Institute of Computing and Cybersystems (ICC) Blog

Day: January 17, 2020

From the ICC Director: Reflections and Goals

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Dear ICC Members and Friends,

Happy New Year! As we begin the new year and the Spring 2020 semester, I wanted to offer some reflections about the 2019 and share some goals for 2020.

For the ICC, the past six months have been thrilling, to say the least. The number of new awards is far above last year, with over $2 million in new projects to-date. And ICC research expenditures are on track for a record year. Thank you to everyone for all your hard work in developing collaborations, writing proposals, winning awards, executing your exciting research, mentoring, advising, and so much more.

The launch of Michigan Tech’s new College of Computing is such a fantastic opportunity. With this shift, we boldly announce that computing is a major field of study and not just an underpinning to other disciplines. I see the new College as a place of opportunity to experiment, collaborate, develop new pedagogies, and become a model for other institutions of higher learning. Our team is strong and creative, and it’s fun working on this puzzle with them.”

As the ICC is the research arm of the College of Computing, we are very much a part of the strategic vision for research in the College. This integration allows us to best utilize the finite resources of both the College of Computing and the ICC to realize the greatest return on key investments in people and resources.

To further support our members, the ICC has secured donor funding  that will make it possible to hire two key personnel in 2020. First, a search for a full-time assistant director for research development is underway. This new position will support ICC researchers as they collectively work to create and implement activities aimed at the growth and development of ICC-affiliated research and graduate programs, including pre- and post-award support, assisting with the financial processes of the institute, and helping to lead the daily administrative functions of the institute. We will also be starting a search soon for the first full-time Research Scientist in the ICC. More details on these hires will made public soon.

I’m very much looking forward to working with all of you in the new year.

Timothy C. Havens
Director, Institute for Computing and Cybersystems

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Tomorrow Needs Seminar: Homin Song, Thurs., Jan. 23, 4 pm

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Homin Song, a postdoctoral researcher at Argonne National Laboratory, will present a lecture on Thursday, January 23, 2020, at 4:00 p.m., in EERC 103.

The lecture is part of the Mechanical Engineering-Engineering Mechanics Graduate Seminar Speaker Series. It is presented in part by the Tomorrow Needs Faculty and Scientist Seminar Series sponsored by the Michigan Tech colleges of Computing, Engineering, and Sciences and Arts, Great Lakes Research Center, and Institute of Computing and Cybersystems. Learn more at mtu.edu/icc/seminars.

Homin’s research interests lie in nondestructive evaluation (NDE) and structural health monitoring (SHM) based on ultrasonic wave motion. His broad spectrum of expertise encompasses the topical areas of NDE/SHM, such as advanced ultrasound sensing technology, signal/data processing, numerical modeling, and experimental solid mechanics. His current postdoctoral research aims at developing a super-resolution non-contact ultrasonic array imaging technique via deep learning.

Song completed a Ph.D. in civil engineering at University of Illinois at Urbana-Champaign in 2019. He holds an M.S. degree from Korea Advanced Institute of Science and Technology (KAIST) and a B.S. from Hanyang University, also in civil engineering.

Homin was awarded the Student Best Paper Award at the 2017 International Workshop on Structural Health Monitoring, the Student Award for Research on NDT from American Concrete Institute, and the Outstanding Paper Award from the Korean Society of Civil Engineers. 

Abstract: Nondestructive evaluation (NDE) and structural health monitoring (SHM) systems are essential for today’s modern structures to ensure their long-term performance and reduced maintenance cost. The talk will present two full-field high-resolution ultrasonic imaging approaches to detect, image, and characterize internal damage in various materials and structural elements. The first approach is a near-field imaging technique via noncontact ultrasonic scanning measurements. Development of novel ultrasonic scanning hardware, numerical and experimental wave mechanics study to understand complicated wave scattering, and wavefield data processing are presented. A unique application of the developed approach to large-scale concrete structures under realistic damage-promoting environments is also presented. The second approach is a far-field imaging technique based on deep learning. A novel hierarchical multi-scale deep learning approach designed to image subtle structural defects is presented. The results are compared with those obtained by a widely accepted high-resolution imaging technique, Time-reversal MUSIC. 

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ECE’s Tony Pinar Joins ICC

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The Institute of Computing and Cybersystems (ICC) is pleased to welcome Tony Pinar as a member. Pinar’s primary research interests are in applied machine learning and data fusion. A lecturer in Michigan Tech’s Electrical and Computer Engineering department, Pinar holds a Ph.D. and M.S. in Electrical Engineering from Michigan Tech. His previous positions include research engineer for Michigan Tech’s Advanced Power System Research Center and electrical design engineer for GE Aviation. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the IEEE Computational Intelligence Society.

Pinar’s teaching interests include machine learning, signal processing, and electronic design. Included among the classes he teaches are Electronics, Electronic Applications, Probability—Signal Analysis, and Control Systems I.

“Teaching is like a puzzle where one may have to take a difficult concept, reduce it to digestible pieces, and deliver them to fresh minds in a way to maximize understanding and insight,” Pinar says. “That challenge is what drives me to be a better teacher.”

Pinar believes that to be a good teacher one must understand the topics very well and he strives for the most effective delivery. “This keeps me on my toes, forces me to constantly identify holes in my knowledge, and drives me to continuously strive to learn new things,” he explains.

On research, Pinar says it is rewarding to work on open-ended and novel problems that are in their infancy and at the cutting edge of today’s technology.

“It is also exciting to me to watch the cutting edge move forward, see what sticks and what doesn’t, and observe how the direction(s) of the field evolve,” he adds. “I’m very new to this domain so I haven’t been able to observe it for long, but I am looking forward to witnessing the future of the field.”

Pinar is looking forward to becoming more involved with research, and he is looking for new collaborations with other ICC and Michigan Tech researchers.

“The resources and network the ICC provides to new—and even established—researchers are set up in a way to cultivate its members’ talent and support career pathways. I am looking forward to being a part of this dynamic Michigan Tech research institute,” Pinar says.

Pinar’s recent publications include the following.

M. A. Islam, D. T. Anderson, A. Pinar, T. C. Havens, G. Scott and J. M. Keller. “Enabling Explainable Fusion in Deep Learning with Fuzzy Integral Neural Networks”. IEEE Transactions on Fuzzy Systems(2019).

U. Agrawal, A.J. Pinar, C. Wagner, T.C. Havens, D. Soria, J.M. Garibaldi. “Comparison of Fuzzy Integral-Fuzzy Measure Based Ensemble Algorithms with the State-of-the-Art Ensemble Algorithms”. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU) (2018).

B. Murray, M.A. Islam, A.J. Pinar, T.C. Havens, D.T. Anderson, G. Scott. “Explainable AI for Understanding Decisions and Data-Driven Optimization of the Choquet Integral”. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2018).

A.J. Pinar, D.T. Anderson, T.C. Havens, A. Zare, T. Adeyeba. “Measures of the Shapley Index for Learning Lower Complexity Fuzzy Integrals”. SpringerGranular Computing(2017).

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