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Stacey Clifton (left), Michelle Dowling (center), and Moeti Masiane (right)

Three funded UrbComp fellows, Stacey Clifton, Michelle Dowling, and Moeti Masiane, earned the graduate certificate in urban computing this spring. The certificate is offered through the National Science Foundation-sponsored multidisciplinary UrbComp Program administered by the Discovery Analytics Center.

Clifton, advised by James Hawdon and B. Aditya Prakash, graduated with a Ph.D. in sociology and Dowling, advised by Chris North and Mike Horning, with a Ph.D. in computer science.

Masiane, advised by Chris North and Eric Jacques, will complete his Ph.D. in computer science during the summer semester.

Dowling and Masiane were also students at the Discovery Analytics Center.

Clifton was drawn to the program both for its multidisciplinary approach and as a way to advance her quantitative skillset.

“I wanted to challenge myself to do something out of the norm and UrbComp provided me with the quantitative skills to be the first in my department to complete a comprehensive examination in advanced quantitative methods,” she said.

“I was able to further apply this skillset to my dissertation research to add a novel component to the study of policing research,” said Clifton. Her dissertation is titled “Coping isn’t for the Faint of Heart: An Investigation into the Development of Coping Strategies for Incoming Police Recruits.”

Clifton, who is joining Radford University as an assistant professor in the Department of Criminal Justice, said she would “100 percent recommend this program as a vital component to graduate studies.”

For Dowling, the program “helped hone the audience for my research to those performing truthfulness determinations based on a given claim,” she said. “This allowed me to focus on how I described my research, making it easier for others to understand its impacts.”

Dowling’s dissertation is titled “Semantic Interaction for Symmetrical Analysis and Automated Foraging of Documents and Terms.”

She said that her first-hand experience of collaborating with others outside her field of study has shown her how beneficial wide collaboration can be.

“I fully intend to continue seeking such collaboration opportunities,” said Dowling, “and I hope to make connections with professors in different departments as I establish myself as an assistant professor at Grand Valley State University.

For Moeti, whose dissertation is on “Insight Driven Sampling for Interactive Data Intensive Computing,” the program expanded his interest in analyzing large data sets and telling stories about such data to include analyzing large data sets related to urban cities.

“UrbComp class projects allowed me to acquire practical experience with data analysis and machine learning and the data modeling skills I have acquired will surely help me in future data analysis work,” said Moeti. “But I think the most important thing I learned in the program was the ethical aspect of data analytics.”

The UrbComp program is open to Virginia Tech master’s and Ph.D. students in any discipline located in Blacksburg or the greater Washington D.C. campus.

For more information contact program coordinator Wanawsha Shalaby.

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.

Moeti Masiane, DAC Ph.D. student in computer science

Moeti Masiane’s initial interest in analyzing data grew even stronger when earning a bachelor’s degree in computer science from the University of the District of Columbia and then a master’s degree from Norfolk State University.

As he began to consider going on to a Ph.D. program in the same field, he was drawn to Virginia Tech and the Discovery Analytics Center. “The expert DAC faculty really made me want to be part of the team,” said Masiane, who is advised by Chris North.

He has been at DAC since 2016, where, he said, “I  am surrounded by talented faculty and students who are always willing to suggest new ways of solving data analysis-related challenges.”

Masiane has focused his Ph.D. research on data visualization. “In the process of trying to analyze large datasets, I realized that there is a research opportunity in trying to solve the big data visualization latency challenge,” he said.

Masiane is also a research trainee in the National Science Foundation-sponsored Urban Computing certificate program, an interdisciplinary program administered through DAC.

On March 28, he will present “Towards Insight Driven Sampling in Big Data Descriptive Analytics” at the UrbComp Seminar Series to discuss his work.

“Sampling is often used by authors of big data visualization systems to reduce big data into small data in order to make the visualization faster and the data compatible with traditional visualization techniques. The impacts of such sampling is known in statistical terms, but unknown in a visualization context,” he said.

His research uses a descriptive data analysis task performed by a class of more than 200 students to investigate and model the impact of sampling on insight, perception, visualization, and sampling errors.

“The ultimate goal is to increase the speed of big data visualization while helping system users make informed decisions on how to achieve this speedup,” Masiane said.

Two papers with his advisor and other collaborators were published in Informatics Journal in 2016: “Interactive Graph Layout of a Million Nodes” and “AVIST: A GPU-Centric Design for Visual Exploration of Large Multidimensional Datasets.”

Masiane, who is on schedule to graduate in May 2020, spent last summer working on his research and plans to do the same this year. His past experience includes working for Google and internships with Adobe and the Army Research Lab.