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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.” 

With restrictions to working in physical office space still in effect, graduate students at the Sanghani Center are working remotely this summer for companies, labs, and programs from coast to coast. Students are not only gaining real-world experience from internships and other opportunities but, in many cases, they are also able to advance their own research interests.

Following is a list of Sanghani Center students and the work they are doing:

Badour AlBahar, a Ph.D. student in electrical and computer engineering, is a computer vision intern at Adobe Vision group in San Jose, California. She is working on human reposing and animation. Her advisor is Jia-Bin Huang.

Sikiru Adewale, a Ph.D. student in computer science, is a software development engineer intern at Amazon Web Service in Seattle, Washington. He is working on data transfer and storage on the AWS snowball device. His advisor is Ismini Lourentzou.

Vasanth Reddy Baddam, a Ph.D. student in computer science, is an research intern at Siemens in Princeton, New Jersey. He is working on contributing to industrial research projects on leveraging machine learning to analyze multi-agent reinforcement learning (MARL) algorithms and implement them. His advisor is Hoda Eldardiry. 

Subhodip Biswas, a Ph.D. student in computer science, is working on Bayesian optimization techniques for automated machine learning (AutoML) and robust artificial intelligence systems as part of the Journeyman Fellowship he received from the DEVCOM Army Research Laboratory (ARL) Research Associateship Program (RAP) administered by the Oak Ridge Associated Universities (ORAU). His advisor is Naren Ramakrishnan.

Jie Bu, a Ph.D. student in computer science, is a research intern at Carbon 3D in Redwood City, California. He is working on artificial intelligence-powered computational geometry. His advisor is Anuj Karpatne.

Si Chen, a Ph.D. student in computer engineering, is a research intern at InnoPeak Technology in Seattle, Washington. She is working on research on model privacy protection. Her advisor is Ruoxi Jia.

Kai-Hsiang Cheng, a master’s degree student in computer science, is an intern at GTV Media Group in New York City. He is working on the content management system of the media’s platform. His advisor is Chang-Tien Lu.

Riya Dani, a master’s degree student in computer science, is a software engineer intern at Microsoft. She is working on web application developments under Azure. Her advisor is Ismini Lourentzou.

Debanjan Datta, a Ph.D. student in computer science, is an intern on the Amazon Web Services team at Amazon in Seattle, Washington. He is working on time series characterization and classification.  His advisor is Naren Ramakrishnan.

Arka Daw, a Ph.D. student in computer science, is an applied scientist intern at Amazon Web Services Lambda Science Team in Seattle, Washington.  He is working on developing an automated causal machine learning framework for setting up experiments and estimating causal effects from observational data. His advisor is Anuj Karpatne.

Yue Feng, a Ph.D. student in electrical and computer engineering, is an intern with the Snap Research Creative Vision Team in Santa Monica, California. She is working on a 3D computer vision project. Her advisor is Jia-Bin Huang.

Chen Gao, a Ph.D. student in electrical and computer engineering, is a research intern at Google in Cambridge, Massachusetts. He is working on creating video panoramas using a cellphone. His advisor is Jia-Bin Huang.

Jianfeng He, a Ph.D. student in computer science, is an intern at Tencent AI Lab in Seattle,Washington. He is working on research about multi-modal dialogue with mentors Linfeng Song and Kun Xu. His advisor is Chang Tien-Lu.

Taoran Ji, a Ph.D. student in computer science, is an intern at Moody’s Analytics in New York City. He is working on analyzing credit and financial data for the global financial markets, which will drive algorithmic improvements in Moody’s Analytics core machine learning and artificial intelligence-driven products. His advisor is Chang-Tien Lu.

Adheesh Juvekar, a Ph.D. student in computer science, is a machine learning and natural language processing intern at Deloitte & Touche LLP. He is working on automatically extracting relevant information from transactional invoices using state of the art deep learning techniques. His advisor is Edward Fox.

M. Maruf, a Ph.D. student in computer science, is a machine learning engineering intern at Qualcomm GNSS/location team in Santa Clara, California. He is applying machine learning techniques to hybrid technology fusion for navigation/positioning in mobile, wearable, automotive, and micro-mobility applications. His advisor is Anuj Karpatne.

Nikhil Muralidhar, a Ph.D. student in computer science, received an Applied Machine Learning Summer Research Fellowship at Los Alamos National Lab in Los Alamos, New Mexico, to work with researchers on physics-informed machine learning for modeling adsorption equilibria in fluid mixtures. His advisor is Naren Ramakrishnan. 

Makanjuola Ogunleye, a Ph.D. student in computer science, is an application support engineer intern at Northwestern Mutual in Milwaukee, Wisconsin. His duties include coding, testing, and implementing complex programs from user specifications. He is also performing client data analysis to support engineering technology to improve and facilitate customer success. His advisor is Ismini Lourentzou.

Nishan Pokharel, a master’s degree student in computer science, is a software engineering intern at Capital One in Mclean, Virginia.  He is working on network infrastructure automation. His advisor is Chris North

Avi Seth, a master’s degree student in computer science, is serving as a graduate team leader this summer for Virginia Tech’s Data Science for the Public Good program. The group works on projects that address state, federal, and local government challenges around today’s relevant and critical social issues. His advisor is Ismini Lourentzou.

Mia Taylor, a master’s degree student in computer science, is a software development intern at Amazon Web Services in Seattle, Washington. Her team is working with Comprehend AutoML which allows customers to build customized natural language processing models using their own data. Her advisor is Lifu Huang.

Yiran Xu, a Ph.D. student in electrical and computer engineering, is an intern with the Snap Research Creative Vision Team in Santa Monica, California. He is working on 3D human reconstruction and video generation/manipulation. His advisor is Jia-Bin Huang.

Shuaicheng Zhang, a Ph.D. student in computer science, is a natural language processing (NLP) research intern at Deloitte in New York City. He is part of the Audit and Assurance AI innovation team, working on open information extraction on internal control files to help auditors effortlessly process these files. His advisor is Lifu Huang.

Yuliang Zou, a Ph.D. student in electrical and computer engineering, is a research intern at Waymo in Mountainview, California. He is working on the perception problem for self-driving cars.  His advisor is Jia-Bin Huang.

Interested in data mining and machine learning, Taoran Ji, a Ph.D. student in computer science, said he was drawn to the Discovery Analytics Center because it plays an active role in these fields.

“There are so many projects at the center that provide great opportunities to practice these techniques in real world applications,” Ji said.

Ji, advised by Chang-Tien Lu, has focused his research on a range of topics, all of which he has been able to explore by collaborating with Lu and other faculty and students at DAC. These include event detection/prediction and associated applications such as civil unrest detection, airport threat detection, transit disruption detection, and emerging science and technology prediction.

Among his published papers, two were included in proceedings at conferences held this year.

“Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks” forecasts the popularity and value of a technology of interest by developing a deep learning model to predict the number of citations that will be received by a patent or paper of interest, which can be used as an indicator of emerging technologies. Ji presented this paper at the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019) in Macao, China, in August.

This research reflects Ji’s  interest in discovering and forecasting emerging technologies which, he said,  have great potential in the research field and can bring value to the market.

“We were able to attain access to a U.S. patent dataset, which can be viewed as the direct scientific output of science and technology activity in the industry,” said Ji. “Inspired by previous works in patent-based technology, we saw the potential value of forecasting a patent’s future citations.”

The second paper, “Feature Driven Learning Framework for Cybersecurity Event Detection,” leverages the huge volume of social media data to focus on using data mining and machine learning techniques to detect ongoing cybersecurity events and develop algorithms to automatically identify and collect online discussion and online complaints of abnormal status such as slow internet service and suspicious email logins. It was published in the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019).

Ji’s work also includes event detection using data from social media like Twitter.

“My team and I have developed a data mining method to identify tweets denoting abnormal or suspicious events — someone brings a knife to the airport, for example — which can potentially cause security problems,” said Ji.  “And in another study, we were able to detect metro service disruptions by analyzing tweets posted from the Washington, D.C., area.”

Some of this work is found in his other published papers: “Multi-Task Learning for Transit Service Disruption Detection”  (ASONAM 2018); “Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media” (CIKM 2017); and “Determining Relative Airport Threats from News and Social Media” (AAAI 2017).

Ji received his master’s degree in computer science from Xidian University, China. His projected Ph.D. graduation date is 2020.