Edward Fox honored as inaugural inductee in ACM SIGIR Academy

Edward Fox, professor of computer science and Sanghani Center faculty member

The Association for Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) has announced that Edward Fox, professor in the Virginia Tech Department of Computer Science and faculty at the Sanghani Center for Artificial Intelligence and Data Analytics, is one of 25 inductees from across the globe in its inaugural SIGIR Academy. 

The inaugural academy inductees, drawn from academia, industry, and beyond, are principal leaders in information retrieval whose significant contributions have shaped the discipline or industry. Click here to read more about Edward’s inauguration.


Sanghani Center Student Spotlight: Xiaolong Li

Graphic is from the paper “Category-Level Articulated Object Pose Estimation.”

Xiaolong Li is a Ph.D. student in computer engineering. His main interest is in computer vision, with a focus on deep 3D representations learning for dynamic scene understanding. 

“Building robust smart algorithms will help machines understand the 3D world around us,” Li said.

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Sanghani Center Student Spotlight: Jesse Harden

Graphic is from the paper “A Specification Language for Matching Mistake Patterns with Feedback.”

Ph.D. student Jesse Harden’s current research is focused on large, high-resolution displays and their use in and benefits for data science.

“I am particularly interested in how we can better design software for large displays for data science. And in the future, I hope to look into how machine learning can be used to improve interactions with large screen UIs for both individual and collaborative use scenario,” said Harden, whose concentration in this area was influenced by reading the past works of his advisor, Chris North, and through their subsequent discussions.

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Sanghani Center Student Spotlight: Brian Keith

Graphic is from the paper “Narrative Maps: An Algorithmic Approach to Represent and Extract Information Narratives”

Having earned two bachelor of science degrees, one in mathematics and one in engineering, and a master’s degree in informatics, all from UniversidadCatólica del Norte, Chile, Brian Keith was looking for a flexible Ph.D. program. The Virginia Tech Department of Computer Science provided that flexibility and led him to the Sanghani Center where interdisciplinary data science is a key focus.

In his Ph.D. research, Keith, co-advised by Chris North and Tanushree Mitra —  is exploring online information narratives, in particular, how to represent, extract, and visualize them. He is also analyzing the issue of how misinformation spreads in these narratives.

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Sanghani Center Student Spotlight: Yali Bian

Yali Bian, Ph.D. student in the Department of Computer Science
Graphic from the paper “DeepVA: Bridging Cognition and Computation through Semantic Interaction and Deep Learning” 

According to Yali Bian, the Sanghani Center’s proclivity for encouraging interdisciplinary research is an added benefit while working on his dissertation topic, “Interactive Deep Learning for Semantic Interaction.” It encompasses several different research areas like human computer interaction, deep learning, visual analytics, and explainable AI. 

Bian is exploring ways to provide user-friendly interactive visualization systems to users unfamiliar with deep learning so that they can make full usage of powerful deep learning models.

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Sanghani Center Student Spotlight: Bipasha Banerjee

When Bipasha Banerjee was looking for a Ph.D. program she had one major criteria: it had to give the highest importance to research. With her continuing passion for knowing more, she wanted to delve deeper into open questions and learn how to solve them.

“The quality of research in computer science at Virginia Tech is unparalleled and professors associated with the Sanghani Center are involved in projects that encompass a large range of real-world issues,” said Banerjee. “I realized this was the right fit for me and, thankfully I was accepted and started an exciting journey of research.”

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Sanghani Center Student Spotlight: Po-Han Chen

Po-Han Chen, Master’s student in the Department of Computer Science
Graphic is from the paper “RISECURE: Metro Incidents And Threat Detection Using Social Media”

Po-Han Chen, a master’s degree student in computer science, was on the research team for the paper, “RISECURE: Metro Incidents And Threat Detection Using Social Media,” that appeared in the proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) held virtually in December.

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Subhodip Biswas receives Journeyman Fellowship from Army Research Lab

Subhodip Biswas, Ph.D. student in the Department of Computer Science

Subhodip Biswas is the recipient of the Journeyman Fellowship through the DEVCOM Army Research Laboratory (ARL) Research Associateship Program (RAP) administered by the Oak Ridge Associated Universities (ORAU). This fellowship will provide Biswas the opportunity to work on Bayesian optimization techniques for automated machine learning (AutoML) and robust AI systems.

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Sanghani Center Student Spotlight: Ola Karajeh

Ola Karajeh, Ph.D. student in the Department of Computer Science
Graphic is from the paper “Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach”

In her Ph.D. research, Ola Karajeh is investigating efficient solutions to process social media such as Twitter for monitoring public health.

She is particularly interested in the brittleness of these systems, e.g., how non-informational tweets can lead to failure of public health monitoring systems. “Since many institutions report success from building supportive decision making systems based on data collected and processed from sources like Twitter, it is important to identify which posts are non-informational,” she said. 

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Virginia Tech researchers garner two major awards in COVID-19 forecasting challenges

Nikhil Muralidhar, a Ph.D. student at the Sanghani Center, is one of the Virginia Tech researchers on the winning DeepOutbreak team.

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.