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Among Virginia Tech graduates celebrating their achievements today include four Ph.D. and five master’s students at the Discovery Analytics Center.

Four Ph.D. students and one master’s student plan to complete degrees during the summer.

“The thoughtful and impactful research our students have engaged in while pursuing their graduate degrees has been recognized by many major academic conferences and is testament to their hard work,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and director of the center.

“We are always very proud of our graduates but especially so this year as they have had to persevere through some very unusual circumstances to achieve their goals,” Ramakrishnan said. “We wish them continued success as they venture into new career challenges at universities, research laboratories, and businesses.”

Ph.D. Spring graduates

Bijaya Adhikari, advised by B. Aditya Prakash, is receiving a Ph.D. in computer science. His research interests are data science and machine learning for large networks and data driven epidemiology. The title of his dissertation is “Domain-based Frameworks and Embeddings for Dynamics over Networks.” Adhikari is joining the Department of Computer Science at the University of Iowa in the fall as a tenure track assistant professor.

Tyler Chang, advised by Layne Watson, is receiving a Ph.D. in computer science. His research interests are numerical approximation, optimization, algorithms, parallel computing, data science, and scientific computing. The title of his dissertation is “Mathematical Software for Multi-objective Optimization Problems.” Chang is joining the Mathematics and Computer Science Division at Argonne National Laboratory in Chicago, Illinois. Specifically, he will work in the Laboratory for Applied Mathematics, Numerical Software, and Statistics as a postdoctoral appointee, a group he previously interned with.

Michelle Dowling, advised by Chris North and Mike Horning, is receiving a Ph.D. in computer science. She is also receiving a graduate certificate in urban computing, a National Science Foundation-sponsored program administered through DAC. Dowling’s research interests are human-computer interaction, data analytics, information visualization, and interactive data visualization. The title of her dissertation is “Semantic Interaction for Symmetrical Analysis and Automated Foraging of Documents and Terms.” Dowling is joining Grand Valley State University, her alma mater, as an assistant professor.

Mohammad Raihanul Islam, advised by Naren Ramakrishnan, is receiving a Ph.D. in computer science. His research interests are social network/media analysis, deep learning, and graph neural network. The title of his dissertation is “Detecting and Mitigating Rumors in Social Media.”  Islam is joining Amazon, Inc., as an applied scientist. 

Liuqing Li, advised by Edward Fox, is receiving a Ph.D. in computer science. His research interests are digital library, social analysis, machine learning, and deep learning. The title of his dissertation is “Event-related Collections Understanding and Services.” Li is joining Yahoo! as a research scientist.

Master’s Spring Graduates

Arjun Choudhry, advised by Naren Ramakrishnan, is receiving a master’s degree in computer science.  His research interests are narrative generation, blockchain technologies. His thesis is titled “The Art of Simplifying Graph Interpretation: Narrative Generation Using Causal Exploration of Directed Graphs.” Choudhry is joining Amazon, Seattle, as a software development engineer.

Jeffrey McCullen, advised by Chandan Reddy, received a master’s degree in computer science. His research interests are machine learning and data analytics in healthcare, and software engineering.  The title of his thesis is “Predicting the Effects of Sedative Infusion on Acute Traumatic Brain Injury Patients.”

Joseph Messou, advised by Jia-Bin Huang, is receiving a master’s degree in computer engineering. His research interests are computer vision and machine learning, efficient training methods for networks, and cybersecurity. The title of his thesis is “Handling Invalid Pixels in Convolutional Neural Networks.”  In the fall, Messou will be a Ph.D. student in computer engineering at the University of Maryland, College Park.

Shih-Yang Su, advised by Jia-Bin Huang, is receiving a master’s degree in computer engineering. His research interests are machine perception, visual representation learning, and reinforcement learning. His thesis is titled “Learning to Handle Occlusion for Motion Analysis and View Synthesis.” In the fall, Su will be a Ph.D. student in computer science at the University of British Columbia, where his research will focus on learning and understanding human motion for motion synthesis and character animations.

Ming Wang, advised by Chris North, is receiving a master’s degree in computer science. Her research interests are visual analytics and information visualization. Her thesis is titled “Bridging Cognitive Gaps Between User and Model in Interactive Dimension Reduction.” Wang is joining Salesforce as a software engineer.

Summer Ph.D. graduates

Zhiqian (Danny) Chen, advised by Chang-Tien Lu, will complete his Ph.D. in computer science. Chen’s research interests are graph mining, urban computing, network science. The title of his dissertation is “Graph Neural Networks: Techniques and Applications.” Chen will join the Computer Science and Engineering Department at Mississippi State University as assistant professor.

Tianyi Li, advised by Chris North, will complete her Ph.D. in computer science. Her research interests include developing systems for computer-supported cooperative work and devising visual analytics tools with user-centered design to combine and coordinate human and artificial intelligence in broader, real-world sensemaking processes. Her dissertation is titled “Solving Mysteries with Crowds: Supporting Crowdsourced Sensemaking with a Modularized Pipeline and Context Slices.”  Li will be joining Loyola University in Chicago as assistant professor.

Thomas Lux, advised by Layne Watson, will complete his Ph.D. in computer science. His research interests are approximation, optimization, and mathematical software. His dissertation is titled “Interpolants and Error Bounds for Modeling and Predicting Variability in Computer Systems.”

Moeti Masiane, advised by Chris North, will complete his Ph.D. in computer science. He has received a graduate certificate in urban computing, a National Science Foundation-sponsored program administered through DAC. Masiane’s research interests include information visualization, data modeling, insight, sampling, and perception modeling. The title of his dissertation is “Insight Driven Sampling for Interactive Data Intensive Computing.”

Summer master’s graduate

Milad Afzalan, advised by Hoda Eldardiry, will complete his master’s degree in computer science. His research interests include machine learning, pattern recognition, smart grid, and energy efficiency. The title of his thesis is “Household electricity load shape segmentation from smart meter data based on temporal patterns and power magnitude.” Afzalan, who will also be receiving a Ph.D. from Virginia Tech in civil engineering, will join ENGIE as a data scientist.

Zhiqian “Danny” Chen, DAC Ph.D. student in the Department of Computer Science

Generating new music inspired by existing music datasets is a major area of interest for Zhiqian “Danny” Chen, a Ph.D. student at the Discovery Analytics Center.

“Music, with its complex hierarchical and sequential structure and its inherent emotional and aesthetic subjectivity, is an intriguing research subject at the core of human creativity,” said Chen. “And because of rapid advances in data-driven algorithms such as deep learning, exploring computational creativity via machine learning approaches is increasingly popular.”

While this exploration has included some work on generative models for music, research that investigates the capabilities of deep learning for creative applications such as style transfer on images and video is limited, he said.

The paper, “Learning to Fuse Music Genres with Generative Adversarial Dual Learning,” aims to fill this space by exploring the idea of style fusion in music with generative adversarial dual learning. Chen presented the paper at the 2017 IEEE International Conference on Data Mining (ICDM) in New Orleans, Louisiana.

In November, Chen will attend ICDM 2018 in Singapore, where he will present “Rational Neural Networks for Approximating Jump Discontinuities of the Graph Convolution Operator,” a study on deep graph learning.

“Effective information analysis generally boils down to the geometry of the data represented by a graph,” said Chen. Typical applications include social networks, transportation networks, spread of epidemic diseases, neuronal networks, biological regulatory networks, telecommunication networks, and knowledge graphs, defined over non-Euclidean graph domains.

Chen’s research in this area focuses on modeling graphs in spectral domains for deriving representations for node level embeddings. He uses graph notions such as adjacency matrices or graph Laplacians to describe geometric structures and reveal latent patterns.

He holds a bachelor’s degree in software engineering and Japanese from Huazhong University of Science and Technology, China, and a master’s degree in software engineering from Peking University, China.

Advised by Chang-Tien Lu, Chen is projected to graduate with a Ph.D. in computer science in Fall 2019.

DAC Ph.D. student, Zhiqian Chen, presenting his paper at ICDM 2017.

The Discovery Analytics Center was strongly represented at the IEEE International Conference on Data Mining (ICDM) in New Orleans, Nov. 18-21, with a number of accepted research papers by DAC faculty and students and DAC faculty serving on committees and panels.

Research papers accepted for the conference include:

• “A Probabilistic Geographical Aspect-Opinion Model for Geo-tagged Microblogs”(Ph. D. student Aman Ahuja and Chandan Reddy, associate professor of computer science, collaborating with Carnegie Mellon University and Singapore University). Ahuja presented this paper at the main conference and received a student travel award.
• “Data-Driven Immunization”(Yao Zhang, Virginia Tech alumnus and currently an assistant professor at the University of Memphis; Anil Vullikanti, associate professor of computer science at the Biocomplexity Institute of Virginia Tech; Aditya Prakash, assistant professor of computer science; and the Oak Ridge National Laboratory). Prakash presented this paper — chosen as a Best Paper finalist – at the main conference.
• “Distributed Representations of Subgraphs” (DAC Ph.D. student Bijaya Adhikari; Yao Zhang; Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science and director of DAC; and B. Aditya Prakash). Adhikari presented this paper at a conference workshop and won a student travel award.
• “Learning to Fuse Music Genres with Generative Adversarial Dual Learning” (DAC Ph.D. student Zhiqian Chen and Chang-Tien Lu, associate professor of computer science and associate director of DAC, collaborating with the Georgia Tech Center for Music Technology). Chen presented this paper at the main conference.
• Two former DAC students, Feng Chen, currently assistant professor at the State University of New York at Albany, and Liang Zhao, currently assistant professor at George Mason University, presented the paper, “A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks.”  They worked on this research with the Georgia Tech Center for Music Technology. Chen presented this paper at the main conference.
• “Online and Distributed Robust Regressions under Adversarial Data Corruption” (Ph.D. student Xuchao Zhang; Liang Zhao; and Chang-Tien Lu, jointly with George Mason University and the U.S. Army Corps of Engineers). Zhang presented this paper at the main conference.

DAC faculty participation in the ICDM Conference included Chang-Tien Lu serving on the program committee and Naren Ramakrishnan serving as an area chair. Ramakrishnan also co-chaired a panel focusing on ethical and professional issues when dealing with social data with Tanushree (Tanu) Mitra, assistant professor of computer science, as one of the panelists. B. Aditya Prakash was invited to participate as a mentor in the ICDM Ph.D. Forum.

The ICDM has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications. ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state-of-the-art in data mining. Besides the technical program, the conference features workshops, tutorials, panels.