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.
Andreea Sistrunk. Photo by Naren Ramakrishnan for Virginia Tech.
Andreea Sistrunk’s motto, “A best solution to everything is up to us to uncover,” evolved on her path to earning a Ph.D. in computer science at Virginia Tech’s Northern Virginia campus.
“In the beginning, I found myself overwhelmed and at times discouraged by how fast technology is advancing,” she said. “As hard as I was trying, I could not get the data I needed for my work.”
Sistrunk’s research for her dissertation is at the intersection of computer science, education policy, and geographical information systems and related to Redistrict, an online software platform built by a team of researchers at the Sanghani Center for Artificial Intelligence and Data Analytics to help school districts with their rezoning efforts.
Laura Freeman, deputy director of Virginia Tech’s National Security Institute and featured speaker at the expo’s Talent Marketplace, will share how the institute is preparing the present and future U.S. workforce for the integration of artificial intelligence systems across all sectors of the economy and society. Photo by Bill Petros for Virginia Tech.
Virginia Tech will exhibit at the first AI Expo for National Competitiveness at the Walter E. Washington Convention Center in Washington, D.C., on May 7-8.
Chaired by former chief executive officer of Google Eric Schmidt, the expo serves as a forum for industry, government, and academic research entities to exhibit some of the latest technological breakthroughs in areas such as artificial intelligence (AI), biotech, energy, networks, computing, microelectronics, manufacturing, and augmented reality. Leaders will discuss these advancements and their implications for U.S. and allied competitiveness.
Hosting alongside the second Ash Carter Exchange on Innovation and National Security, the event is free and open to the public but registration is recommended. For detailed information about the event, visit the expo’s online agenda.
Laura Freeman, deputy director of Virginia Tech’s National Security Institute, will be the featured speaker at the expo’s Talent Marketplace on the first day.
Additionally, Virginia Tech organizations that lead innovative research technologies in AI will demonstrate their expertise on the following topics at the university’s booth No. 506 on May 8. Among them is the Sanghani Center for Artificial Intelligence and Data Analytics.
Ph.D. student scholarship recipient Sangwoo Kim (at center) with faculty mentors Anuj Karpatne (at left) and Venkat Sridhar. Photo by Tonia Moxley for Virginia Tech.
The initiative builds upon a consistent collaboration between the two centers that began with the inauguration of CAIA in 2021. Faculty from the two centers have been working on joint research projects that includes a National Science Foundation-sponsored Convergence Accelerator project and some faculty are members of both centers.
Virginia Tech researchers elected in the 2023 class of AAAS Fellows are: (top row, from left) Eric Burger, Nancy Ross, Naren Ramakrishnan, (bottom row, from left) Barbara Ryder, Liwu Li, and Brenda Winkel. Virginia Tech photo
The American Association for the Advancement of Science (AAAS), one of the world’s largest general scientific societies and publisher of the Science family of journals, has named its 2023 class of fellows.
Six Virginia Tech researchers are named among the latest class of 502 scientists, engineers, and innovators. The newly elected AAAS Fellows represent the fields of biological sciences, chemistry, medical sciences, and engineering followed by neuroscience and physics.
“I congratulate our researchers who are being honored as lifetime fellows for their groundbreaking contributions to the scientific community,” said Dan Sui, senior vice president for research and innovation. “These highly regarded researchers are developing and improving technologies and innovations that inform new pathways in wireless communications, machine learning algorithms, mineral physics, plant metabolism, and diversifying the field of computing.”
Mehul Sanghani, chief executive officer and founder of Octo, will deliver the keynote address at Virginia Tech’s University Commencement ceremony on Friday, May 10.
Octo is a technology firm focused on solving national security’s most complex problems. In the last decade, Sanghani built and grew the company around the foundational belief of meeting, exceeding, and advancing customer missions.
Sanghani took a leap of faith founding Octo at the age of 30 with encouragement from his family and others. Since its inception in 2006, the company has experienced exponential success under his leadership.
Octo has been repeatedly recognized, catching the attention of a number of Fortune 100 companies as an acquisition target. In January 2023, IBM announced it was acquiring the company for just under $1.3 billion.
In 2021, a gift from Mehul and his wife, Hema Sanghani, also a Virginia Tech graduate, made a historic $10 million gift to their alma mater; $1.5 million of the gift was allocated to establish The Market of Virginia Tech, a first-of-its-kind on-campus food pantry to students facing food insecurity.
Graphic is the poster “Distributionally Ambiguous Multistage Stochastic Integer and Disjunctive Programs: Applications to Sequential Two-player Interdiction Games,” presented at the INFORMS Annual Meeting 2023.
Ph.D. student Sumin Kang was drawn to the Department of Industrial Systems Engineering by its prestigious faculty with particular expertise in optimization for logistics problems with uncertainty.
“As a logistics enthusiast, I found their focus aligned very well with my own interests,” said Kang, who is advised by Manish Bansal, core faculty at the Sanghani Center. “And the interdisciplinary environment fostering a multi-faceted approach in problem solving at the Sanghani Center added to Virginia Tech’s appeal.”
Kang’s research interests lie in optimization under uncertainty, with a focus on network optimization problems and vulnerability analysis.
“Specifically I am interested in optimization problems with incomplete information about distributions of uncertain parameters,” he said. “These optimization problems find an application in the network interdiction problem. The network interdiction problem involves a game between two players, the interdictor and the network user, where the network user aims to minimize the objective value like traveling cost and security threat level, while the interdictor aims to maximize disruption of network.
“Solving this problem is valuable for identifying network vulnerabilities, particularly in cases of unexpected disruptions,” said Kang. “My proposed solution approaches consider the interdictor’s varying risk appetite towards unknown distributions.”
Kang’s interest in this research began as a master’s degree student in logistics at Korea Aerospace University, when he started to struggle with logistic optimization problems, he said, because despite the prevalence of real-world uncertainty, the literature mainly focused on deterministic cases due to their high complexity. This motivated him to address the gap and contribute to the domain of optimization with uncertainty for large-scale problems.
(From left) Chang Lu, the Fred W. Bull Professor of Chemical Engineering; Daphne Yao, professor of computer science; and Xiaoting Jia, associate professor in the Bradley Department of Electrical and Computer Engineering. Photo by Peter Means for Virginia Tech.
An estimated one in six people suffer from a brain disorder worldwide, according to the American Brain Foundation. Current research has provided some insight into cell-communication inside the brain, but there are still a lot of unknowns surrounding how this crucial organ functions. What if there was a comprehensive map that took into consideration not just the biology of the brain, but the specific location where the biology occurs?
Researchers in the College of Engineering have developed a powerful, cost-effective method to do just that.
Chang Lu, the Fred W. Bull Professor of Chemical Engineering, has been leading a research project that could be groundbreaking for brain research. The newly published article in the journal Cell Reports Methods features interdisciplinary research along with faculty in two additional departments within the College of Engineering:
Poster presentation at CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling workshop during the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CPVR)
Medha Sawhney earned a bachelor’s degree from the Manipal Institute of Technology in India, where she majored in electronics and communications engineering, with a minor in data science. When considering a graduate degree in computer science, Sawhney was drawn to Virginia Tech and the Sanghani Center by a research-focused environment that offered opportunities to learn from and work with professors well known in their respective fields of research which interconnected well with her own.
“A research-focused environment makes it easy to concentrate on your work by providing interesting and challenging research projects; professors who guide you in every way; and funding opportunities via grants from organizations like the National Science Foundation,” she said. “And most professors – even if they are not your direct advisor — are extremely approachable to guide you or discuss problems.”
Sawhney entered the university as a master’s degree student but is now pursuing a Ph.D. She is advised by Anuj Karpatne.
Having worked in the domain of computer vision since her undergraduate years, Sawhney’s current research is at the intersection of computer vision and mechanobiology.
Two projects — supported by the NSF — predict the behavior and mechanics of human as well as bacteria cells. One of them involves predicting the force exerted by cells in order to be able to predict their movement using traction-force microscopy images collected in the field of mechanobiology.
“The physics knowledge that we are integrating in our machine learning methods includes phenomenological models of cell and bacteria migration and knowledge of the mechanical forces governing interactions between cells and fiber backgrounds,” she said.
The second project involves tracking the movement of bacteria cells to predict and also study the characteristics of their motion such as their velocity, their stickiness, and other such measures. This study is directed towards cancer research.
“The resolution of microscopy and the dense fibrous environment the bacteria is in makes it challenging to differentiate the bacteria in an image by just looking at it since the bacteria sometimes merges with the 3D media or goes inside,” she said. “We use artificially-generated motion and temporal features of the microscopic bacteria images as input to the machine learning model to be able to identify and track them.”
Sawhney gave a poster presentation of her work, “Detecting and Tracking Hard-to-Detect Bacteria in Dense Porous Backgrounds,” at a CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling workshop during the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CPVR) last fall.
This was preliminary work for the paper, “MEMTrack: A deep learning-based approach to microrobot tracking in dense and low-contrast environments,” which will be published in an upcoming volume of the Advanced Intelligent Systems journal.
Sawhney will also be presenting her work on bacteria tracking at the first Workshop on Imageomics during the Association for the Advancement of Artificial Intelligence (AAAI 24) conference next week.
She is also serving on the program committee for the workshop.
Projected to graduate in 2026, her ideal job would be one that offers challenges and in which her work would have an impact on society.
The Cloud-based Distributed Radio Frequency Machine Learning project team members at work. Photo by Isabella Rossi for Virginia Tech.
A student-led research team is working with Amazon to advance use cases for machine learning within the cloud for wireless communication applications.
The Virginia Tech National Security Institute is collaborating with Amazon Web Services (AWS) to give 11 undergraduate students and a graduate research assistant experience deploying state-of-the-art machine learning algorithms in the cloud for distributed radio frequency spectrum sensing through the Emerging Technology Research Fellowship. The fellowship aims to improve the performance of radio frequency spectrum sensing algorithms by leveraging multiple sensors collaborating through the cloud.
