Gratz receives Association of Former Students Distinguished Achievement Award in Teaching

Dr. Paul V. Gratz, associate professor in the Department of Electrical and Computer Engineering at Texas A&M University, was awarded the 2016 Association of Former Students (AFS) Distinguished Achievement Award in Teaching — College Level. He is one of four faculty members in the college of engineering selected to receive the award.

Since 1982, the AFS teaching award has been presented to faculty members who are renowned for their expertise and exemplary dedication to the education of their students.

Dr. Miroslav Begovic, electrical and computer engineering department head, said Gratz deserves the award because he has been an early adopter of blended learning within the department and college, having restructured ECEN 350 as a blended learning class.

The restructured class features live, recorded lectures published online and online quizzes replacing traditional homework, among other enhancements. Those efforts have yielded two benefits — a two to three week increase in material covered during a semester as well as improvements in student retention from a traditionally high drop-rate class.

Gratz has also been a leader in the department’s efforts to develop a distance learning masters program. His ECEN 676 class during spring 2016 served as the pilot class for the distance learning masters program. Based on his experiences he is developing a set of distance learning training sessions for faculty.

Gratz is a member of the computer engineering and systems group. He received his Ph.D. in electrical and computer engineering from the University of Texas at Austin in 2008. His research interests include energy-efficiency, reliability and performance in processor microarchitectures, memory systems and on-chip interconnection networks.

He has received a Teaching Excellence Award from The Texas A&M University System and a Best Paper Award from the ASPLOS’09 conference.

The AFS teaching award will be formally presented to all recipients in spring 2017 at the annual college awards banquet.

Computer Engineering and Systems Group’s Faculty and Staff Award winners recognized

M. Katherine Banks, vice chancellor and dean of engineering and director of the Texas A&M Engineering Experiment Station (TEES), recognized two Faculty and Staff Award winners in the Computer Engineering and Systems Group during the 2016 Faculty and Staff Awards banquet.

Banks presented Carolyn Warzon with a Staff Excellence Award and Alex Sprintson with the William O. & Montine P. Head Memorial Research Fund Award for Contributions.

Sprintson, who joined the department in 2006, received his B.Sc. degree (summa cum laude), M.Sc. and Ph.D. degrees in electrical engineering from the Technion – Israel Institute of Technology in Haifa, Israel, in 1995, 2001 and 2003, respectively. From 2003 to 2005 he was a postdoctoral research fellow at the California Institute of Technology. His honors include the Prof. Andrew Viterbi post-doctoral fellowship, the Wolf Award for his Ph.D. studies, the Miriam and Aaron Gutwirth Fellowship for Special Excellence in Graduate Studies and numerous academic awards of excellence.

Sprintson’s research interests are in the broad area of communication networks with a focus on algorithmic and Information-theoretic aspects of networking, network coding and its applications in communication networks, and Quality of Service (QoS) routing.

Warzon, administrative coordinator for the Computer Engineering and Systems Group, joined the department in 1996. Warzon has been in the college of engineering since 1985. Other honors she has received include the 2005 Presidents Meritorious Service Award, the Dean’s Staff Achievement Award from the college of engineering, and the department’s Outstanding Staff Award.

Researchers in electrical and computer engineering receive award for brain-inspired computing

Two graduate students and their adviser in the Department of Electrical and Computer Engineering at Texas A&M University received the Honorary Mention Best Paper Award from the 2016 IEEE International Symposium on Circuits and Systems (ISCAS).

Qian Wang, Youjie Li and their thesis adviser, Dr. Peng Li, received the award for their paper titled, “Liquid state machine based pattern recognition on FPGA with firing-activity dependent power gating and approximate computing,” at ISCAS, which was held in Montreal, Canada. This award was conferred by the Neural Systems and Applications Technical Committee of IEEE Circuits and Systems (CAS) Society.

For a very long time, the human brain has been a great inspiration for building efficient intelligent systems. Nevertheless, mimicking the information processing capabilities of the brain in VLSI-based computing systems is a completely nontrivial task and entails the development of efficient processor architectures and hardware-friendly learning mechanisms. The researchers’ paper demonstrates how the liquid state machine (LSM), a biologically plausible recurrent spiking neural network model, can be used to enable brain-inspired neural processors. An LSM processor architecture with integrated on-chip learning capability has been demonstrated on the reconfigurable FPGA platform for pattern and speech recognition applications. This work also investigates novel firing activity-based low power and approximate computing techniques to boost system energy efficiency.

Wang and Li are part of Dr. Li’s research group, and have recently passed their Ph.D. and M.S. thesis defenses, respectively. Dr. Li is a professor in the department, a faculty member of the Texas A&M Institute for Neuroscience and Texas A&M Health Science Center, and an IEEE Fellow. In addition to this award, Dr. Li has received five other best paper awards from premier IEEE/ACM conferences.

ISCAS is the world’s premier networking forum of leading researchers in the highly active fields of theory, design and implementation of circuits and systems.

Duffield appointed Fellow of the IET

Dr. Nick Duffield, professor in the Department of Electrical and Computer Engineering at Texas A&M University, professor by courtesy in the Department of Computer Science and Engineering, and Director of the Texas A&M Engineering Big Data Initiative was appointed Fellow of the Institution of Engineering and Technology (IET).

The IET, which is based in the United Kingdom, is one of the world’s largest engineering institutions with more than 167,000 members in 127 countries. It is also the most multidisciplinary – to reflect the increasingly diverse nature of engineering in the 21st century.

IET Fellowship is awarded to individuals who have sustained high levels of achievement, for example through leadership, influence, senior responsibility, innovation and professional service, at the forefront of engineering, technology or cognate disciplines for a period of five years or more.

“I am honored to be recognized as a Fellow by the IET. I intend use my relations with the IET Fellow community to help build international connections in my research fields of communications networking and data science”.

Duffield received his bachelor’s degree in natural sciences in 1982 and a master’s in 1983 from the University of Cambridge, UK. He received his Ph.D. in mathematical physics from the University of London, U.K., in 1987. His research focuses on data and network science, particularly applications of probability, statistics, algorithms and machine learning to the acquisition, management and analysis of large datasets in communications networks and beyond.

Before joining the department, Duffield worked at AT&T Labs-Research, Florham Park, New Jersey, where he held the position of distinguished member of technical staff and was an AT&T Fellow. He previously held post-doctoral and faculty positions in Dublin, Ireland and Heidelberg, Germany.

Duffield, the author of numerous papers and holder of many patents, is co-inventor of the smart sampling technologies that lie at the heart of AT&T’s scalable Traffic Analysis Service. He is specialty editor-in-chief of journal Frontiers in ICT and he was charter chair of the IETF working group on packet sampling. Duffield is an IEEE Fellow and serves on the Board of Directors of ACM SIGMETRICS. He is an associate member of the Oxford-Man Institute of Quantitative Finance.

The goal of IET is working to engineer a better world by inspiring, informing and influencing our members, engineers and technicians, and all those who are touched by, or touch, the work of engineers.

Second Big Data workshop fosters connections across disciplines at Texas A&M University

The second annual Big Data workshop was held recently at Texas A&M University to foster connections across disciplines that intersect this area and help people to continue to identify opportunities for collaboration. The workshop was comprised of 27 short talks from speakers from across the university, organized in thematic sessions with time for discussion. The sessions encompassed Big Data in Sensing and Social Applications; Environment, Resources and Power; Materials; Cybersecurity; and Bioinformatics, Medicine & Health Sciences. Participants also discussed broader issues for big data research in the university, including infrastructure support, computational resources and availability of data for collaboration. There were over 90 registered attendees.

Many researchers across Texas A&M have current or emerging research interests in big data methods, systems or applications, and there are currently opportunities at the federal level for major funding of cross-disciplinary projects in data science.

Building on the first workshop held last year, Dr. Nick Duffield, professor in the Department of Electrical and Computer Engineering and director of the Texas A&M Engineering Big Data Initiative, and Dr. Dilma Da Silva, head of the Department of Computer Science and Engineering, organized the workshop to continue to build community amongst big data researchers at Texas A&M.

Since the first workshop, interdisciplinary teams from Texas A&M have submitted proposals for funding opportunities including the NSF BIGDATA and NSF Big Data Spokes programs. In order to help researchers better position themselves for these and other opportunities, the Texas A&M Engineering Experiment Station (TEES), in partnership with the Texas A&M Division of Research, Texas A&M AgriLife Research, Texas A&M Health Science Center (TAMHSC) and the Texas A&M Transportation Institute (TTI), has awarded nearly $350,000 in seed grant funding to seven interdisciplinary research teams for big data.

“Texas A&M is positioned to lead in applications of big data in its disciplinary areas of strength, not only in research, but by leveraging its network of cross-sector partnerships to realize the benefits of big data applications more widely,” said Duffield. Texas A&M will host a conference on “Advances in Big Data Modeling, Computation and Analytics,” on Sept.22-24, which will feature leading researchers and practitioners in the field.

The 2016 workshop program, including slides for some presentations, can be found at http://cesg.tamu.edu/bigdata2016/.