if you make good use of them. They can help doctors make better medical decisions for their patients and help patients better understand their healthcare conditions,” Zhu said.

For example, she said, when deciding how to treat a new patient, a doctor might ask “How does rheumatic fever affect the heart when the patient is pregnant?” But, reviewing all the clinical notes in the database is impossible and a search engine cannot deal with this kind of query very well.

The AI-based Question Answering system that Zhu is working on can help by reading and comprehending the whole corpus, retrieving the most relevant articles or notes when given a human question, and selecting the most precise answers from them.

“My DAC advisor gives me a lot of freedom to explore while providing a lot of support to further my research,” said Zhu. “My lab mates are good partners with whom I can start heated discussions with at any time and the staff is nice and helpful.”

Zhu said she also likes the “city life” afforded by DAC’s northern Virginia location. In her free time she also enjoys cooking Chinese food, baking, and taking car trips with friends to visit places like Luray Caverns, Atlantic City, and New York City.

In May, Zhu will be traveling to The Web Conference 2019 in San Francisco to present a first-author paper, “A Hierarchical Attention Retrieval Model for Healthcare Question Answering.”

She is projected to earn her Ph.D. in computer science in May 2022 and plans to seek a position in academia.