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    Robert West of DePauw University to Present Lecture Feb. 8

    Dr. Robert West, the Elizabeth P. Allen Distinguished University Professor, Department of Psychology and Neuroscience, DePauw University, will present a lecture on Monday, February 8, 2021, at 2:00 p.m., via online meeting.

    The title of Dr. West’s lecture is, “Why Josh Stole the Password: A Decision Neuorscience Approach to Insider Threat in Information Security.”

    The lecture is hosted by the Human-Centered Computing (HCC) research group of the Institute of Computing and Cybersystems (ICC) and the Department of Cognitive and Learning Sciences (CLS).


    Robert West Bio

    Dr. Robert West received his Ph.D from the University of South Carolina in Cognitive Development, and completed postdoctoral work at the Rotman Research Institute in Toronto, studying cognitive aging and cognitive neuroscience.

    He has been on faculty at the University of Notre Dame, Iowa State University, and is currently the Elizabeth P. Allen Distinguished University Professor in the Department of Psychology and Neuroscience at DePauw University. He is a fellow of the Association for Psychological Science, the Psychonomic Society, and the Midwestern Psychological Association; and a founding member of the NeuroIS Society.

    West’s research interests and publications span the areas of decision neuroscience, cognitive neuroscience of aging, and cognitive control. He has served as the associate editor for the Journals of Gerontology: Psychological Science, and is currently associate editor for Psychology and Aging.


    Lecture Abstract

    Cybercrime has a significant impact on nations, corporations, and individuals. Violations of information security can reduce consumer confidence and valuation at the corporate level, and jeopardize social and financial well-being at the personal level. In this talk, I will explore the findings of some of my recent research in order to demonstrate the utility of a decision neuroscience approach to providing insight into the neural correlates of ethical decision making in the context of information security.

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    Sun Named to Lou and Herbert Wacker Professorship in Mechanical Engineering

    by Office of the Provost & Senior VP for Academic Affairs

    Ye “Sarah” Sun (ME-EM) has accepted the Lou and Herbert Wacker Professorship in Mechanical Engineering, which was created to retain and attract high-quality faculty who are at the top of their profession, can excite students to think beyond the classroom material, and knows how to integrate their research into the classroom.

    Sun was chosen for this position as she is recognized as a rising star and outstanding researcher in the area of wearable sensors, systems, and robotics and a respected member of the smart health community.

    In recognition of her innovative research in wearable sensors, Sun’s NSF CAREER award was selected for presentation to congressional offices in April 2019.

    Sun is the director of the Institute of Computing and Cybersystems’s Center for Cyber-Physical Systems.

    Among her research honors is the prestigious National Science Foundation (NSF) CAREER Research Award on “System-on-Cloth: A Cloud Manufacturing Framework for Embroidered Wearable Electronics.”

    Sun will use this recognition and support to enhance her research in wearable and soft robotics. Her goal is to develop flexible textile robotics by leveraging the physical understanding and modeling of textile materials and dynamics and the recent advances of morphological computing.

    Textile robotics are not only able to enhance human capabilities via wearable design but also achieve autonomous locomotion. The controllable structures of textiles directly provide a unified platform that is capable of integrating sensing and actuating into textile robotics itself. The positioning support will be used to recruit graduate students and to set up the manufacturing platform.


    1010 with … Nathir Rawashdeh, Weds., Dec. 16

    Nathir Rawashdeh (right) and Dan Fuhrmann, Interim Dean, Dept. of Applied Computing

    You are invited to spend one-zero-one-zero—that is, ten—minutes with Dr. Nathir Rawashdeh on Wednesday, December 16, from 5:30 to 5:40 p.m.

    Rawashdeh is assistant professor of applied computing in the College of Computing at Michigan Tech.

    He will present his current research work, including the using artificial intelligence for autonomous driving on snow covered roads, and a mobile robot using ultraviolet light to disinfect indoor spaces. Following, Rawashdeh will field listener questions.

    We look forward to spending 1010 minutes with you!

    Did you miss last week’s 1010 with Chuck Wallace? Watch the video below.

    1010 with … Chuck Wallace, Assoc. Prof, Computer Science, December 9, 2020.

    The 1010 with … series will continue on Wednesday afternoons in the new year on January 6, 13, 20, and 27 … with more to come!


    Celebrate Husky Innovation January 25-29

    Husky Innovate is organizing Innovation Week, a series of innovation themed events the week of January 25 to 29, 2020. Our goal is to provide opportunities for students, faculty and alumni to meet virtually to engage around the topic of innovation.

    We will host panel discussions, alumni office hours and the Bob Mark Business Model Pitch Competition from 5:30 to 7:30 p.m. on Thursday, January 28.

    We will celebrate entrepreneurship, innovative research and projects on campus and within our extended MTU community.

    If you are interested in hosting an innovation tour, participating in a panel discussion, leading a workshop or something else, sign-up here.

    Faculty and staff are invited to celebrate innovation week with an innovation themed learning module or student activity.


    Siva Kakula to Present PhD Defense Dec. 21, 3 pm

    Graduate student Siva Krishna Kakula, Computer Science, will present his PhD defense, “Explainable Feature- and Decision-Level Fusion,” on Monday, December 21, 2020, from 3:00 to 5:00 p.m. EST Kakula is advised by Dr. Timothy Havens, College of Computing.

    Siva Kakula earned his master of science in computer engineering at Michigan Tech in 2014, and completed a bachelor of technology in civil engineering at IIT Guwahati in 2011. His research interests include machine learning, pattern recognition, and information fusion.

    Download the informational flier below.

    Lecture Abstract

    Information fusion is the process of aggregating knowledge from multiple data sources to produce more consistent, accurate, and useful information than any one individual source can provide. In general, there are three primary sources of data/information: humans, algorithms, and sensors. Typically, objective data—e.g., measurements—arise from sensors. Using these data sources, applications such as computer vision and remote sensing have long been applying fusion at different “levels” (signal, feature, decision, etc.). Furthermore, the daily advancement in engineering technologies like smart cars, which operate in complex and dynamic environments using multiple sensors, are raising both the demand for and complexity of fusion. There is a great need to discover new theories to combine and analyze heterogeneous data arising from one or more sources.

    The work collected in this dissertation addresses the problem of feature- and decision-level fusion. Specifically, this work focuses on Fuzzy Choquet Integral (ChI)-based data fusion methods. Most mathematical approaches for data fusion have focused on combining inputs relative to the assumption of independence between them. However, often there are rich interactions (e.g., correlations) between inputs that should be exploited. The ChI is a powerful aggregation tool that is capable modeling these interactions. Consider the fusion of N sources, where there are 2N unique subsets (interactions); the ChI is capable of learning the worth of each of these possible source subsets. However, the complexity of fuzzy integral-based methods grows quickly, as the fusion of N sources requires training 2N-2 parameters; hence, we require a large amount of training data to avoid the problem of over-fitting. This work addresses the over-fitting problem of ChI-based data fusion with novel regularization strategies. These regularization strategies alleviate the issue of over-fitting while training with limited data and also enable the user to consciously push the learned methods to take a predefined, or perhaps known, structure. Also, the existing methods for training the ChI for decision- and feature-level data fusion involve quadratic programming (QP)-based learning approaches that are exorbitant with their space complexity. This has limited the practical application of ChI-based data fusion methods to six or fewer input sources. This work introduces an online training algorithm for learning ChI. The online method is an iterative gradient descent approach that processes one observation at a time, enabling the applicability of ChI-based data fusion on higher dimensional data sets.

    In many real-world data fusion applications, it is imperative to have an explanation or interpretation. This may include providing information on what was learned, what is the worth of individual sources, why a decision was reached, what evidence process(es) were used, and what confidence does the system have on its decision. However, most existing machine learning solutions for data fusion are “black boxes,” e.g., deep learning. In this work, we designed methods and metrics that help with answering these questions of interpretation, and we also developed visualization methods that help users better understand the machine learning solution and its behavior for different instances of data.


    Sarah Sun to Present ME-EM Graduate Seminar Dec. 3, 4 pm

    by Mechanical Engineering – Engineering Mechanics

    The next virtual Graduate Seminar Speaker will be held at 4 p.m. tomorrow (Dec. 3) via Zoom. Sarah Sun (ME-EM) will present “E-Logo: Embroidered Wearable Electronics.”

    Sun is an associate professor in the Department of Mechanical Engineering-Engineering Mechanics and an affiliated associate professor in the Department of Biomedical Engineering at Michigan Tech since 2014.


    Sidike Paheding Lecture is Dec. 11, 3 pm

    Assistant Professor Sidike Paheding, Applied Computing, will present his lecture, “Deep Neural Networks for UAV and Satellite Remote Sensing Image Analysis,” on Dec. 11, 2020, at 3:00 p.m. via online meeting.

    Paheding’s research focuses on the areas of computer vision, machine learning, deep learning, image/video processing, and remote sensing.

    The lecture is presented by the Department of Computer Science.

    Lecture Abstract

    Remote sensing data can provide non-destructive and instantaneous estimates of the earth’s surface over a large area, and has been accepted as a valuable tool for agriculture, weather, forestry, defense, biodiversity, etc. In recent years, deep neural networks (DNN), as a subset of machine learning. for remote sensing has gained significant interest due to advances in algorithm development, computing power, and sensor systems.

    This talk will start with remote sensing image enhancement framework, and then primarily focuses on DNN architectures for crop yield prediction and heterogeneous agricultural landscape mapping using UAV and satellite imagery.

    Speaker Biography

    Paheding is an associate editor of the Springer journal Signal, Image, and Video Processing, ASPRS Journal Photogrammetric Engineering & Remote Sensing, and serves as a guest editor/reviewer for a number of reputed journals. He has advised students at undergraduate, M.S., and Ph.D. levels, and authored/coauthored close to 100 research articles.


    Bo Chen, CS, Wins REF Grant for Decentralized Cloud Storage Project

    Bo Chen, Computer Science, has been awarded a Fall 2020 REF Research Seed Grant (REF-RS) for his project, “Towards Secure and Reliable Decentralized Cloud Storage.” Funding for the 12-month, $25,800 award begins on January 1, 2021.

    “This grant will provide significant help to advance my current research,” says Chen. “This is really exciting news for me.”

    Bo Chen is a researcher with the ICC’s Cybersecurity and Computing Education research groups.

    As a recipient of the REF seed grant, which is awarded by the Michigan Tech Office of the Vice President for Research, Chen will participate in review and feedback for the next round of REF proposals. View the full list of Fall 2020 REF award recipients here.

    Abstract

    A decentralized cloud storage system eliminates the need of dedicated computing infrastructures by allowing peers which have spare storage space to join the network and to provide storage service. Compared to the conventional centralized cloud storage system, it can bring significant benefits including cheaper storage cost, better fault tolerance, greater scalability, as well as more efficient data storing and retrieval, making it well fit the emerging Internet of things (IoT) applications.

    While bringing immense benefits, the decentralized cloud storage system also raises significant security concerns, since the storage peers are much less reputable than the traditional data centers and may more likely misbehave.

    This project thus aims to build a secure and reliable decentralized cloud storage system which can serve as the cloud infrastructure for future IoT applications. The project will actively investigate two fundamental security issues faced by the decentralized cloud storage system: 1) How can we prevent the malicious storage peers from stealing the data? 2) How can we ensure that once the data are stored into the system, they are always retrievable even if the storage peers misbehave?

    To address the aforementioned issues in an untrusted p2p environment, the PI will integrate efficient integrity checking with the blockchain, as well as the broadly equipped secure hardware like Intel SGX. The PI will also broaden the educational impact of the proposed project by actively involving both graduate and undergraduate students from the MTU cybersecurity programs.


    Research Excellence Fund Awards Announced

    by Vice President for Research Office

    The Vice President for Research Office announces the Fall 2020 REF awards. Thanks to the individual REF reviewers and the REF review panelists, as well as the deans and department chairs, for their time spent on this important internal research award process.

    Research Seed Grants:

    • Sajjad Bigham, Mechanical Engineering-Engineering Mechanics
    • Bo Chen, Computer Science
    • Daniel Dowden, Civil and Environmental Engineering
    • Ana Dyreson, Mechanical Engineering-Engineering Mechanics
    • Hassan Masoud, Mechanical Engineering-Engineering Mechanics
    • Xinyu Ye, Civil and Environmental Engineering