Please join the online Graduation Recognition Celebration for Electrical and Computer Engineering at 6 p.m. on Friday, May 8, 2020.
More information can be found here: https://engineering.tamu.edu/events/recognition-celebration.html and from emails sent by the department.
“CONGRATULATIONS!” from all the faculty and staff at Computer Engineering Systems Group!
List of Spring 2020’s CEEN Graduates listed here:
Graduates Spring 2020 PhD Final
Congratulations to CESG’s Dr. Paul Gratz!
Dr. Gratz’s paper titled “Synchronized Progress in Interconnection Networks (SPIN) : A New Theory for Deadlock Freedom” was selected for The IEEE Micro Top Picks in Architecture for 2018.
This paper proposes a new theoretical approach to deadlock freedom in interconnection networks, based upon reframing the problem as one of coordination among independent actors as opposed to a problem of resource acquisition ordering.
To read more about Dr. Gratz’s research, see Rachel Rose’s ECE article on the department news page in February 2019.
IEEE Micro publishes its yearly “Micro’s Top Picks from the Computer Architecture Conferences” as its May / June 2019 issue. This issue collects the year’s most significant research papers in computer architecture based on novelty and potential for long-term impact.
Get an early look at Dr. Gratz’s paper here:
“IEEE Micro Top Paper Pick 2018 – Gratz Synchronized Progress in Interconnection Networks (SPIN) A New Theory for Deadlock Freedom”.
Nick Duffield, professor in the Department of Electrical and Computer Engineering, College of Engineering at Texas A&M University, is the new director of the Texas A&M Institute of Data Science (TAMIDS), the Division of Research announced (in October 2018).
“Texas A&M’s choice to prioritize data science by creating TAMIDS presents a tremendous opportunity to build a groundbreaking and innovative environment,” Vice President for Research Mark A. Barteau said. “Texas A&M is preeminent in fields where data science is poised to have an enormous impact. As director of TAMIDS, Dr. Duffield brings outstanding credentials from a career spanning academia and industry, with a skill set combining technological leadership, scientific achievement, interdisciplinary collaboration, commercial impact, community building, and education. Texas A&M is committed to supporting the development of TAMIDS, under Dr. Duffield’s vision and leadership, to catalyze our growth in data science, and establish a distinctive position in the data science ecosystem that builds on Texas A&M’s unique strengths.”
Before joining Texas A&M in 2014, Duffield was a Distinguished Member of Technical Staff and AT&T Fellow at AT&T Labs Research in Florham Park, N.J. He received his doctorate in physics from the University of London. He held academic positions in Europe before joining AT&T in 1995.
Duffield is an author or co-author on more than 160 publications in the areas of data science and computer networking. He holds 54 U.S. patents and his work has been implemented in Internet systems, services and standards. His current research involves algorithms for data streaming and machine learning, computer-network measurement and resilience, and applications of data science to transportation, agriculture and hydrology. Duffield’s work at Texas A&M has received support from the National Science Foundation, DARPA, Google and Intel. He is a fellow of IEEE as well as the Institution of Engineering and Technology, and has twice received the Association for Computing Machinery (ACM) SIGMETRICS Test-of-Time award. He is an elected member of the governing board of ACM SIGMETRICS.
The Texas A&M Institute of Data Science pursues and supports new approaches of multi-disciplinary data science research, education and external partnerships. These approaches cross departmental and college boundaries to address all facets of the data-science landscape that naturally connect engineering, technology, science and the humanities and inform wider policy and social challenges.
For more information on TAMIDS: tamids.tamu.edu
About Research at Texas A&M University: As one of the world’s leading research institutions, Texas A&M is at the forefront in making significant contributions to scholarship and discovery. Research conducted at Texas A&M represented annual expenditures of more than $905.4 million in fiscal year 2017. Texas A&M ranked in the top 20 of the National Science Foundation’s Higher Education Research and Development survey (2016), based on expenditures of more than $892.7 million in fiscal year 2016. Texas A&M’s research creates new knowledge that provides basic, fundamental and applied contributions resulting, in economic benefits and improved quality of life for the peoples of the state, nation and world. To learn more, visit http://research.tamu.edu.
Media Contact: Susan Wolff, (979) 847-9365, s-wolff@tamu.edu
Source: Texas A&M Today
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.
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.
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://ecencesg.wpengine.com/bigdata2016/.
On Friday, March 28, Texas A&M University has the pleasure of hosting “Texas Systems Day” at Rudder Tower. This workshop brings together researchers from universities around the state in the fields of systems, controls, and robotics. It is planned to make this an annual event with locale rotating among the universities
The plenary speaker is Professor Jessy Grizzle of the University of Michigan who will talk on the subject of underactuated 3D walking by robots. There will be a Panel Discussion on the topic, “Future Directions in Systems, Control & Robotics.” Other talks include, “Translational Control Design for Lower-Limb Prosthetics and Orthotics: Lessons from Robot Locomotion”, by Prof. Robert Gregg, Mechanical Engineering and Biological Engineering at UT Dallas, “Multiscale Robotics and Control: from Microns and Milimeters to Human Size”, by Prof. Dan Popa, Electrical Engineering at Next Generation Systems lab and UT Arlington Research institute, and, “Architectures for Learning and Representation in Robotics”, by Prof. Mohan Sridharan, Computer Science at Texas Tech.
Texas A&M will also have two professors giving presentations, Prof. Bryan Rasmussen from the Mechanical Engineering Department presenting, “Distributed Control of Building Energy Systems”, and Prof. Raktim Bhattacharya from the Aerospace Engineering Department presenting, “Computational Uncertainty in Cyber Physical Systems”. To conclude the day, there will be a poster presentation and reception in Koldus room 110.
The Steering Committee of the conference consists of Prof. P. R. Kumar of Texas A&M University, Dean Mark Spong of the College of Engineering at University of Texas, Dallas, and Prof. Ari Arapostathis of University of Texas in Austin. Prof. Raktim Bhattacharya serves as the Chair of the 2014 Organizational Committee, with members consisting of Profs. Steve Yurkovich from UT Dallas, Kamesh Subbarao from UT Arlington, Beibei Ren from Texas Tech, Fathi Ghorbel from Rice, and Ari Arapostathis from UT Austin.
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Computer Engineering & Systems Group
Department of Electrical & Computer Engineering
Texas A&M University
333E WERC, College Station, Texas, 77843-3259
Phone (979) 458-5005, Fax (979) 845-2630
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