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    Susanta Ghosh is PI on $170K NSF Grant

    Susanta Ghosh

    Susanta Ghosh (ICC-DataS/MEEM/MuSTI) is Principal Investigator on a project that has received a $170,604 research and development grant from the National Science Foundation. The project is titled “EAGER: An Atomistic-Continuum Formulation for the Mechanics of Monolayer Transition Metal Dichalcogenides.” This is a potential 19-month project.

    Dr. Ghosh is an assistant professor of Mechanical Engineering-Engineering Mechanics at Michigan Tech. Before joining the Michigan Tech College pof Engineering, Dr. Ghosh was an associate in research in the Pratt School of Engineering at Duke University; a postdoctoral scholar in the departments of Aerospace Engineering and Materials Science & Engineering at the University of Michigan, Ann Arbor; and a research fellow at the Technical University of Catalunya, Barcelona, Spain. His M.S. and Ph.D. degrees are from the Indian Institute of Science (IISc), Bangalore. His research interests include multi-scale solid mechanics, atomistic modeling, ultrasound elastography, and inverse problem and computational science.

    Abstract: Two-dimensional materials are made of chemical elements or compounds of elements while maintaining a single atomic layer crystalline structure. Two-dimensional materials, especially Transition Metal Dichalcogenides (TMDs), have shown tremendous promise to be transformed into advanced material systems and devices, e.g., field-effect transistors, solar cells, photodetectors, fuel cells, sensors, and transparent flexible displays. To achieve broader use of TMDs across cutting-edge applications, complex deformations for large-area TMDs must be better understood. Large-area TMDs can be simulated and analyzed through predictive modeling, a capability that is currently lacking. This EArly-concept Grant for Exploratory Research (EAGER) award supports fundamental research that overcomes current challenges in large-scale atomistic modeling to obtain an efficient but reliable continuum model for single-layer TMDs containing billions of atoms. The model will be translational and will contribute towards the development of a wide range of applications in the nanotechnology, electronics, and alternative energy industries. The award will further support development of an advanced graduate-level course on multiscale modeling and organization of symposia in two international conferences on mechanics of two-dimensional materials. Experimental samples of TMDs contain billions of atoms and hence are inaccessible to the state-of-the-art molecular dynamics simulations. Moreover, existing crystal elastic models for surfaces cannot be applied to multi-atom thick 2D TMDs due to the presence of interatomic bonds across the atomic surfaces. The crystal elastic model aims to solve this problem by projecting all interatomic bonds onto the mid-surface to track their deformations. The actual deformed bonds will, therefore, be computed using the deformations of the mid-surface. Additionally, a technique will be derived to incorporate the effects of curvature and stretching of TMDs on their interactions with substrates. The model will be exercised to generate insights into the mechanical instabilities and the role of substrate interactions on them. The coarse-grained model will overcome the computational bottleneck of molecular dynamics models to simulate TMDs samples comprising billions of atoms. This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.


    Scalable Spectral Sparsification of Graph Laplacians and Integrated Circuits

    Circuit board

    Researcher: Zhuo Feng, Associate Professor, Electrical and Computer Engineering

    Sponsor: National Science Foundation: SHF: Small

    Amount of Support: $450,000

    Duration of Support: 3 years

    Abstract: This research is motivated by investigations on scalable methods for design simplifications of nanoscale integrated circuits (ICs). This is to be achieved by extending the associated spectral graph sparsification framework to handle Laplacian-like matrices derived from general nonlinear IC modeling and simulation problems. The results from this research may prove to be key to the development of highly scalable computer-aided design algorithms for modeling, simulation, design, optimization, as well as verification of future nanoscale ICs that can easily involve multi-billions of circuit components. The algorithms and methodologies developed will be disseminated to leading technology companies that may include semiconductor and Electronic Design Automation companies as well as social and network companies, for potential industrial deployments.

    Spectral graph sparsification aims to find an ultra-sparse subgraph (a.k.a. sparsifier) such that its Laplacian can well approximate the original one in terms of its eigenvalues and eigenvectors. Since spectrally similar subgraphs can approximately preserve the distances, much faster numerical and graph-based algorithms can be developed based on these “spectrally” sparsified networks. A nearly-linear complexity spectral graph sparsification algorithm is to be developed based on a spectral perturbation approach. The proposed method is highly scalable and thus can be immediately leveraged for the development of nearly-linear time sparse matrix solvers and spectral graph (data) partitioning (clustering) algorithms for large real-world graph problems in general. The results of the research may also influence a broad range of computer science and engineering problems related to complex system/network modeling, numerical linear algebra, optimization, machine learning, computational fluid dynamics, transportation and social networks, etc.

    More details.


    Improving Reliability of In-Memory Storage

    Electronic circuit board

    Researcher: Jianhui Yue, PI, Assistant Professor, Computer Science

    Sponsor: National Science Foundation, SHF: Small: Collaborative Research

    Amount of Support: $192, 716

    Duration of Support: 3 years

    Abstract: Emerging nonvolatile memory (NVM) technologies, such as PCM, STT-RAM, and memristors, provide not only byte-addressability, low-latency reads and writes comparable to DRAM, but also persistent writes and potentially large storage capacity like an SSD. These advantages make NVM likely to be next-generation fast persistent storage for massive data, referred to as in-memory storage. Yet, NVM-based storage has two challenges: (1) Memory cells have limited write endurance (i.e., the total number of program/erase cycles per cell); (2) NVM has to remain in a consistent state in the event of a system crash or power loss. The goal of this project is to develop an efficient in-memory storage framework that addresses these two challenges. This project will take a holistic approach, spanning from low-level architecture design to high-level OS management, to optimize the reliability, performance, and manageability of in-memory storage. The technical approach will involve understanding the implication and impact of the write endurance issue when cutting-edge NVM is adopted into storage systems. The improved understanding will motivate and aid the design of cost-effective methods to improve the life-time of in-memory storage and to achieve efficient and reliable consistence maintenance.

    Publications:

    Pai Chen, Jianhui Yue, Xiaofei Liao, Hai Jin. “Optimizing DRAM Cache by a Trade-off between Hit Rate and Hit Latency,” IEEE Transactions on Emerging Topics in Computing, 2018. doi:10.1109/TETC.2018.2800721

    Chenlei Tang, Jiguang Wan, Yifeng Zhu, Zhiyuan Liu, Peng Xu, Fei Wu and Changsheng Xie. “RAFS: A RAID-Aware File System to Reduce Parity Update Overhead for SSD RAID,” Design Automation Test In Europe Conference (DATE) 2019, 2019.

    Pai Chen, Jianhui Yue, Xiaofei Liao, Hai Jin. “Trade-off between Hit Rate and Hit Latency for Optimizing DRAM Cache,” IEEE Transactions on Emerging Topics in Computing, 2018.

    More details


    Appropriating Everyday Surfaces for Tap Interaction

    Zachary Garavet and Siva Kakula

    Researchers

    Scott Kuhl (Associate Professor, CS)

    Keith Vertanen (Assistant Professor, CS)

    Sponsor: ECE Alumnus Paul Williams ’61

    Amount of Support: $44,000

    Duration of Support: 1 year

    What if an everyday surface, like a table, could be transformed into a rich, interactive surface that can remotely operate things like computers, entertainment systems, and home appliances?

    That’s what Michigan Tech Institute of Computing and Cybersystems (ICC) researchers Keith Vertanen and Scott Kuhl set out to do with a $44K seed grant from Electrical and Computer Engineering alumnus Paul Williams ’61.

    Vertanen, assistant professor of computer science, and Kuhl, associate professor of computer science, are members of the ICC’s Center for Human-Centered Computing, which integrates art, people, design, technology, and human experience in the research of multiple areas of human-centered computing. They were assisted in this research by PhD candidate Siva Krishna Kakula, Computer Science, and undergraduate Zachary Garavet, Computer Engineering.

    The team’s research goals were threefold: to create machine learning models that can precisely locate a user’s taps on a surface using only an array of inexpensive surface microphones; demonstrate the feasibility and precision of the models by developing a virtual keyboard interface on an ordinary wooden table; and conduct user studies to validate the system’s usability and performance.

    The researchers are working on a related technical conference paper to present to their peers. Their outcomes included a prototype virtual keyboard that supports typing at rates comparable to a touchscreen device; possibly the first-ever acoustic sensing algorithm that infers a continuous two-dimensional tap location; and novel statistical models that quickly adapt to individual users and varied input surfaces.

    Further, their results, hardware, and data sets can be applied to future collaborative work, and were used in the researchers’ $500K National Science Foundation proposal, “Text Interaction in Virtual and Augmented Environments,” which is under review.

    Future applications of the research include enriched interactions in Virtual Reality (VR) and Augmented Reality (AR), compared to existing vision-only based sensing; and on-body interaction, like using your palm as an input surface.

    Vertanen and Kuhl plan to continue this research, working to improve the accuracy of tap location inference, build richer interactions like swiping or tapping with multiple fingers, develop wireless sensor pods that can be quickly and easily deployed on any flat surface, and explore the display of virtual visual content on surfaces via Augmented Reality smartglasses.

    View a video about this research at https://youtu.be/sF7aeXMfsIQ.

    Seed grant donor Paul Williams is also the benefactor of the Paul and Susan Williams Center for Computer Systems Research, located on the fifth floor of the Electrical Energy Resources Center. The 10,000-square-foot, high-performance computing center—the home of the ICC—was established to foster close collaboration among researchers across multiple disciplines at Michigan Tech

    The ICC, founded in 2015, promotes collaborative, cross-disciplinary research and learning experiences in the areas of cyber-physical systems, cybersecurity, data sciences, human-centered computing, and scalable architectures and systems. It provides faculty and students the opportunity to work across organizational boundaries to create an environment that mirrors contemporary technological innovation.

    Five research centers comprise the ICC. The ICC’s 50 members, who represent 15 academic units at Michigan Tech, are collaborating to conduct impactful research, make valuable contributions in the field of computing, and solve problems of critical national importance.

    Visit the ICC website at mtu.edu/icc. Contact the ICC at icc-contact@mtu.edu or 906-487-2518.

    Download a summary of this research.


    Development of a Low-Cost Marine Mobile Networking Infrastructure

    Zhaohui Wang

    Researchers:

    Zhaohui Wang, Assistant Professor, ECE

    Nina Mahmoudian, Adjunct Professor, ME-EM

    Sponsor: ECE alumnus Paul Williams ’61
    Amount of Support: $50,000
    Duration of Support: 1 year

    Underwater acoustic communication has been in use for decades, but primarily for military applications. In recent years, private sectors such as environmental monitoring, off-shore oil and gas exploration, and aquaculture have become interested in its possibilities.

    But existing research about underwater acoustic communication networks often relies on human-operated surface ships or cost-prohibitive autonomous underwater vehicles (AUVs). And these cost barriers can limit academic research evaluation to computer simulations, constraining research innovation towards practical applications.

    Recognizing the above gap, Michigan Tech Institute of Computing and Cybersystems (ICC) researchers Zhaohui Wang, assistant professor, Electrical and Computer Engineering, and Nina Mahmoudian, adjunct professor, Mechanical Engineering-Engineering Mechanics,  saw an opportunity to combine their areas of expertise: for Wang, underwater acoustic communications, for Mahmoudian, low-cost marine robotics and AUVs.

    Also part of the research team were PhD student Li Wei, Electrical and Computer Engineering, and post-doc research engineer Barzin Moridian, Mechanical Engineering-Engineering Mechanics. The team also collaborated with scientists at Michigan Tech’s Great Lakes Research Center.

    With a $50K seed grant from Electrical and Computer Engineering alumnus Paul Williams ’61, the team took the research beneath the surface to develop a low-cost marine mobile infrastructure and investigate the challenges and possible solutions in engineering a leading-edge AUV communication network.

    They broke it down into three areas: the development of low-cost, high-modularity autonomous surface vehicles (ASVs), each equipped with a collection of sensors and serving as surrogates for AUVs; equipping each ASV with an acoustic modem and implementing communication and networking protocols to facilitate underwater communication among the vessels; and conducting field experiments to collect data about the fundamental challenges in mobile acoustic communications and networking among AUVs.

    The team’s outcomes included two low-cost, autonomous, on-the-water boats; an experimental data set, data analysis, and preliminary results; a technical paper presented at the 2018 IEEE OES Autonomous Underwater Vehicle Symposium; and a marine mobile wireless networking infrastructure for use in continued research.

    Just half of their seed grant has been used, and this summer Wang and Mahmoudian will work to improve the boats and the communications system, and conduct more field research. In addition, they are planning to write two National Science Foundation proposals to take their research even further.

    View a summary of the research here.

    Seed grant donor Paul Williams is also the benefactor of the Paul and Susan Williams Center for Computer Systems Research, located on the fifth floor of the Electrical Energy Resources Center. The 10,000-square-foot, high-performance computing center—the home of the ICC—was established to foster close collaboration among researchers across multiple disciplines at Michigan Tech

    The ICC, founded in 2015, promotes collaborative, cross-disciplinary research and learning experiences in the areas of cyber-physical systems, cybersecurity, data sciences, human-centered computing, and scalable architectures and systems. It provides faculty and students the opportunity to work across organizational boundaries to create an environment that mirrors contemporary technological innovation.

    Five research centers comprise the ICC. The ICC’s 50 members, who represent 15 academic units at Michigan Tech, are collaborating to conduct impactful research, make valuable contributions in the field of computing, and solve problems of critical national importance.

    Visit the ICC website at mtu.edu/icc. Contact the ICC at icc-contact@mtu.edu or 906-487-2518.

    Download a summary of the research.


    ECE Department to Host Cyber-physical Security Workshop July 30-31

    The Department of Electrical and Computer Engineering is pleased to announce a two-day workshop on cyber-physical security for power infrastructure and transportation to be held on campus July 30-31, 2019. Experts from industry and the academy will share information on current threats and countermeasures to protect power infrastructure and transportation systems.

    Registration protocols will support 13 hours of continuing education for professional license holders.

    More detailed information on the workshop can be found on the ECE blog.

    The cost for Michigan Tech faculty and staff to attend is $100, and the cost for students is $25. Register for the workshop on the online store. To receive the discount, faculty and staff must use the promotional code MTUFAC, and students must use the code MTUSTU on the registration form checkout page.

    Questions about the workshop can be directed to ECE at 7-2550 or ece@mtu.edu.


    Havens Is Co-Chair of Fuzzy Systems Conference

    Timothy HavensTimothy Havens (CC/ICC) was General Co-Chair of the 2019 IEEE International Conference on Fuzzy Systems in New Orleans, LA, June 23 to 26. At the conference, Havens presented his paper, “Machine Learning of Choquet Integral Regression with Respect to a Bounded Capacity (or Non-monotonic Fuzzy Measure),” and served on the panel, “Publishing in IEEE Transactions on Fuzzy Systems.”

    Three additional papers authored by Havens were published in the conference’s proceedings: “Transfer Learning for the Choquet Integral,” “The Choquet Integral Neuron, Its PyTorch Implementation and Application to Decision Fusion,” and “Measuring Similarity Between Discontinuous Intervals – Challenges and Solutions.”