Engineering Departments

Computer Science


From left, Ali Butt and Chao Wang
Blacksburg, VA , October 20, 2014
Virginia Tech College of Engineering

Massive amounts of data, collected daily, range from traditional consumers using cell phone technology to big corporations storing the buying patterns of thousands of individuals. According to one recent study reported in Computerworld, the amount of event data generated in the U.S. alone is estimated to be 7 million pieces per second and climbing.

Managing the massive or, as they are now commonly labeled, “big data” processing systems is a huge undertaking.

“There is currently a disconnect between programmers who develop the big data applications and system engineers who oversee large data centers that support these applications. It leads to reduced performance and missed optimization opportunities,” said Ali R. Butt, associate professor of computer science at Virginia Tech.

Butt and his colleague, Chao Wang, assistant professor of electrical and computer engineering, also of Virginia Tech, are now in the process of trying to develop innovative resource management tools for these big data processing systems. They are using a $750,000 grant from the National Science Foundation (NSF) to improve the technology.

Big data processing systems provide the computing substrate for a wide range of applications in such fields as high-speed physics, economics, genomics, astronomy, and meteorology.

“It is therefore crucial, for computing–based scientific discovery, to sustain these data-driven systems at scale in the presence of emerging technologies such as specialized microprocessors, GPUs, and hybrid storage systems,” Butt said.

Butt is a past recipient of an NSF CAREER Award on computing performance. This earlier award, valued at $400,000 allowed him to focus on a better understanding of the increasing performance gap between computing power and storage technology, especially for high performance computing (HPC) environments, for some five years prior to receiving this new NSF honor.

Having a better understanding of the application behavior and its interactions with the mixed/hybrid infrastructure “play a central role in creating highly efficient systems for current and future generations of big data applications,” Wang said.

The Virginia Tech team plans to address the disconnect between programmers and system engineers by leveraging their expertise in both distributed computing and software engineering.

Wang joined Virginia Tech in 2011 after spending seven years at the NEC Laboratories in Princeton, N.J. He had worked on complex computer systems, including hardware, software, and embedded systems.

“Current systems treat the user-provided software codes as a black box, which makes it very difficult to fine-tune the system for running these codes,” Wang said. So, Wang and Butt hope to employ static/dynamic program analysis techniques to build informative application models. These models will then be used to help predict application behavior and for managing the computing resources.

The overall goal is to develop what the two researchers are calling Pythia, an online application-aware oracle framework for fine-tuning big data systems on emerging heterogeneous resources. In Greek literature, Pythia was the name of any priestess, throughout the history of the Temple of Apollo, credited for her prophecies.

“Imagine if you can see into the future and know how an application would behave, you can have a strategy for scheduling resources to maximize the system performance -- this is the vision behind Pythia,” Butt said.

Butt leads the Distributed Systems and Storage Laboratory at Virginia Tech, which focuses on innovations in computer systems ranging from cloud computing to specialized operating-system-level optimizations for emerging hardware technologies. Before joining the faculty of Virginia Tech in 2006, he completed his doctorate in electrical and computer engineering at Purdue University. He received his bachelor’s degree in electrical engineering from the University of Engineering and Technology in Lahore, Pakistan.

Wang is also a recipient of the NSF CAREER award, the Office of Naval Research Young Investigator award, Virginia Tech College of Engineering Outstanding New Assistant Professor Award, and many best paper awards. He leads the Reliable and Secure Software Laboratory at Virginia Tech, which focuses on innovations in software engineering, formal methods, parallel programming. He received a Technology Commercialization Award in 2006. Wang completed his doctorate at the University of Colorado at Boulder in 2004, and won the 2003-2004 ACM Outstanding Ph.D. Dissertation Award in Electronic Design Automation. He received his bachelor’s and master’s degrees from Peking University, China.



Daphne Yao
Blacksburg, VA , September 24, 2014
Virginia Tech College of Engineering

In cybersecurity, “the detection of insider attacks is a problem that we have known for a long time to be notorious to solve,” said Daphne Yao, the newly appointed L-3 Fellow and associate professor of computer science at Virginia Tech.

The U.S. Army agrees with her. It just awarded Yao an Army Research Office Young Investigator Award “to detect anomalies that are caused by system compromises and malicious insiders. “

The $150,000 award will allow her to design big data algorithms that will focus on discovering logical relations among human activities. This research ranges from the analysis of low-level machine events to the reasoning about the legitimacy of human activities with respect to organizational security goals. She will look for abnormal action sequences and workflows.

Recording this type of data “can be useful for detecting insider attacks,” said Yao who previously won a National Science Foundation CAREER award to develop software that differentiated human-user computer interaction from that of malware, commonly known as malicious software.

Today’s military operations must have trustworthy networked systems in both the cyberspace and the physical world, and the importance of real-time surveillance is critical. 

“If we are successful, our proposed solutions will provide a leap forward to stronger Army command and control of cyberspace capabilities on the battlefield as well as in day-to-day operations,” Yao said. Preliminary studies prior to the awarding of the young investigator award have shown promising results.

Yao seeks to provide trustworthy data and an infrastructure that will support a variety of military needs. They include a soldier’s mobile computing device, people inside an armored fighting vehicle with a network embedded system, and operators using satellite links to connect a command station with those in the field.

“One key insight that inspires our approach of triggering a discovery is that human security experts tend to analyze the underlying relations of event occurrences as opposed to treating them independently,” Yao explained. “Triggering relations among cyberspace events at all levels can provide powerful evidence for system and network assurance status.”

Otherwise, Yao believes, events that happen in the cyberspace network are not placed in context.

The type of system assurance Yao envisions is a guarantee that when a user enters a password, the computer is free of spyware key-loggers and/or that the organizational network is free of compromised computers that may be controlled by malicious outsiders.

The host of the operating system and software could include: a workstation, a laptop, a server, an embedded system, or a mobile smart phone. The network assurance would be between these multiple hosts.

“Because almost all modern computing devices are connected to networks, system assurance and network assurance need to be addressed together,” Yao said.

Yao’s 2010 NSF CAREER Award allowed her to effectively isolate infected computer hosts and detected in advance stealthy malware. Her work was highlighted at the 2014 ACM Symposium on Information, Computer, and Communications Security in Kyoto, Japan.

When she announced her findings in Japan, she said at that time that, “This type of semantic reasoning is new and very powerful. The true significance of this security approach is its potential proactive defense capability. Conventional security systems scan for known attack patterns, which is reactive. Our anomaly detection based on enforcing benign properties in network traffic is a clear departure from that.”



From left: Bert Huang, Kurt Luther, and Sharath Raghvendra
Blacksburg, VA , September 02, 2014
Virginia Tech College of Engineering

Bert Huang

Research Interests:

His name is on six patents, ranging from machine learning for power grids to ways to analyze spatiotemporally ambiguous events to combinatorial optimization methods and systems. Since fall of 2011, Huang has worked as a postdoctoral research associate at the University of Maryland’s Department of Computer Science. He conducts collaborative research on machine learning in network and relational domains, focusing on topics including large-scale probabilistic methods and computational learning theory for structured models.

Education:

Master's Degree: Philosophy in Computer Science, Columbia University

Master's Degree: Computer Science, Columbia University

Doctoral Degree: Computer Science, Columbia University
 

Kurt Luther

Research Interests:

Luther’s main research interests include human–computer interaction (HCI), social computing and crowdsourcing, and creativity support tools. Specifically, building and studying social computing systems to enhance human creativity and problem solving abilities, in domains such as computer animation, visual design, knowledge discovery, and citizen science. Also interested in connections to the digital humanities, especially history.

Education:

Bachelor's Degree: Computer Graphics Technology, Minor in Art and Design, Purdue University

Doctoral Degree: Human-Centered Computing, Georgia Tech
 

Sharath Raghvendra

Research Interests:

Raghvendra focuses on the design of algorithms for geo-metric problems. He is particularly interested in the creation of algorithmic tools and methodologies which are applicable to large-scale, unstructured, and potentially very high dimensional geometric data.

Education:

Bachelor's Degree: Computer Science and Engineering, Indian Institute of Information Technology (IIIT), Hyderabad, India

Doctoral Degree: Computer Science, Duke University



Allison Tegge
Blacksburg, VA , August 27, 2014
Virginia Tech College of Engineering

Allison Tegge, a post-doctoral associate researcher with Virginia Tech’s Department of Computer Science, has been awarded a three-year National Institutes of Health fellowship worth $150,000.

Tegge was awarded the Individual Postdoctoral Fellowship, also known as an F32, by the National Institute of Environmental Health Sciences through the Ruth L. Kirschstein National Research Service Awards program. The fellowships provide up to three years of support for promising postdoctoral researchers who have the potential to become productive, independent investigators within the broad scope of biomedical, behavioral, or clinical research, according to the agency’s website.

The fellowship is tied to Tegge’s work on researching how liver cells signal one another. The process is not yet understood and is a focal point of research by Virginia Tech College of Engineering faculty Padma Rajagopalan, associate professor of chemical engineering, and T. M. Murali, associate professor of computer science. Murali and Rajagopalan will co-mentor Tegge on her research.

Rajagopalan has developed an in vitro 3-D bioengineered liver tissue that contains three major cell types. In humans, the liver is primarily responsible for metabolizing foreign compounds such as alcohol, cigarette smoke, and drugs. Rajagopalan and Murali are collaborating on discovering how these cell types may be communicating with each other in order to maintain cellular function.

Their combined team is working on the effort as part of the Virginia Tech Institute for Critical Technology and Applied SciencesCenter for Systems Biology of Engineered Tissues, with funding from the National Science Foundation and the Environmental Protection Agency. Tegge’s work focuses on the computational aspects of the research. She is developing computer algorithms that in essence will discover the code for inter-cellular signaling within the liver, which, in turn, could lead to a similar understanding of other body organs.

“Allison’s research is at the interface of computer science and tissue engineering, and it will map how protein pathways that mediate inter-cellular signaling may be perturbed by exposure to environmental chemicals,” said Murali. “She will develop cutting-edge graph-theoretic algorithms to discover these patterns.”

Part of the in-lab research by Rajagopalan involves exposing the liver tissue models to various toxic environmental chemicals. Researchers then watch and test how the cells within the sample react to the administration, including activation of protein signaling pathways. Tegge’s algorithms will help “discover” which protein pathways create a signal that can cause observed changes in gene expression, added Murali.

“This award from the National Institutes of Health is a testament to the promise of her research,” said Murali. Tegge has been working on the research for nearly two years, and wants to use the fellowship to move into an academic research track, becoming an independent researcher.

Tegge obtained her bachelor’s and master’s degrees from the University of Illinois in 2006 and 2008, respectively, and her doctoral degree in informatics from University of Missouri, Columbia, in 2012.


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