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.
Cherie Poland earned a Master of Engineering from the Department of Computer Science’s first new graduate program for the Virginia Tech Innovation Campus. Photo courtesy of Cherie Poland
This is the latest entry on Poland’s list of achievements. To name only a few, she was issued one European patent and had five of her U.S. patent applications filed; created and later sold a biotech company; ran her family-owned cattle ranch (while holding a full-time position as a biotech patent examiner at the U.S. Patent and Trademark Office); and earned six college degrees, including a J.D.
Spring 2022 Commencement ceremonies and related events are under way on Virginia Tech campuses in Blacksburg and in the greater metropolitan D.C. area.
“We celebrate our graduates who have persevered over hurdles raised by the Covid pandemic to reach their academic goals. For longer than anyone would have suspected at the onset of the pandemic, this group of students had to adapt to a virtual environment. Online, they attended classes, met with their advisors, conducted research, presented papers at conferences, and worked at internships,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science at Virginia Tech and director of the Sanghani Center for Artificial Intelligence and Data Analytics. “We are proud of all they have accomplished during their years at the center and wish them continued success as they begin their professional careers.”
Following is a list of Sanghani Center graduates:
Ph.D.
Chidubem Arachie, advised by Bert Huang, has earned a Ph.D. in computer science. His research interest lies in developing algorithms for weakly supervised learning. The title of his dissertation is “Learning with Constraint-Based Weak Supervision.” Arachie is joining Google in California as a software engineer.
Yali Bian, advised by Chris North, has earned a Ph.D. in computer science. His research interests include human-computer interaction, visual analytics, machine learning, and machine teaching. The title of his dissertation is “Human-AI Sensemaking with Semantic Interaction and Deep Learning.” Bian is joining the Human and AI Systems Research (HAR) Lab at Intel Labs, Santa Clara, California, as a research scientist.
Subhodip Biswas,advised by Naren Ramakrishnan, has earned a Ph.D. in computer science. His primary research lies in spatial data mining, geographic information systems, education, and crowdsourcing. The title of his dissertation is “Spatial Optimization Techniques for Redistricting.” He has also earned a graduate certificate in urban computing. Biswas is joining the AI verification team at the autonomous vehicle company Zoox in Foster City, California.
Debanjan Datta, advised by Naren Ramakrishnan, has earned a Ph.D. in computer science. Datta’s research focus is on data mining and machine learning, with a special interest in algorithms on anomaly detection and tabular data. The title of his dissertation is “A Framework for Automated Discovery and Analysis of Suspicious Trade Records.” Datta is joining Amazon Web Services (AWS) as an applied scientist.
Chen Gao, advised by Jia-Bin Huang, has earned a Ph.D. in electrical and computer engineering. His research interest lies in the field of computational photography and computer vision. He is focusing on view synthesis and video manipulation. The title of his dissertation is “Learning Consistent Visual Synthesis.” Chen will be joining Meta in Seattle, Washington, as a research scientist.
Taoran Ji, advised by Chang-Tien Lu, has earned a Ph.D. in computer science. His research interests include natural language processing, text mining, and machine learning. The title of his dissertation is “On Modeling Dependency Dynamics of Sequential Data: Methods and Applications.” Ji has joined Moody’s Analytics in New York, as director, artificial Intelligence and machine learning.
Xiaolong Li, advised by Lynn Abbott, has earned a Ph.D. in electrical and computer engineering. His primary research interest is in the area of computer vision, with a special focus on deep 3D representations learning toward dynamic scene understanding. The title of his dissertation is “3D Deep Learning for Object-Centric Geometric Perception.” Li is joining AWS AI in Seattle, Washington, as an applied scientist.
Yuliang Zou, advised by Jia-Bin Huang, has earned a Ph.D. in electrical and computer engineering. His research interest lies in designing label-efficient and/or robust visual understanding methods. The title of his dissertation is “Label-Efficient Visual Understanding with Consistency Constraints.” Zou is joining Waymo, an autonomous driving technology company in Mountain View, California, as a research scientist.
Master’s Degree
Larissa Basso, advised by Chang-Tien Lu, has earned a master’s degree in computer science. Her primary research focus is satellite image retrieval. The title of her thesis is “CLIP-RS: A Cross-modal Remote Sensing Image Retrieval Based on CLIP, Northern Virginia Case Study.”
Chih-Fang Chen, advised by Chang-Tien Lu, has earned a master’s degree in computer science. His primary research interest is urban computing. The title of his thesis is “Metrohelper: A Real-time Web-based System for Metro Incidents Detection Using Social Media.” Chen is joining Amazon as a software developer engineer.
Kai-Hsiang Cheng, advised by Chang-Tien Lu, has earned a master’s degree in computer science. His primary research interests are applied machine learning and data mining. The title of his thesis is “Leverage Fusion of Sentiment Features and Bert-based Approach to Improve Hate Speech Detection.” Cheng is joining Gettr in New York City as software developer.
Riya Dani, advised by Ismini Lourentzou, has earned a master’s degree in computer science. Her primary research involves generating videos of unseen concepts using machine learning. The title of her thesis is “Concept Vectors for Zero-Shot Video Generation.” Dani is joining Amazon Web Services (AWS) in Northern Virginia as an associate solutions architect.
Xuan Li, advised by Lynn Abbott, has earned a master’s degree in electrical and computer engineering. His research focuses on continual learning that prevents a deep neural model from catastrophic forgetting in sequential tasks. The title of his thesis is “Referencing Unlabelled World Data to Prevent Catastrophic Forgetting in Class-incremental Learning.” Li is joining Amazon as software development engineer.
Gopikrishna Rathinavel, advised by Naren Ramakrishnan, has earned a master’s degree in computer science. His research focus is on using deep learning techniques for wireless anomaly detection. The title of his thesis is “Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback.”
Stephen Sun, advised by Chang-Tien Lu, has earned a master’s degree in computer science. His primary research interest is social media analytics. The title of his thesis is “Estimate Flood Damage Using Satellite Images and Twitter Data.” Sun is joining TikTok Inc. in Mountain View, California, as a software engineer.
Han Xu, advised by Lynn Abbott, has earned a master’s degree in electrical and computer engineering. His research focuses on skin segmentation without color information. The title of his thesis is “Color Invariant Skin Segmentation.”
As founder and CEO of Octo, a technology and consulting firm focused on using emerging technologies to solve the federal government’s most challenging problems, Mehul Sanghani ’98 is no stranger to opportunity, sacrifice, and even regret. He’ll impart these messages and others to graduates of Virginia Tech’s College of Engineering as the Distinguished Alumni Speaker for the spring 2022 commencement ceremonies on May 14. Read more about his life and philanthropy — including a generous endowment for the Sanghani Center for Artificial Intelligence and Data Analytics here.
Twelve highly accomplished Virginia Tech faculty experts in computer science and computer engineering have formally affiliated with the Virginia Tech Innovation Campus in Alexandria. This first cohort of Innovation Campus faculty will play a vital role in shaping the new campus by helping to establish key research themes, enhancing the project-based curriculum, and developing the campus governance structure. Among these 12 experts are Naren Ramakrishnan, Thomas L. Phillips Professor of Engineering and director of the Sanghani Center for Artificial Intelligence and Data Analytics and center faculty Chang-Tien Lu, professor of computer science and director of the computer science program, Northern Virginia. Read more here.
Graphic is from the paper “T3: Domain-Agnostic Neural Time-series Narration”
Would you like a virtual assistant that could go through chunks of large reports with pages upon pages of tables and raw numeric data and summarize it all in a short paragraph?
This is what Mandar Sharma is trying to accomplish with his Ph.D. research in the area of natural language generation.
“The progress of artificial intelligence depends heavily upon our ability to communicate with machines and natural language is the crux of human communication,” Sharma said. The paper, “T3: Domain-Agnostic Neural Time-series Narration,” which he presented at the 2021 IEEE International Conference for Data Mining, generates succinct narratives that describe large time-series datasets.
“With a dataset of time-series and narrative pairs, a promising direction for future exploration lies in learning direct mappings from numbers to text, extending beyond just time-series,” said Sharma, who is advised by Naren Ramakrishnan.
They are exploring how to create explanations of the effects of semantic interactions on a deep learning model through the analysis of perturbations and differences in the model after interactions.
“Through these explanations, we hope to demonstrate how models adjust when people inject prior knowledge into them through semantic interaction and validate whether the updated model adequately captures this prior knowledge,” said Faust, who earned her Ph.D. in computer science from the University of Arizona in December 2021.
“Dr. North was at the top of my list,” she said. “Together, we crafted an application, including a research proposal, a fellowship plan, and a mentorship plan, and submitted it to the program.”
January 21, 2020 – Students and faculty of the Data Analytics Center work together at the Virginia Tech Research Center – Arlington. (Photo by Erin Williams/Virginia Tech)
Virginia Tech and Amazon are partnering to advance research and innovation in artificial intelligence and machine learning. The Amazon – Virginia Tech Initiative for Efficient and Robust Machine Learning will include machine learning-focused research projects, doctoral student fellowships, community outreach, and an establishment of a shared advisory board.
“This partnership affirms the value of our connection to Amazon as we scale up project-based learning and research programs in artificial intelligence and machine learning,” said Virginia Tech President Tim Sands. “Building Virginia Tech’s strength and expertise in these fields will support critical technological advancements and our commitment to fuel workforce development in the commonwealth.”
“We are delighted to collaborate with Virginia Tech in launching this new initiative which brings together the top talent in our two organizations in a joint mission to achieve ground-breaking advances in robust machine learning,” said Prem Natarajan, vice president of Alexa AI – Natural Understanding at Amazon. “The proximity of this initiative to Amazon’s HQ2 will catalyze research efforts that leverage the depth of talent in the Northern Virginia area to address some of the most pressing challenges in AI.” To learn more about the initiative which will be housed in the College of Engineering and led by Sanghani Center for Artificial Intelligence and Data Analytics researchers, read full story here.
The Imageomics Institute will create a new field of study that uses images of living organisms to understand biological life processes.
Researchers in three different disciplines at Virginia Tech are partnering in a $15 million grant from the National Science Foundation (NSF) to establish an institute in the new field of “imageomics,” aimed at creating a new frontier of biological information using vast stores of existing image data, such as publicly funded digital collections from national centers, field stations, museums, and individual laboratories.
The goal of the institute is to characterize and discover patterns or biological traits of organisms from images and gain insights into how function follows form in all areas of biology. It will expand public understanding of the rules of life on Earth and how life evolves.
One of 10 finalists in the Alexa Prize SimBot Challenge, Virginia Tech’s team members meet regularly for updates on their specific work and overall progress on the project. The winner will be announced in 2023. Photo by Andrew Cybak for Virginia Tech.
A Virginia Tech team from the Sanghani Center for Artificial Intelligence and Data Analytics is one of 10 finalists chosen to compete in the Alexa Prize SimBot Challenge. The challenge focuses on advancing the development of next-generation virtual assistants that continuously learn and gain the ability to perform common sense reasoning to help humans complete real-world tasks.
“The SimBot should be able to understand the intention of a task as well as any instructions or feedback it receives from a user and interpret the environment to correctly predict what action is needed to complete it,” said Lifu Huang, assistant professor of computer science and faculty at the Sanghani Center. Click here to read more about how the team will tackle this challenge.
Graphic is from the paper “Sensemaking Strategies with Immersive Space to Think”
Focused on using virtual/augmented reality for day-to-day productivity tasks, Kylie Davidson is investigating how immersive technologies can be used during sensemaking.
“The goal is to add computational analytics to our software prototype to assist the user in real-time while they complete a sensemaking task,” she said.
After graduating with a bachelor’s degree in computer science from James Madison University, Davidson chose a Ph.D. program at Virginia Tech where she could conduct cutting-edge computer science research with real-world impact.”
“At the Sanghani Center,” she said, “I get to work with a community of researchers who are solving real-world problems every day.”
