“We are now just beginning to experience living super-interconnected lives,” said Butt. “Imagine five or 10 years from now when we will live in smart houses that use all kinds of sensors to monitor your safety, adjust the cooling or heating, and many other little devices and things that are only beginning to be used. These things require valuable computing abilities and information on the cloud to work properly and be useful.”
Butt, who also holds a courtesy appointment in electrical and computer engineering, is the principal investigator on the collaborative research project. He is partnering with Muhammad Shahzad, assistant professor of computer science from North Carolina State University, to design new techniques for massive data management and processing in the cloud, as well as study the actual nodes computers use to transfer information. The project is funded by the National Science Foundation.
Barbara Ryder, professor of computer science in the College of Engineering at Virginia Tech, has been conferred the title of professor emerita by the Virginia Tech Board of Visitors.
The emerita title may be conferred on retired professors, associate professors, and administrative officers who are specially recommended to the board by Virginia Tech President Tim Sands. Nominated individuals who are approved by the board receive an emeritus certificate from the university.
A member of the university community since 2008, Ryder served as head of the Department of Computer Science from 2008 until 2015. During that time, the number of undergraduate computer science degrees and majors doubled, and computer science research expenditures per tenure-track faculty member nearly tripled.
Ryder made significant contributions in teaching and research in her eight years at Virginia Tech. She had 23 research publications, including 12 in highly selective conferences and journals. She graduated one Ph.D. student, mentored three postdoctoral researchers and nine undergraduate researchers, and served on six additional Ph.D. dissertation committees.
She held the J. Byron Maupin Professorship of Engineering from 2008 until 2016, has been an Association for Computing Machinery Fellow since 1998, and is widely recognized internationally as a research expert on inter-procedural program analysis.
Jessica Zeitz Self had become accustomed to being in the minority. As she made her way through the doctoral program in the Department of Computer Science in the College of Engineering at Virginia Tech, Self, who earned her Ph.D. in 2016, was always mindful of the fact that she was one of only a handful of women. No wonder. Women who earned undergraduate degrees in computer science in 2015 were just 18 percent of the academic population, according to the National Science Foundation. When Self was hired as an assistant professor of computer science at the University of Mary Washington this year, she became part of a professional cadre of women that represents only 25 percent of the total STEM workforce in the industry.
Self’s collegiate experience at Virginia Tech allowed her to become a champion for diversity in her field, however. Being one of just three women out of a cohort of 40 in 2011, she made it a priority to weave diversity into her academic training. “One of the main issues with the gender gap in computer science is that girls simply aren’t exposed to what computer science is,” said Self.
Lenwood Heath gave the Clavius Distinguished Lecture in the Department of Computer and Information Science at Fordham University in New York City on Thursday, November 10. Dr. Heath is a professor in the Department of Computer Science at Virginia Tech.
MetaStorm is a joint research project with Liqing Zhang, associate professor in the Department of Computer Science at Virginia Tech, and Amy Pruden, professor in Civil & Environmental Engineering at Virginia Tech. Metagenomics is the capturing of microbial DNA sequence from environmental samples, where the environment might be soil, the ocean, or the human gut, for example. Especially important is that such samples contain multiple species of organisms, so the DNA sequence collected originates from a variety of unknown sources. Modern DNA sequencing results in a large number of short sequences, called reads, that are typically analyzed by using each read as a query to search a large database of known DNA or protein sequences. The accumulated results of such searches indicate what biological entities are present in the sample and what biological functions (proteins) are performed by organisms in the sample. Existing computational pipelines to perform these searches and subsequent analyses tend to be inflexible. We have developed a user-customizable analysis pipeline called MetaStorm that promises to support more targeted investigations of metagenomic data sets. MetaStorm provides the capability of assembling the reads into longer sequences, called contigs, that allow more precise identification of sequence matches. Also, MetaStorm allows the user to provide her own specialized sequence database to guide the search for particular classes of genes, for example, antibiotic resistance genes. MetaStorm is available as a free Web service where users upload their metagenomic data sets, select the desired analyses, and visualize the results in several novel ways.
Dr. Heath’s research interests include theoretical computer science, algorithms, graph theory, computational biology, and bioinformatics. Dr. Heath completed a Ph.D. in computer science at the University of North Carolina, Chapel Hill, an M.S. in mathematics at the University of Chicago, and a B.S. in mathematics at the University of North Carolina, Chapel Hill. Before joining the faculty at Virginia Tech in 1987, he was an instructor of applied mathematics and member of the Laboratory of Computer Science at MIT. He has supervised 11 computer science PhD students to completion and currently supervises 8 computer science graduate students. He has worked on a number of computational biology and bioinformatics projects funded by the National Science Foundation, including the current Beacon project, which captures, represents, infers, and simulates signal transduction pathways in plants. Other projects involve computational genomics, motif finding, and machine learning. Work in metagenomics is a natural fit to his interests in computational genomics.
Liang Zhao, computer science Ph.D. alumnus, has been named one of the Top 20 New Stars in Data Mining, provided by Microsoft searching. Microsoft searching mines the past 6 years of Knowledge Discovery and Data Mining (KDD) submissions and combines the big data from Microsoft to then achieve the ranking by an automatic algorithm.
Liang Zhao is an assistant professor in the Department of Information Sciences and Technology at the Volgenau School of Engineering. He is also affiliated with the Department of Computer Science. His research interests include data mining and machine learning, with particular emphasis on social media modeling, feature selection, and text mining. He has led the papers in prestigious conferences and journals including ACM SIGKDD, IEEE ICDM, SIAM Data Mining, PLoS One, and IEEE BigData, and served as the reviewer for leading conferences and journals such as ACM SIGKDD, ACM TKDD, IEEE ICDM, SIAM Data Mining, ACM TIST, ACM SIGSPATIAL, and Geoinformatica. He also owns two US IP discloses on social media mining.