“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.
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.
A Virginia Tech project created to educate and inspire computational thinking was named one of the top projects by the readers of The MagPi, a magazine dedicated to work using Raspberry Pis, affordable and accessible mini-computers originally designed to teach computer programming to people of all ages.
Wu Feng, Elizabeth and James E. Turner Jr. Faculty Fellow, and colleagues Adrian Sandu (CS), Eric DeSturler (Math), Chris Roy (AOE), and Danesh Tafti (ME) received funding from AFOSR for a project entitled “A Deep-Learning Approach towards Auto-Tuning CFD Codes”.
Francisco Servant’s paper was accepted in the International Conference of Software Engineering 2017: Francisco Servant, James A. Jones, “Fuzzy Fine-grained Code-history Analysis”. Proceedings of the 39th International Conference on Software Engineering (ICSE 2017), Buenos Aires, Argentina, May 2017. Dr. Servant also gave a talk about his research at Virginia Commonwealth University.
Chris North, professor and associate director of the Discovery Analytics Center, along with colleagues Naren Ramakrishnan and Nicholas Polys received new funding from General Dynamics for a project entitled “CHITA: Computer Human Interactive Text Analytics”.
Ing-Ray Chen, along with his U.S. Army Research Laboratory (ARL) collaborators Dr. Jin-Hee Cho and Dr. Ananthram Swami, won the 2016 ARL Publication Award. The award ceremony was held on 11/8/2016 at the U.S. Army Research Laboratory in Adelphi, MD. This award goes to Dr. Chen for his outstanding contributions toward a group effort on the publication “A Survey of Trust Management for Mobile Ad Hoc Networks”. This publication provides a survey of trust management schemes developed for Mobile Ad Hoc Networks (MANETs) and discusses generally accepted classifications, potential metrics, and trust metrics in MANETs. Future research areas on trust management in MANETs based on the concept of social and cognitive networks are also discussed in this publication. The team’s outstanding contributions reflect great credit upon them, the U.S. Army Research Laboratory, the U.S. Army Research, Development and Engineering Command, and the Department of the Army.
The goal of the program is to introduce undergraduates, with interests and background in both computing and music, in multidisciplinary research that creates computational and artistic approaches for exploring musical scores, with possible applications for automated performance guidance and advanced musical analysis.
Ed Fox took part in the Coordinated, Behaviorally-Aware Recovery for Transportation & Power Disruptions project. Read More
Daphne Yao and Xiaokui Shu from IBM Research gave a 1.5-hour-long tutorial at the 23rd ACM Computer and Communications Security (CCS) Conference at the Hofburg Palace in Vienna, Austria on October 25th. The tutorial is on program anomaly detection techniques, specifically how to use data analytic and program analysis methods to accurately predict anomalous behaviors of complex software and protect critical systems against zero-day exploits. ACM CCS is a top computer security conference with record breaking 1,000+ attendees this year. The Yao group is one of the leading research groups on systematizing and democratizing data-driven security techniques for programs. Xiaokui is a former PhD student of Dr. Yao, who graduated in the spring of 2016.
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. Read More
Kirk Cameron (PI) and co-PIs Ali Butt, Yili Hong, Layne Watson, Danfeng Yao, and Godmar Back received funding for a significant new project entitled, “VarSys: Managing variability in high-performance computing systems.” This high-profile award will allow the PIs and their students to pursue important research in systems, and add to the visibility of stack@cs and the CS department. Read More
Daphne Yao and her collaborator at Texas A&M Chemical Engineering Department, Victor Ugaz, are excited to start their new inter-disciplinary NSF EAGER project on anonymous crowdsensing for citizen science, specifically for early epidemic detection. Daphne’s group is working on designing novel and scalable cryptographic signature schemes to support anonymous-yet-accountable sensing. If successful, this anonymous sensing framework together with the miniature smartphone-powered bacteria-testing PCR devices being invented in Victor’s lab will allow volunteers to contribute to national or global epidemic monitoring anywhere and anytime, without any privacy concerns. The NSF’s EAGER program is specifically designed for this type of new and high-risk high-reward research.
Daphne is an associate professor of computer science, Turner Fellow, and L-3 Fellow at Virginia Tech. Professor Ugaz is the holder of the Charles D. Holland ’53 Professorship and Thaman Professorship at Texas A&M University.
Eli Tilevich received funding from NSF for his project entitled, “Addressing Resource Scarcity via Distributed Mobile Services.”
Steve Edwards’s newly funded NSF project, “Promoting a Growth Mindset Using Automated Feedback” is a collaboration with Dr. Manuel Perez at the University of North Carolina at Charlotte and with Berea College.
Yang Cao’s newly funded NSF project, “Identifying and modeling the advantages of regulating protein abundance in Caulobacter crescentus” is a collaboration with John Tyson (VT Biological Sciences) and Kathleen Ryan (UC Berkeley).
Ed Fox (PI) and Andrea Kavanaugh received funding from NSF for a new project entitled, “Global Event and Trend Archive Research (GETAR).”
Chandan Reddy’s newly funded NSF project is entitled, “An Integrated Predictive Modeling Framework for Crowdfunding Environments.”
T.M. Murali and Kurt Luther received NIH funding for their collaborative project “Using Crowdsourced Design to Visualize Effects of Environmental Chemicals on Signaling Networks”.
Adrian Sandu received NSF funding for his proposal “Multirate Multimethod Time Integration Algorithms for Multiscale Multiphysics Problems”.
C.T. Lu received support from Northrop Grumman for “Cyber and Advanced Data Analytics and Processing.”
Wu Feng and PhD student Vignesh Adhinarayanan received the Best Paper Award at the IEEE International Symposium on Workload Characterization.
Computer Science Department faculty and students presented six research papers and one tutorial at the 22nd ACM Conference on Knowledge Discovery and Data Mining (KDD 2016), held in August in San Francisco. KDD is the premier annual international conference on knowledge discovery and data mining. Virginia Tech was among the top-10 represented university and industry groups at KDD. In addition the most viewed video and the second most downloaded papers at KDD were written by Virginia Tech CS PhD students and faculty.
One of my research topics that I’m most passionate about is on developing machine learning algorithms that detect cyberbullying in social media. Cyberbullying is a serious public health threat that is detrimentally shaping the online experience. And while Internet technology is rapidly amplifying our ability to communicate, it’s important to develop complementary technology to help mitigate the harm of such detrimental communication.
Computer programs that detect online harassment could allow automatic interventions, e.g., providing advice to those involved, but we don’t yet have machine learning algorithms that can handle the scale, the structure, and the rapidly changing nature of cyberbullying. Standard approaches for classification are hindered by the cost of labeling bullying examples and the need for social context to differentiate bullying from other less harmful behavior.
My group is developing machine learning algorithms that use weak supervision, where the input to the algorithm isn’t whether each interaction is bullying, but general indicators of bullying, such as offensive language. The algorithms try to extrapolate from that using social media data, considering who’s sending and receiving messages with the provided indicators, and the overall structure of the relationships in the data. The algorithms do collective, data-driven discovery of who is bullying, who’s being bullied, and what additional vocabulary is indicative of bullying.
Denis Gracanin, an associate professor in the College of Engineering’s Department of Computer Science, along with Joseph Wheeler, professor of architecture in the College of Architecture and Urban Studies and co-director of the Center for Design Research, and Clive Vorster, a visiting instructor in the School of Architecture + Design, have worked the past three years with students from architecture, industrial design, interior design, and computer science to envision how people will interact with their homes in the near future.
Clifford A. Shaffer, professor of computer science in the College of Engineering at Virginia Tech, has been awarded the W.S. “Pete” White Chair for Innovation in Engineering Education by the Virginia Tech Board of Visitors. The W.S. “Pete” White Chair for Innovation in Engineering Education was established by American Electric Power to honor Pete White, a 1948 graduate of Virginia Tech, and to encourage new interest in the teaching of engineering and improve the learning process. Recipients hold the chair for a period of two years.
Kurt Luther’s research partnership is revealing the differences in the latitude and attitude of Americans during the Civil War era one historical document at a time and it’s inviting “citizen historians” to transcribe, tag, and discuss primary sources. It may also open up discussions into issues of race, citizenship, and identity.