Department Announcements

If You Build It (with pizza) They Will Come

The Computer Club hosted a workshop for dual booting Unix and Windows on Saturday, September 5th. For full story visit link.

CEAS Newsletter

For the latest news at the College of Engineering and Applied Sciences, you can access the July issue of the CEAS Newsletter at: College of Engineering and Applied Sciences e-News.

Ajay Gupta Elected as Vice-Chair of IEEE Computer Society Technical Activities Committee

Dr. Ajay Gupta, a Professor of Computer Science at Western Michigan University, has been elected as the Vice-Chair of the prestigious IEEE Computer Society (IEEE-CS) Technical Activities Committee. Besides playing a key role in shaping technical activities of IEEE-CS, Dr. Gupta will be responsible for bringing together internationally renowned researchers at workshops, conferences, and other initiatives in order to foster innovation and collaboration for the benefit of computing technologies worldwide. IEEE, with over 400,000 members, is the world's largest professional association dedicated to advancing technological innovation. Dr. Gupta, a senior member of IEEE, is a world renowned specialist in parallel, distributed and high-performance computing and directs the Wireless Sensor Networks Laboratory of Western Michigan University. For the past four years, he has been Chair of IEEE-CS Technical Committee on Parallel Processing. In his work for the Committee, he has led initiatives in promoting parallel processing research and education to various constituents worldwide, including the development of computer science undergraduate curricula integrating parallel and high-performance computing topics in undergraduate courses. In the past Dr. Gupta has helped organize various ACM and IEEE conferences, including the International IEEE Conference on High Performance Computing for the past 20 years. He is also a member of Technical Meeting Request Committee at IEEE-CS and Member-At-Large of Technical and Conferences Activities Board (T&C) Executive Committee at IEEE-CS.

Learn more about the Computer Science Department at Western Michigan University and check out the relevant office of Undergraduate or Graduate Admissions to enroll.

NSF XSEDE Super-Computing Infrastructure Allocation

Congratulations to Prof. Fahad Saeed (CS/ECE) who has been allocated time (and space) on the prestigious NSF Extreme Science and Engineering Discovery Environment (XSEDE) super-computing infrastructure. The XSEDE is the most powerful and robust collection of integrated digital resources and supercomputing services in the world. Computing times on these machines are acquired via peer-review of the proposed projects and are highly competitive. Dr. Saeed and his PhD student Sandino Perez recently co-authored a paper "parallel algorithm for compression of next generation genome sequencing data" that was accepted in IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA-15), Finland. They will further their research by conducting scalability studies for petascale genomics data using XSEDE computing machines.

IEEE Elevation to Senior Member

Congratulations to Dr. Fahad Saeed for his elevation to Senior Member of the IEEE. Only 9% of IEEE members have achieved Senior Member level. The Senior Member level is the highest grade to which a member of the IEEE may apply.

Graduate Teaching Effectiveness Award

Congratulations to Jason Johnson, this year's recipient of the All-University Graduate Teaching Effectiveness Award with the Department of Computer Science.

Study Engineering in China Summer Program

A special China program, one credit with tuition fee waive, for two weeks in China, starts now. All expenses within China are covered by Sichuan University in China. The program fee is $400 only for visa, insurance, and registration fees and you earn 1 credit for free. If you are interested, contact Dr. Dewei Qi immediately. Seats are limited and allocated on a first come first served basis. More information can be found here.

Bachelor of Science in Data Science

The Departments of Statistics and Computer Science announce the creation of a B.S. degree in Data Science beginning Fall 2015. Data Science is a rapidly evolving discipline and sits at the intersection of Statistics and Computer Science. This evolution has been driven by the exponential increase in processing power available and the ever-increasing amount of data now collected, stored and available in every facet of business, science and government. There is an ever-increasing need for big data, and going forward it is likely that most jobs for statistics graduates will include a big data component. It is also clear that many computer science undergraduate graduate job opportunities will involve big data as well. This B.S degree prepares practitioners in data science. For more information regarding the requirements of the B.S. in Data Science, please see the listing on the Statistics Department site.

Center for High Performance Computing and Big Data

The Department of Computer Science at Western Michigan University is pleased to announce the formation of the Center for High Performance Computing and Big Data. The Center’s co-directors will be Drs. Elise DeDoncker, John Kapenga and Fahad Saeed. The Center will support Big Data science projects using high performance computing resources from the High Performance Computational Science (HPCS) Lab facilities. These facilities include a high performance computation cluster installed in 2012 with funding from a $289,574 National Science Foundation Major Research Instrumentation (MRI) grant to support interdisciplinary projects in computational science and engineering.

Research Awards

NSF Visualization and Analysis for C Code Security Grant

Dr. Steve Carr (WMU, PI), James Yang (WMU, co-PI), Jean Mayo (MTU, PI) and Ching-Kuang Shene (MTU, co-PI) have been awarded a $300,000 National Science Foundation grant ($169K WMU, $131K MTU) entitled “VACCS - Visualization and Analysis for C Code Security.” The grant will develop an educational system which will utilize static and dynamic program analysis to help detect potential security vulnerabilities and use visualization to help teach programmers about the potential errors in their code. The goal of this project is to help students learn by seeing what is wrong with programs rather than just having it explained in words.

National Science Foundation Cloud-Based Software Testing Grant

Dr. Zijiang Yang (PI) has been awarded a $65,559 National Science Foundation EAGER grant entitled “Systematic and Scalable Testing of Concurrent Software in the Cloud.” The objective of this research is to develop new algorithms and software tools to address the crucial problems of systematic and scalable testing of shared-memory concurrent software. The proposed methods, based on new symbolic execution algorithms and large-scale parallelization over clusters and the cloud, have the potential to achieve a super-linear speedup over the current state-of-the-art. If successful, this research will result in a new and practical software testing framework, which will be crucial in reducing the development cost for concurrent software, thereby leading to cheaper, more reliable, and more secure computer systems. NSF EAGER award supports exploratory work in its early stages on untested, but potentially transformative, research ideas or approaches. In addition, Dr. Yang has received a Google Computer Science Engagement Award, which gives him an unrestricted gift of $5,000 to support his teaching and research in Computer Science.

National Science Foundation High Performance Computing Big Data Grant

Dr. Fahad Saeed, assistant professor of computer science and electrical & computer engineering, was recently awarded a Research Initiation Initiative (CRII) research grant of US $171,341 from the National Science Foundation (NSF). The grant will support his research on high performance algorithms and architectures for Big Data. The research proposal entitled “HPC Solutions to Big NGS Data Compression” (Feb 2015 – Feb 2017) proposes to design and implement novel data-aware solutions for compression of large genomic data sets using high performance architectures and algorithms. Successful completion of this research will have significant impact on clinical as well as system biology labs and will move us one step closer to personal genomics era. This two-year pre-CAREER award was competitively awarded through NSF’s merit-review process and is supported by the NSF CCF Core program. Dr. Saeed is the sole PI on this grant.

Qatar Foundation Intelligent Transport Systems Grant

Drs. Ala Al-Fuqaha (WMU, PI), Elyes Ben Hamida (QMIC, Lead-PI) and Bharat Bhargava (Purdue University, PI) have been awarded a $900,000 Qatar Foundation grant to study intelligent transport systems (ITS). Through the use of wireless technologies, ITS systems will enable vehicles to autonomously communicate with other nearby vehicles or road infrastructures and thus, will have the potential to accelerate the deployment of a wide range of road safety and driver assistive applications. This innovative project aims at establishing a long term and multidisciplinary R&D efforts between Qatari and US research centers and universities, with the objective of designing, deploying and evaluating an Adaptive ITS Framework for the dynamic adaptation of the security and performance features based on changes in the ITS applications needs and context. The proposed framework and security models will be integrated in a standard compliant ITS platform, and a set of active road safety applications will be demonstrated in Doha city through small scale deployments.

National Science Foundation Adaptive Memory Resource Management Grant

Drs. Steve Carr (WMU, co-PI), Laura Brown (MTU, PI) and Zhenlin Wang (MTU, co-PI) have been awarded a $400,000 National Science Foundation grant entitled “Adaptive Memory Resource Management in a Data Center - A Transfer Learning Approach.” Cloud computing has become a dominant scalable computing platform for both online services and conventional data-intensive computing. By sharing computing resources among a large set of subscribers, a cloud computing data center (DC) provides a cost effective means to give users access to computational power and data storage that is not practical in an individual setting. To guarantee Quality of Service (QoS), a DC often has to over-commit its resources to meet the goal. This proposal focuses on the effective management of memory resources within a cloud computing DC using transfer learning.

National Science Foundation Cognitive Radio Grant

Drs. Ala Al-Fuqaha (WMU, co-PI), Bilal Khan (CUNY, PI) and Kirk Dombrowski (UNL, co-PI) have been awarded a $499,986 National Science Foundation grant entitled “Applying Behavioral-Ecological Network Models to Enhance Distributed Spectrum Access in Cognitive Radio.” In drawing the connection from the problem of resource-sharing in Cognitive Radio (CR), to models of solutions found within human/animal societies, this project evaluates the extent to which our models of patterns of co-use in biological systems can be profitably leveraged within the context of distributed uncoordinated CR societies to enable individuals and groups to maximize their utility. Of particular relevance to this endeavor is recent ethnographic research on foraging networks of indigenous peoples and human foragers, which has found social relations to be a critical context in which natural selection acts on resource use and co-use behaviors. These findings concerning human behavior lie at the forefront of anthropology, revealing the tensions between sharing networks and optimal strategies and altering our understanding of past human social evolution, and by extension, our vision of the future evolution of artificial CR societies.

National Science Foundation Genome Sequencing Grant

Prof. Fahad Saeed have been awarded $40,000 from the National Science Foundation (NSF) for developing high-performance solutions for Big genomic Data. This project deals with the design and development of high performance algorithms and implementations for aligning large number of genomes using innovative sampling and domain decomposition strategies. The proposed algorithms will be implemented on hybrid computing platforms consisting of multicore clusters, GPU's and FPGA’s.