The Sanghani Center is home to high-profile research, garnering recognition within and beyond the data analytics community.
Our talented team has been recognized with many competitive research awards and featured in major news and media outlets such as the Wall Street Journal, Newsweek, the Boston Globe and the Chronicle of Higher Education.
DeepOutbreak, a team of researchers from Virginia Tech, Georgia Tech, and the University of Iowa, has taken first place in the COVID-19 Symptom Data Challenge.
The competition explores how Facebook symptom survey data can enable earlier detection and improved situational awareness of COVID-19 and flu outbreaks that can help both public health authorities and the general public make better decisions.
The first place award, announced by Catalyst @Health 2.0 in late December, and the team’s work will be featured on the Facebook Data for Good blog. Facebook was one of the sponsors of the challenge. Click here to read more about the challenge.
Virginia Tech’s growing impact in the greater Washington, D.C., metro area will receive a significant boost thanks to a multimillion-dollar gift from Octo founder and CEO Mehul Sanghani ’98 and his wife, Hema Sanghani ’99.
The couple’s $10 million gift primarily supports the newly renamed Sanghani Center for Artificial Intelligence and Data Analytics, which will be headquartered in the first academic building at the university’s Innovation Campus in Alexandria, Virginia. A majority of the gift is endowed to support recruiting, research, and fellowships at the center, which has operated since 2011 and was formerly known as the Discovery Analytics Center. Funding will also be allocated toward a Sanghani Center scholars program which will afford scholarship opportunities to underrepresented minorities to pursue graduate degrees with a focus on artificial intelligence.
Reflecting on his experience, Wang, a senior at Thomas Jefferson High School for Science and Technology in Alexandria, Virginia, said that the two most valuable things he learned are first, while some of the approaches you try do not work as planned, they could serve as stepping stones to the final model and second, “speak up and be unafraid of sharing failures so as not to get stuck in a single direction.”
Wang, whose interest lies in social media mining and natural language processing, worked under the supervision of Chang-Tien Lu, professor of computer science, and Lu’s Ph.D. student Kaiqun Fu.
the graduates at Virginia Tech’s 2020 Fall commencement are five Ph.D.’s and six
master’s students at the Discovery Analytics Center.
“This year has certainly been a challenging one but our students have persevered. Remotely, they completed required courses and successfully finalized and defended their research,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and director of the center. “We are very proud of all they have accomplished and wish them continued success in their new professional positions.”
Nearly half the world’s forests are under threat of deforestation and forest degradation.
Forests are at most risk of being destroyed by degradation — slashed trees, bare clearings, newly formed trenches and water gullies, and water clouded by eroding soil — which often leads to deforestation. Forest degradation has an even greater environmental, economic, and social impact because it not only affects the structure and function of a forest, but also lowers its capacity to provide goods and ecosystem services to help keep air and water clean, provide wildlife and humans with shelter and food, and capture carbon. More than three-quarters of the world’s land-based species live in forests, and over 1.5 billion people rely directly on forests for their livelihoods. Click here to read more.
Akshita Jha’s primary research focuses on how to prevent automated machine learning models from exacerbating existing biases.
“As an example,” Jha said, “the commercial algorithm, COMPAS, used by judges and officers across the United States to assess a defendant’s likelihood to re-offend has been shown to discriminate unfairly against African American defendants.”
Yi-Chun Chang, 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”
Yi-Chun Chang, who holds a bachelor’s degree in business information management from National Taiwan University, was drawn to pursue a master’s degree in computer science at Virginia Tech by its reputation for quality research and the prospect of working Chang-Tien Lu, now his advisor.
“Being a student at the Discovery Analytics Center is amazing,” said Chang. “We have plenty of resources and so many great opportunities to collaborate.”
Chang’s current project with Lu is a collaboration with a Maryland firm funded by the Washington Metropolitan Area Transit Authority (WMATA). The team is developing an advanced spatiotemporal event detection system of several layers to deal with data preprocessing, information extraction, threat level analysis, and visualization and extract security-related information from social media contents that can help metro police improve security on trains and at metro stations.
The Discovery Analytics Center continually brings together computer scientists, engineers, and statisticians to meet the research and workforce needs of today’s data-driven society. This Fall, DAC welcomes new faculty member Lifu Huang. He has joined the Virginia Tech Department of Computer Science as an assistant professor, having earned his Ph.D. in computer science at the University of Illinois Urbana-Champaign.
Huang’s primary research interests are in the fields of natural language processing, machine learning and artificial intelligence. He is specifically interested in building efficient models and benchmarks that can encourage machines to perform human-level intelligence.
Chang-Tien Lu, professor in the Department of Computer Science and associate director of DAC
The challenge of detecting threats in war zones is even greater when assessing the possibility of an insider attack.
“Seemingly innocent insiders can become dangerous due to a number of circumstances including personal relationships and geospatial environments,” said Chang-Tien Lu, a professor in the Department of Computer Science, associate director of the Discovery Analytics Center, and a faculty member in the National Science Foundation- sponsored UrbComp program