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“Working with text data is challenging but that is what I like about it,” said Shane Bookhultz, a Ph.D. student in the Department of Statistics. “It is inherently noisy because of different mannerisms, choices of words, and tones. Unlike numerical data, which is pretty concrete, text data can have various interpretations.”

Bookhultz — who is also a research trainee in the National Science Foundation-sponsored Urban Computing graduate certificate program — was introduced to this research area by his advisor, Scotland Leman. Then he started exploring more text issues with different media.

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Along his educational path, Jianfeng He learned an important lesson: Having a good advisor should be the number one priority in choosing a Ph.D. program. The opportunity to work with Chang-Tien Lu drew him to Virginia Tech and the Discovery Analytics Center after spending a short period of time at another university.

He’s focus is on data analysis of social media and he is currently working on image editing based on user requests and text classification based on machine learning.

This research builds upon an interest that began while He was an undergraduate majoring in digital media technology at the Central China Normal University and required to learn media design software, including Adobe Photoshop, Adobe Premiere, and MAYA.

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Aditya Prakash, associate professor of computer science and faculty at the Discovery Analytics Center has moved from Blacksburg to DAC’s location at the Virginia Tech Research Center – Arlington.

“My work is frequently motivated by public health, urban computing, and web-related problems and this location is fertile ground for collaborations in these domains,” Prakash said. “Moving to the greater Washington D.C. metro area will help me further expand my research activities, due to its ‘one of its kind’ proximity to government agencies, companies, and hospitals/medical centers.”

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Next month Badour AlBahar will travel to Seoul, Korea, to present a paper, “Guided Image-to-Image Translation with Bi-Directional Feature Transformation” at the premier International Conference on Computer Vision (ICCV).

A second year Ph.D. student in the Department of Electrical and Computer Engineering, AlBahar said she is “extremely fortunate to be able to explore and broaden my knowledge in computer vision and machine learning with Professor Jia-Bin Huang and my fellow colleagues at the Discovery Analytics Center. Working with people from different backgrounds and experiences has enabled me to grow and learn in ways I never knew possible.”

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You Lu knew that the Discovery Analytics Center would be a great fit for his research when he applied to the Virginia Tech Ph.D. program in computer science. “I had heard about Professor Bert Huang and knew that he and I were working in a similar research area — graphical models,” said Lu. “I felt I could learn a lot from him and I am so glad he agreed to be my advisor.”

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With a master’s degree in computer science from Indraprastha Institute of Information Technology (IIIT) Delhi, Prerna Juneja joined Dell EMC where, for three years, she worked for the company’s flagship product VPLEX, a storage virtualization appliance that provides continuous availability and data mobility. She garnered four awards for her work there: the Dell Champion Award in 2018, and Excellence@Dell Bronze Award in 2018, 2017, and 2016.

Deciding to pursue a Ph.D. in computer science, Juneja said she chose Virginia Tech over other universities because of its faculty who work in cutting-edge interdisciplinary research in the area of human computer interaction. Her advisor is Tanushree Mitra.

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Davon Woodard will spend the 2019 Fall academic semester as a visiting scholar at the University of the Witswatersrand in Johannesburg, South Africa.

There, the Ph.D. student in the planning, governance, and globalization program in the School of Public and International Affairs and a research trainee in the National Science Foundation-sponsored Urban Computing (UrbComp) Certificate program administered through the Discovery Analytics Center, will conduct the first phase of research for his dissertation. He is comparing both online and offline social networks in two historically marginalized black communities — Johannesburg and Bronzeville in Chicago, Illinois — to get a better understanding of their structure, practices, and effects.  Click here to read more about Davon’s research on social networks.

Sneha Mehta has been selected to attend the Deep Learning and Reinforcement Learning Summer School (DLRLSS), from July 24 to August 2, in Edmonton, Alberta, Canada.

Mehta is a Ph.D. student in computer science at the Discovery Analytics Center, advised by Naren Ramakrishnan. In May, she began a summer internship as a data scientist at Netflix headquarters in Los Gatos, California, where she is researching novel methods to improve machine translation for subtitles.

“I applied to the Summer School because deep learning and reinforcement learning are very relevant to my work at problem solving both at DAC and at Netflix,” said Mehta. “Hearing directly from some of the pioneers in the field will be a great – and invaluable – experience.”

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Tanushree Mitra, assistant professor of computer science in the College of Engineering and a faculty member at the Discovery Analytics Center, has received a Social Media and Democracy Research Grant, giving her access to Facebook data to study how misinformation and other problematic content spread on the platform. This is the first time Facebook has given academics access to its data.

Mitra is among 60 international researchers — and one of only two women principal investigators — to receive the grant, funded by a number of leading foundations and administered through a Social Science One and Social Science Research Council collaborative partnership that bridges the gap between academics and the private sector.  Click here to read more about Mitra’s grant.

Jia-Bin Huang, assistant professor in the Bradley Department of Electrical and Computer Engineering and a faculty member at the Discovery Analytics Center, has received a Google Faculty Research Award to support his work in detecting human-object interaction in images and videos.

The Google award, which is in the Machine Perception category, will allow Huang to tackle the challenges of detecting two aspects of human-object interaction: modeling the relationship between a person and relevant objects/scene for gathering contextual information and mining hard examples automatically from unlabeled but interaction-rich videos.  Click here to read more about Jia-Bin’s Google Award.