Three funded fellows earn UrbComp graduate certificate this spring

Stacey Clifton (left), Michelle Dowling (center), and Moeti Masiane (right)

Three funded UrbComp fellows, Stacey Clifton, Michelle Dowling, and Moeti Masiane, earned the graduate certificate in urban computing this spring. The certificate is offered through the National Science Foundation-sponsored multidisciplinary UrbComp Program administered by the Discovery Analytics Center.

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Congratulations to DAC’s 2020 Spring and Summer Graduates!

Among Virginia Tech graduates celebrating their achievements today include four Ph.D. and five master’s students at the Discovery Analytics Center.

Four Ph.D. students and one master’s student plan to complete degrees during the summer.

“The thoughtful and impactful research our students have engaged in while pursuing their graduate degrees has been recognized by many major academic conferences and is testament to their hard work,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and director of the center.

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DAC Student Spotlight: Gopikrishna Rathinavel

Gopikrishna Rathinavel, DAC M.S. student in the Department of Computer Science

Gopikrishna Rathinavel was introduced to machine learning through the biotechnology courses he took as an undergraduate.

“Eager to learn more, I began attending lectures by industry experts in machine learning,” Rathinavel said. “Soon I was captivated by the potential that machine learning offers as a discipline. It can add valuable insights in any domain where there is some data to exploit.”

He also began following the work of Discovery Analytics Center Director Naren Ramakrishnan, who is now his advisor, and other Virginia Tech faculty.

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DAC Student Spotlight: Omer Zulfiqar

Omer Zulfiqar, DAC master’s student in the Department of Computer Science.

Graphic is from the paper, “RIDE-SECURE: Metro Security Incidents And Threat Detection Using Social Media”

After graduating from Virginia Tech in December 2018 with a bachelor of science degree in electrical engineering and a minor in computer science, Omer Zulfiqar moved to northern Virginia to be closer to his family. He was also in close proximity to the university’s location in the greater Washington, D.C. area.g

In Fall 2019, he began pursuing a master’s degree in computer science and once again, chose Virginia Tech, this time at the Falls Church campus.

“Virginia Tech is a world renowned university in the field and at the Discovery Analytics Center I am able to work on interdisciplinary collaborations guided by incredible faculty, like my advisor Dr. Chang-Tien Lu, who are doing some amazing research work in the fields of artificial intelligence, machine learning, and data mining,”  Zulfiqar said.

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Research award aims to develop new algorithms for information extraction and understanding from scholarly literature

Naren Ramakrishnan, Director of DAC and Professor in the Department of Computer Science

The Discovery Analytics Center has received a research award from the Center for Security and Emerging Technology (CSET) at Georgetown University to support data-informed analysis for policymakers  concerning emerging technologies and their security implications. DAC will develop methods to extract novel insights at scale from full-text analytics of publications to better understand emerging technologies and their prevalence, spatial and temporal trends, and relationships.

“Algorithmic components developed by DAC will go into a high-performance pipeline that enables inspection of extracted patterns as well as the lineage of data transformations underlying the patterns,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and DAC director, who is the principal investigator for the project.

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DAC Student Spotlight: Andreea Sistrunk

Andreea Sistrunk, DAC Ph.D. student in Department of Computer Science

Graphic is from the paper “REGAL: A regionalization framework for school boundaries”

When Andreea Sistrunk started taking classes at Virginia Tech in the fall of 2014 she had left her job as a full time teacher in northern Virginia to devote more time to her two young daughters, ages three and seven.

“It was becoming more difficult for me to hold a full time job and be a good mother so I chose to take a break from work,” Sistrunk said. “I used a sort of ‘mom’s night out’ to enroll in a graduate course at Virginia Tech because I really missed learning new things.”

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DAC Student Spotlight: Nikhil Muralidhar

Nikhil Muralidhar, DAC and UrbComp Ph.D. student in the Department of Computer Science

Graphic is from Muralidhar’s paper on “PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly”

Choosing to pursue a Ph.D. in computer science at Virginia Tech was easy for Nikhil Muralidhar.

“Virginia Tech was my top choice for good reason,” Muralidhar said. “It is known for its quality research and interdepartmental collaborations, for encouraging students to work on real world interdisciplinary applications, and for pioneering programs like UrbComp.”

Also factoring in his decision was the opportunity to join the Discovery Analytics Center.

“I had been following DAC’s track record of high quality, practical research since I was a Virginia Tech undergraduate. I am happy to be part of a rare breed of research labs with both extensive industrial and academic collaborations. The facilities are state-of-the-art and the faculty are approachable, helpful, and use their experience to guide their students to become successful researchers,” said Muralidhar, who is advised by Naren Ramakrishnan.

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DAC Student Spotlight: Lei Zhang

Lei Zhang, DAC Ph.D. student in the Department of Computer Science

Graphic is from Zhang’s research on “Situation-Based Interpretable Learning for Personality Prediction in Social Media”

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.

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DAC Student Spotlight: Mohammad Raihanul Islam

Mohammad Raihanul Islam, DAC Ph.D. student in the Department of Computer Science

Graphic is from Islam’s paper on “RumorSleuth: joint detection of rumor veracity and user stance”

Classifying rumors and fake news in social media is the focus of Mohammad Raihanul Islam’s work at the Discovery Analytics Center.

“A rumor generally refers to an interesting piece of information — widely disseminated through a social network — that is not easy to substantiate,” said Islam, a Ph.D. student in computer science.

Later, it can turn out to be true, false, or remain unverified.

“The threat of rumors and fake news is very real and identification is crucial because rumors and fake news can lead to deleterious effects on users and society,” he said. “For example, spreading unverified malicious content could cause severe economic downfalls within a short period of time.”

The objective of his research, he said, is to develop a range of machine learning methods to effectively detect and characterize rumor veracity in social media.

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DAC Student Spotlight: Debanjan Datta

Debanjan Datta, DAC Ph.D. student in the Department of Computer Science

Graphic is from Datta’s paper on ”Detecting Suspicious Timber Trades”

Debanjan Datta’s interest in data mining focuses on systems that perform anomaly detection with both interpretability and the ability to incorporate domain knowledge and human input.

In a recent Discovery Analytics Center study with the World Wildlife Fund, Datta developed a framework that can apply machine learning on massive trade datasets to detect patterns of suspicious timber records that relate to possible illegal trade. He shared results of the study, “Detecting Suspicious Timber Trades,” at the Conference on Innovative Applications of Artificial Intelligence (IAAI) earlier this month.

The research involves analyzing, record-by-record, thousands of lines of export and import data.

“By analyzing available timber data, along with open source domain knowledge, we are trying to develop software and algorithms that will help flag suspicious timber at the border in real time. Such a human-machine approach can improve both efficiency and effectiveness,” Datta said.

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