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Virginia Tech’s Fall Commencement ceremony for the Graduate School is now underway (livestream here) and seven students from the Sanghani Center are among those receiving degrees. 

“This has been a tough year and they successfully navigated obstacles caused by the COVID19 pandemic to achieve their academic goals and we are very proud of them,” 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. 

Following is a list of Sanghani Center 2021 summer and fall graduates:

Ph.D.

Khoa Doan, advised by Chandan Reddy, has earned a Ph.D. in computer science.  His primary research interests lie in Machine Learning and Information Retrieval. The title of his dissertation is “Generative models meet similarity search: efficient, heuristic-free and robust retrieval”.  Doan has joined Baidu Research as a machine learning researcher. 

You Lou, co-advised by Bert Huang and Naren Ramakrishnan, earned a Ph.D. in computer science. His research areas are structured prediction, probabilistic graphical models, variational inference, and deep generative models. The title of his dissertation is “Modeling Structured Data with Invertible Generative Models.” Lou has joined Motional, a driverless technology company, as a machine learning research scientist.

Anika Tabassum, advised by B. Aditya Prakash, has earned a Ph.D. in computer science. She also earned the Urban Computing graduate certificate. For her Ph.D. research, she worked to develop explainable and domain-guided machine learning frameworks for power systems to aid decision-making for emergency management authorities. The title of her dissertation is “Explainable and Network-based Approaches for Decision-making in Emergency Management.” Tabassum has joined Oak Ridge National Laboratory in Tennessee as a postdoctoral research associate in the Discrete Algorithms Group, working on various projects related to scientific machine learning. 

Tian Shi, advised by Chandan Reddy, has earned a Ph.D. in computer science. His primary research interests lie natural language processing and machine learning. The title of his dissertation is “Novel Algorithms for Understanding Online Reviews.” Shi has joined Moody’s Analytics as a machine learning research scientist.

Ping Wang, advised by Chandan Reddy, has earned a Ph.D. in computer science. Her primary research focuses on question answering, graph mining, information extraction, and survival analysis with their applications in the healthcare domain. The title of her dissertation is “Automatic Question Answering and Knowledge Discovery from Electronic Health Records.” Wang has joined the Computer Science Department at Stevens Institute of Technology in Hoboken, New Jersey, where she is an assistant professor.  

Master’s Degree

Eman Abdelrahman, advised by Edward Fox, has earned a master’s degree in computer science. Her research interest lies in applying machine learning and natural language processing on Arabic scientific datasets such as ETDs in order to improve the accessibility to Arabic scientific data. The title of her thesis is “Improving the Accessibility of Arabic ETDs with Metadata and Classification.” She is remaining at Virginia Tech and the Sanghani Center to pursue a Ph.D. in computer science, advised by Ismini Lourentzou. 

Aarathi Raghuraman, advised by Lenwood Heath, has earned a master’s degree in computer science. Her primary research interests lie in biomedical data science and bioinformatics. The title of her thesis is “Predicting Mutational Pathways of Influenza A H1N1 Virus using Q-learning. Raghuraman has joined LexisNexis Legal and Professional in Raleigh, North Carolina, as a data scientist.

Esther Robb, advised by Jia-Bin Huang, has earned a master’s degree in computer engineering. Her primary research interests lie in reinforcement learning and data-efficient learning. The title of her thesis is “Data-Efficient Learning in Image Synthesis and Instance Segmentation.” Robb is pursuing a Ph.D. in computer science at Stanford University.

After graduating with a bachelor’s degree in computer science from Webster University, Khoa Doan entered the workforce. For the next few years, he held positions as a software developer and data engineer in the advertising industry and at NASA and gained experience processing large datasets.

“I came to appreciate both the theoretical and practical contributions,” said Doan. “Working with large datasets is tricky because solutions become much more constrained. The challenge is what interests me and it makes me really happy if I am able to solve a problem.”

Doan decided to pursue a master’s degree in computer science at the University of Maryland. When looking for a Ph.D. program, he was attracted to Virginia Tech and the Discovery Analytics Center “because of a good mix of strong theoretical foundation and practical research objectives. There is a diversity and plethora of research opportunities, especially in things that matter.”

And since being at DAC, he said, “I have learned a lot from the DAC community. I have good friends with both similar and diverse research interests.”

Doan’s main research interest is in scalable machine learning and data mining. His current focus is on deep hashing for similarity search, using neural networks as a basis for efficiently “searching” for similar items in very large databases. For example, he searches for similar documents in news articles, books or papers, and images.

“This problem is very hard because we have to pay attention to both efficiency — how to retrieve the items fast, and sometimes in real-time — and effectiveness,” said Doan. “Items can be similar because of similar words, but also because of similar authors, or similar topics, thus it is very difficult to choose the right concept to describe similarity and convert these informal concepts into mathematical equations.” Doan is also working with his advisor, Chandan Reddy, on research with Criteo, a leading advertising company that has made a significant investment in machine learning.

“Having worked in the advertising industry, solving computational problems in this field is of interest to me, as well, and is a great opportunity,” Doan said.