Institute of Computing and Cybersystems (ICC) Blog

Category: Havens

1010 with … Tim Havens, Weds., Jan. 20, 5:30-5:40 pm

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You are invited to spend one-zero-one-zero—that is, ten—minutes with Dr. Timothy Havens on Wednesday, January 20, from 5:30 to 5:40 p.m. EST.

Havens is the Associate Dean for Research in the College of Computing, Director of the Institute of Computing and Cybersystems, and the William and Gloria Jackson Associate Professor of Computer Systems at Michigan Tech.

In this informal discussion, Havens will talk about undergraduate research opportunities at Michigan Tech, his research in AI and machine learning, and answer your questions about the College of Computing.

We look forward to spending 1010 minutes with you!

Did you miss the December 16, 1010 with Nathir Rawashdeh? Watch the video below.

The 1010 with … series continues on Wednesday January 27 … with more to come!

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Panel Discussion Jan. 5: Mobility at Michigan Tech: “Where are we?”

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Mobility is an increasingly used word today in conjunction with the advent of automated vehicle technologies, but what else is covered under this term that is often defined as“the ability to move or be moved freely and easily“? Even more importantly, what is happening at Michigan Tech related to Mobility? Dr. Pasi Lautala (CEE) is working as a Faculty Fellow sponsored by the Vice President for Research Office toward building a collaborative environment for Mobility-related development and research and expanding Michigan Tech’s role as a leader in the field. 

As a kickoff event for these efforts, Dr. Lautala will be hosting a virtual panel discussion on Tuesday, January 5th, from 3:00-4:30 p.m. (EST).  This virtual event will bring together leading Mobility experts from our Michigan Tech community to discuss the wide range of issues addressed under the umbrella of Mobility. The panelists will start the event by briefly introducing how they and their teams are involved in Mobility, followed by an hour-long open discussion on Mobility and related issues. We encourage all university and local community members interested in Mobility to tune in and participate in the discussion. 
The panelists will include:

  • Bill Buller,  Senior Research Scientist, Michigan Tech Research Institute (MTRI) 
  • Timothy Havens, William and Gloria Jackson Associate Professor of Computer Systems
  • Don LaFreniere, Associate Professor of Geography and GIS
  • Jeff Naber,  Ron and Elaine Starr Professor in Energy Systems, Mechanical Engineering—Engineering Mechanics
  • Chelsea Schelly, Associate Professor of Sociology, Social Sciences
  • Roman Sidortsov,  Assistant Professor, Energy Policy, Social Sciences

This panel discussion is the first in a series of events related to Mobility planned for the spring semester, and will largely focus on the current state of Mobility at Michigan Tech.  Following events will seek to bring in external experts to share their insights and begin to develop building blocks that will lay the foundation for specific Mobility-related collaborative research proposals.

To participate in the event, use the Zoom link provided below. For more information, please contact Pasi Lautala at ptlautal@mtu.edu.

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

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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.

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Tim Havens: Warm and Fuzzy Machine Learning

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What are you doing for supper this Monday night at 6? Grab a bite with Dean Janet Callahan and Associate Professor Tim Havens, director of the Michigan Tech’s Institute of Computing and Cybersystems and associate dean for research in the College of Computing. Get the full scoop and register at mtu.edu/huskybites.

“Nearly everyone has heard the term ‘Deep Learning’ at this point, whether to describe the latest artificial intelligence feat like AlphaGo, autonomous cars, facial recognition, or numerous other latest-and-greatest gadgets and gizmos,” says Havens. “But what is Deep Learning? How does it work? What can it really do—and how are Michigan Tech students advancing the state-of-the-art?”

In this session of Husky Bites, Prof. Havens will talk about everyday uses of machine learning—including the machine learning research going on in his lab: explosive hazards detection, under-ice acoustics detection and classification, social network analysis, connected vehicle distributed sensing, and other stuff.

Joining in will be one of Havens’ former students, Hanieh Deilamsalehy, who earned her PhD in electrical engineering at Michigan Tech. She’s now a machine learning researcher at Adobe. Dr. Deilamsalehy graduated from Michigan Tech in 2017 and headed to Palo Alto to work for Ford as an autonomous vehicle researcher. She left the Bay Area for Seattle to take a job at Microsoft, first as a software engineer, and then as a machine learning scientist. In April she accepted a new machine learning position at Adobe, “in the middle of the pandemic!”

Havens is a Michigan Tech alum, too. He earned his BS in ‘99 and MS in Electrical Engineering in ‘00, then went to the MIT Lincoln Laboratory, where he worked on simulation and modeling of the Airborne Laser System, among other defense-related projects. From there it was the University of Missouri for a PhD in Electrical and Computer Engineering, researching machine learning in ontologies and relational data.

Nowadays, Havens is the William and Gloria Jackson Associate Professor and Associate Dean for Research in the College of Computing. In addition to serving as director of Michigan Tech’s ICC, he also heads up the ICC Center for Data Sciences and runs his own PRIME Lab, too (short for Pattern Recognition and Intelligent Machines Engineering).

“An important goal for many mobile platforms—terrestrial, aquatic, or airborne—is reliable, accurate, and on-time sensing of the world around them.”Tim Havens

Havens has spent the past 12 years developing methods to find explosive hazards, working with the US Army and a research team in his lab. According to a United Nations report, more than 10,000 civilians were killed or injured in armed conflict in Afghanistan in 2019, with improvised explosive devices used in 42 percent of the casualties. Havens is working to help reduce the numbers.

“Our algorithms detect and locate explosive hazards using two different systems: a vehicle-mounted multi-band ground-penetrating radar system and a handheld multimodal sensor system,” Havens explains. “Each of these systems employs multiple sensors, including different frequencies of ground penetrating radar, magnetometers and visible-spectrum cameras. We’ve created methods of integrating the sensor information to automatically find the explosive hazards.” 

As a PhD student at Michigan Tech, Deilamsalehy worked alongside Havens as a research assistant in the ECE department’s Intelligent Robotics Lab (IRLab). “My research was focused on sensor fusion, machine learning and computer vision, fusing the data from IMU, LiDAR, and a vision camera for 3D localization and mapping purposes,” she says. “I used data from a sensor platform in the IRLab, mounted on an unmanned aerial vehicle (UAV), to evaluate my proposed fusion algorithm.”

Havens is also co-advisor to students in the SENSE (Strategic Education through Naval Systems Experience) Enterprise team at Michigan Tech, along with ME-EM Professor Andrew Barnard. Students in SENSE design, build, and test engineering systems in all domains: space, air, land, sea, and undersea. Like all Enterprise teams, SENSE is open to students in any major. 

Prof. Havens, when did you first get into engineering? What sparked your interest?

I first became an engineer at Michigan Tech in the late 90s. What really sparked my interest in what-I-do-now was my introductory signal processing courses. The material in these courses was the first stuff that really ‘spoke’ to me. I have always been a serious musician and the mathematics of waves and filters was so intuitive because of my music knowledge. I loved that this field of study joined together the two things that I really loved: music and math. And I’ve always been a computer geek. I was doing programming work in high school to make extra money; so that side of me has always led me to want to solve problems with computers.

Hometown, Hobbies, Family?

I grew up in Traverse City, Michigan, and came to Tech as a student in the late 90s. I’ve always wanted to come back to the Copper Country; so, it’s great that I was able to return to the institution that gave me the jump start in my career. I live (and currently work from home) in Hancock with my partner, Dr. Stephanie Carpenter (an author and MTU professor), and our two fur children, Rick Slade, the cutest ginger in the entire world, and Jaco, the smartest cat in the entire world. I have a grown son, Sage, who enjoys a fast-paced life in Traverse City. Steph and I enjoy exploring the greater Keweenaw and long discussions about reality television, and I enjoy playing music with all the local talent, fishing (though catching is a challenge), and gradually working through the lumber pile in my garage.

Dr. Deilamsalehy, how did you find engineering? What sparked your interest?

I was born and raised in Tehran, Iran. I have always been into robotics. I was a member of our robotics team in high school and that led me to engineering. I decided to apply to Michigan Tech sort of by chance when a friend of mine told me about it. I looked at the programs in the ECE department, and felt they aligned with my interests. Then soon after I first learned about Michigan Tech, I found out that one of my undergraduate classmates went there. I talked to him, and he also encouraged me to apply. And that’s how I was able to join Michigan Tech for my PhD program. My degree is in electrical engineering but my focus at Michigan Tech involved computer science and designing Machine Learning solutions.

Hobbies and Interests?

I now live in Seattle, famous for outdoor activities—kind of like the UP, but without the cold—so I do lots of mountaineering, biking, rock climbing, and in the winter, skiing. I learned how to ski at Michigan Tech, up on Mont Ripley. It’s steep, and it’s cold! Once you learn skiing on Ripley, you’re good. You can ski just about anywhere.
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College of Computing, CNSA Program Focus of HostingAdvice Article

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The College of Computing and the Institute of Computing and Cybersystems (ICC) are the subjects of an article published today (Sept. 2, 2020) on HostingAdvice.com, a website and blog that educates visitors to the site about the world of web hosting.

The article, for which College of Computing Dean Adrienne Minerick was interviewed, provides a close look at the new College, its well-established Computer Science and Software Engineering degree programs (B.S., M.S., and Ph.D.), new Cybersecurity and Mechatronics undergraduate programs, as well as faculty research and the ICC.

Special emphasis is placed on the Computer Network and Systems Administration undergraduate degree program, in which students prepare for careers as network and computer systems administrators, commonly referred to as a “sysadmins.”

Read the full article here.

“Our readers know that a lot goes into finding the best providers of shared, dedicated, and virtual private servers,” said Sean Garrity, managing editor at HostingAdvice.com. “The article provides information about how to prepare if you want to to break into the industry as a professional, not just a consumer.”

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SOSSEC / US Army ERDC Award to Study Adaptive AI

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Dr. Timothy Havens, College of Computing, and Dr. Anthony Pinar, Electrical and Computer Engineering, have been awarded a two-year, $428,707 project by the SOSSEC Inc. / U.S. Army ERDC to investigate “Modeling and Algorithm Development for Adaptive Adversarial AI for Complex Autonomy.”

The project will study how autonomous systems operate in complex and unstructured environments, focusing on sensing, processing, and decision-making capabilities.

Havens and Pinar are members of the Institute of Computing and Cybersystem’s Center for Data Sciences.

Tim Havens is associate dean for research, College of Computing, the William and Gloria Jackson Associate Professor of Computer Systems, and director of the Institute of Computing and Cybersystems.

Tony Pinar is a lecturer and senior design coordinator in the Electrical and Computer Engineering department.

The SOSSEC Consortium was specifically formed to address the needs of the Department of Defense (DoD). It was founded on a simple concept: that collaboration, innovation, and cooperation among a broad spectrum of industry, academia and non-profit entities vastly improves the products and services delivered to its clients, according to the organization’s website.

The mission of the US Army Engineer Research and Development Center (ERDC), an integral component of the Office of the Assistant Secretary of Defense for Research and Engineering, is to help solve the nation’s most challenging problems in civil and military engineering, geospatial sciences, water resources, and environmental sciences for the benefit of the Army, the Department of Defense, civilian agencies, and the public good, according to the organizations’s website.

The Institute of Computing and Cyberersystems (ICC) promotes collaborative, cross-disciplinary research and learning experiences through six research centers in the areas of computing education, cyber-physical systems, cybersecurity, data sciences, human-centered computing, and scalable architectures and systems, for the benefit of Michigan Technological University and society at large.

The ICC’s 55 members represent more than 20 academic disciplines at Michigan Tech. Member scientists are collaborating to conduct impactful research, make valuable contributions in the field of computing, and solve problems of critical national importance.

ICC’s Center for Data Sciences (DataS) focuses on the research of data sciences education, algorithms, mathematics, and applications. DataS fosters interdisciplinary collaborations by bringing together diverse faculty and students from varied disciplines to discover new knowledge and exciting research opportunities in the field of data sciences.

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$243K DURIP Award will Multiply Michigan Tech Research Capabilities

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Dr. Timothy Havens (ICC), Dr. Andrew Barnard (GLRC), Dr. Guy Meadows (GLRC), and Dr. Gowtham (IT/ECE) have been awarded an Office of Naval Research DURIP grant titled, “Acoustic Sensing System and High-Throughput Computing Environment and Threat Monitoring in Naval Environments Using Machine Learning.”

The $243,169 award will fund procurement of new high throughput computing and underwater acoustic sensing systems for use by researchers at Michigan Tech.

The Defense University Research Instrumentation Program (DURIP) supports universities through awards meant to build the infrastructures necessary for relevant, high-quality Navy research.

We believe that these resources will considerably multiply our capability and productivity in assisting the U.S. Navy, and DoD at large, to move forward on numerous fronts. We have excellent resources, but lack some infrastructure capabilities to make a leap in theory and applications.

Timothy Havens, Director, Institute of Computing and Cybersystems

Havens says that the award supports two active U.S. Navy projects in particular, “ONR Graduate Traineeship Award: Multi-Modal, Near-Shore, Ice-Covered Arctic Acoustic Propagation Measurements and Analysis (ONR #N00014-18-1-2592)” and “Localization, Tracking, and Classification of On-Ice and Underwater Noise Sources Using Machine Learning (US NSWC #N00174-19-1-0004).”

“With this new equipment we can begin to conduct more detailed, realistic, and repeatable sensor/target experiments, and facilitate expansion of current research into related areas of interest to the DoD, such as deep learning with digital phased arrays and persistent, distributed sensing with sensor arrays,” Havens notes.

“The equipment will significantly enhance Michigan Tech capabilities for six other Department of Defense (DoD)-funded projects as well, including NGA, SPAWAR, and DARPA awards,” he adds.

Finally, through graduate student participation in the research, and collaboration with the undergraduate SENSE Enterprise at Michigan Tech (Strategic Education through Naval Systems Experiences), the equipment will augment Navy STEM education and future workforce development.

Tim Havens is associate dean for research, College of Computing, the William and Gloria Jackson Associate Professor of Computer Systems, and director of the Institute of Computing and Cybersystems.

Andrew Barnard is director of the Great Lakes Research Center,
associate professor, Mechanical Engineering—Engineering Mechanic, and Faculty advisor to the undergraduate SENSE Enterprise.

Guy Meadows is director of the Marine Engineering Laboratory, the Robbins Professor of Sustainable Marine Engineering, and a research professor in the Department of Mechanical Engineering-Engineering Mechanics.

Gowtham is director of research computing for Michigan Tech’s Information Technology department; an adjunct assistant professor, Physics; a research associate professor, Electrical and Computer Engineering; and an NSF XSEDE Campus Champion.

The Institute of Computing and Cyberersystems (ICC) promotes collaborative, cross-disciplinary research and learning experiences through six research centers in the areas of computing education, cyber-physical systems, cybersecurity, data sciences, human-centered computing, and scalable architectures and systems, for the benefit of Michigan Technological University and society at large.

The ICC’s 55 members represent more than 20 academic disciplines at Michigan Tech. Member scientists are collaborating to conduct impactful research, make valuable contributions in the field of computing, and solve problems of critical national importance.

The Great Lakes Research Center (GLRC) provides state-of-the-art laboratories to support research on a broad array of topics. Faculty members from many departments across Michigan Technological University’s campus collaborate on interdisciplinary research, ranging from air–water interactions to biogeochemistry to food web relationships.

One of the GLRC’s most important functions is to educate the scientists, engineers, technologists, policymakers, and stakeholders of tomorrow about the Great Lakes basin. The Center for Science and Environmental Outreach provides K–12 student, teacher, and community education/outreach programs, taking advantage of the Center’s many teaching labs.

The GLRC also contains a lake-level marine facility and convenient deep-water docking, providing a year-round home for Michigan Tech’s surface and sub-surface fleet of marine vehicles.


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Tim Havens, Tony Pinar Co-Authors of Article in IEEE Trans. Fuzzy Systems

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An article by Anthony Pinar (DataS/ECE) and Timothy Havens (DataS/CC), in collaboration with University of Missouri researchers Muhammad Islam, Derek Anderson, Grant Scott, and Jim Keller, all of University of Missouri, has been published in the July 2020 issue of the journal IEEE Transactions on Fuzzy Systems.

The article is titled, “Enabling explainable fusion in deep learning with fuzzy integral neural networks.” Link to the article here.

Tony Pinar

Tim Havens

Abstract:
Information fusion is an essential part of numerous engineering systems and biological functions, e.g., human cognition. Fusion occurs at many levels, ranging from the low-level combination of signals to the high-level aggregation of heterogeneous decision-making processes. While the last decade has witnessed an explosion of research in deep learning, fusion in neural networks has not observed the same revolution. Specifically, most neural fusion approaches are ad hoc, are not understood, are distributed versus localized, and/or explainability is low (if present at all). Herein, we prove that the fuzzy Choquet integral (ChI), a powerful nonlinear aggregation function, can be represented as a multilayer network, referred to hereafter as ChIMP.

We also put forth an improved ChIMP (iChIMP) that leads to a stochastic-gradient-descent-based optimization in light of the exponential number of ChI inequality constraints. An additional benefit of ChIMP/iChIMP is that it enables explainable artificial intelligence (XAI). Synthetic validation experiments are provided, and iChIMP is applied to the fusion of a set of heterogeneous architecture deep models in remote sensing. We show an improvement in model accuracy, and our previously established XAI indices shed light on the quality of our data, model, and its decisions.

Citation
M. Islam, D. T. Anderson, A. J. Pinar, T. C. Havens, G. Scott and J. M. Keller, “Enabling Explainable Fusion in Deep Learning With Fuzzy Integral Neural Networks,” in IEEE Transactions on Fuzzy Systems, vol. 28, no. 7, pp. 1291-1300, July 2020, doi: 10.1109/TFUZZ.2019.2917124.

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Tim Havens Gives Talk at Los Alamos National Lab

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Dr. Timothy Havens presented the lead talk at the Los Alamos National Laboratory’s ISR-2 Seminar Series on Advancing Toward Modern Detection and Estimation Techniques for Multi-Sensor Scenarios, presented online July 9, 2020.

Tim Havens is associate dean for research for the College of Computing, director of the Institute of Computing and Cybersystems (ICC), and the William and Gloria Jackson Associate Professor of Computer Systems.

The talk, “Explainable Deep Fusion,” described Havens’s sensor fusion systems research that seeks to combine cooperative and complementary sources to achieve optimal inference from pooled evidence.

Havens specifically discussed his innovations in non-linear aggregation learning with Choquet integrals and their applications in deep learning and Explainable AI.

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