Mohammed Seyam, computer science graduate student, was one of four students among the latest group of Virginia Tech Global Perspectives Program scholars who visited and studied programs at universities in Switzerland, Italy, and France for 13 days earlier this summer. They and their fellow scholars researched trends and issues in higher education, teaming up with peers at the universities of Basel and Zurich in Switzerland. After returning to the United States, the Global Perspective scholars presented their findings at the Swiss Embassy in Washington, D.C., continuing a tradition established in 2010. Noha ElSherbiny, computer science graduate student, also participated in the program last year.
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.
The energy of a new academic year is always welcome. In addition to greeting new students, we often have the privilege of bringing new faculty members in to the department. This year we are very glad to welcome Associate Professor Chandan Reddy and Assistant Professor Gang Wang, each of whom brings critically needed teaching and research expertise in important growing areas. Dr. Reddy earned his PhD at Cornell University. He joins us after serving on the faculty at Wayne State University for several years. Chandan is an expert in data mining and machine learning, with applications to healthcare analytics, bioinformatics and social network analysis. He is part of our department’s presence in the National Capital Region (NCR), where he will also join the Discovery Analytics Center. Dr. Wang received his PhD from the University of California, Santa Barbara. His research and teaching interests are in security, with a particular focus on Internet measurement, mobile networks, and the interplay between human-computer interaction (HCI) and security. Stay tuned for more hiring news in the year ahead—everywhere we look we see growth and opportunities for computer science, so we look forward to recruiting more excellent faculty, staff, and students to join our team!
DAC is excited to be part of Virginia Tech’s venture to distinguish its research and education in the field of data and decision sciences through this new initiative. Naren Ramakrishnan, DAC Director, said, “Our data analytics and decision sciences planning group draws members from engineering, sciences, business, liberal arts, humanities, and the natural resources, and our goal is to make this complex be an asset for the entire university.”
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.
From September 14th -17th, 9 CS students and 2 CS faculty (Cal Ribbens, Barbara Ryder) journeyed to Austin, Texas to participate in the 2016 ACM Richard Tapia Celebration of Diversity in Computing. Of the approximately 1000 attendees, 536 were students, 135 were faculty and 260 were representatives from industry/government. This was the 10th Tapia Conference whose theme, Diversity Matters, was reflected in keynote speeches, professional development programs, a student research poster session, a career fair, and “birds-of-a-feather” meetings on practical approaches to supporting diversity and inclusion.
Our two goals in attending Tapia were to: (i) expose CS@VT African-American and Latino/a graduate and undergraduate students to a professional computing conference in which they would be in the majority, and (ii) actively recruit minority graduate students for our MS/Ph.D. programs and for possible future faculty positions.
Dr. Ryder reported, “It was a thrill to personally meet and talk to so many African-American and Latino/a colleagues in computing, including several of our CS@VT alumni – Dr. Cheryl Seals (Auburn), Dr. Jeremy Barksdale (Microsoft), Dr. Kevin Buffardi (Cal State, Chico) and CS@VT Distinguished Alumna Dr. Jamika Burge.” Dr. Ribbens stated: “The Tapia conference is a great opportunity for our students to meet peers and hear from incredible role models, and for faculty to share ideas and enthusiasm with other schools who are also committed to improving diversity in CS.” The excitement of our student participants is expressed in their comments:
Sean Crenshaw: “Tapia gave me the opportunity to network with the best in the tech industry who are transforming current standards so that we, the next generation of minorities, can follow in their footsteps.”
Jazmine Zurita: “The conference was the perfect way to network with recruiters, more so than we can in standard career fairs.”
Gustavo Arango Argoty: “The most interesting aspect of the conference was to see how big companies develop computing applications to understand society and hence its diversity.”
Vanessa Cedeno: “Being able to meet other people with the passion of promoting and including diversity in Computer Science was exciting and inspiring.”
Souleymane Dia: “It’s been one of the best opportunity for me to directly interact with industry leaders and connect with them for future opportunities.”
Moeti Masiane : “The conference was a wonderful venue for networking, placing players from academia and industry in a fun and open environment.”
CS students Moeti Masiane, Tianna Woodson, Kelvin Aviles, and Teresa Lin also attended. This was a great experience. It continues a strong tradition of CS@VT participation in the Tapia conferences (we have been Gold Supporters of Tapia for many years). We hope to offer the opportunity to attend to more of our students and faculty in future years. To that end, alumni and friends of CS@VT can donate to the department’s Barbara Ryder Diversity in Computing Fund by sending a check to the VT Foundation account #861127.
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.