Faculty Candidate Muhammad Fahad to Present Lecture April 9

The College of Computing’s Department of Applied Computing invites the campus community to a lecture by MERET faculty candidate Muhammad Fahad on Thursday, April 9, 2020, at 3:30 p.m., via an online Zoom meeting. His talk is titled, “Motion Planning and Control of Autonomous Mobile using Model Free Method.”

Link to the Zoom meeting here.

Dr. Fahad currently works as a robotics engineer at National Oil Well Varco. He received his M.S. and Ph.D. in electrical engineering from Stevens Institute of Technology, Hoboken, NJ, and his B.S in EE at University of Engineering and Technology, Lahore, Pakistan.

Fahad has extensive experience designing control and automation systems for the process industry using traditional control methods and robots. His research interests include cooperative distributed localization, human robot interaction (HRI), deep reinforcement learning (DRL), deep inverse reinforcement learning (DIRL) and generative adversarial imitation learning (GAIL), simulation tools design, parallel simulation frameworks and multi-agent learning.

Lecture Abstract. Robots are playing an increasingly important part in our daily lives. This increasing involvement of robots in our everyday lives has highlighted the importance of human-robot interaction, specifically, robot navigation of environments occupied by humans, such as offices, malls and airports. Navigation in complex environments is an important research topic in robotics.

The human motion model consists of several complex behaviors that are difficult to capture using analytical models. Existing analytical models, such as the social force model, although commonly used, are unable to generate realistic human motion and do not fully capture behaviors exhibited by humans. These models are also dependent on various parameters that are required to be identified and customized for each new simulation environment. 

Artificial intelligence has received booming research interest in recent years. Solving problems that are easy for people to perform but difficult to describe formally is one of the main challenges for artificial intelligence. The human navigation problem falls directly in this category, where it is hard to define a universal set of rules to navigate in an environment with other humans and static obstacles.

Reinforcement learning has been used to learn model-free navigation, but it requires a reward function that captures the behaviors intended to be inculcated in the learned navigation policy. Designing such a reward function for human like navigation is not possible due to complex nature of human navigation behaviors. The speaker proposes to use measured human trajectories to learn both the reward function and navigation policy that drives the human behavior.

Using a database of real-world human trajectories–collected over a period of 90 days inside a mall–we have developed a deep inverse reinforcement learning approach that learns the reward function capturing human motion behaviors. Further, this dataset was visualized in a robot simulator to generate 3D sensor measurement using a simulated LIDAR sensor onboard the robot. A generative adversarial imitation learning based method is developed to learn the human navigation policy using these human trajectories as expert demonstration. The learned navigation policy is shown to be able to replicate human trajectories both quantitatively, for similarity in traversed trajectories, and qualitatively, in the ability to capture complex human navigation behaviors. These navigation behaviors include leader follower behavior, collision avoidance behavior, and group behavior. 


Stay Home. Stay Safe. Stay in Touch.

Dear College of Computing Students, Families, and Friends:

In all our daily tasks and interactions, Michigan Tech and the College of Computing remain closely focused on delivering to you the best possible educational experience; we are also mindful of your over-all health and well being. We wish to do as much as we possibly can to help you successfully complete this semester, and guide and support you on your way to finishing your degree.

We’ve compiled some of the many University and community resources available to you below. All kinds of help and support is out there, and everyone is eager to assist in this uncertain time.

You are invited to contact Dean Minerick, and any of us in Computing and across campus, with your questions and concerns, large or small.

Academic Leadership
Adrienne Minerick, Dean: minerick@mtu.edu
Dan Fuhrmann, Director, MERET/CMH/Applied Computing: fuhrmann@mtu.edu
Linda Ott, Chair, Computer Science: linda@mtu.edu

Undergraduate Academic Advisors
Denise and Kay, The College of Computing’s academic advisors, are on duty and available by email, phone, and Zoom.
Denise Landsberg, Computer Science, Software Engineering: dllandsb@mtu.edu
Kay Oliver, CNSA, Cybersecurity, EET, Mechatronics, Health Informatics: koliver@mtu.edu
Advising Website:

Faculty and Staff
We hope that you always feel welcome to contact your instructors and mentors with questions, concerns, and help with an assignment. We are all standing by to help you successfully complete this semester, prepare for summer and fall classes, and get ready for for spring graduation.
Find all the Computing faculty here. Find the Computing staff here.

Finally, Michigan Tech and the College of Computing are continually populating and updating our websites and blogs with the latest news.

A few more links:

Get the latest information and updates regarding Michigan Tech’s response to COVID-19 at mtu.edu/covid-19. View updates to this alert.

Meal Packets are available 24 hours a day, 7 days a week at Public Safety and Police Services.

The Dean of Students Office has compiled a comprehensive list of emergency resources for students.

Students who are experiencing unforeseen financial emergencies can apply for assistance.


Leo Ureel Is this Week’s Deans’ Teaching Showcase Selection

Dean Adrienne Minerick and the College of Computing are pleased to announce that Leo Ureel, Computer Science Lecturer and Ph.D. student, is this week’s Deans’ Teaching Showcase. Leo is also coordinator of the College of Computing Learning Center (CCLC) in Rekhi Hall and faculty advisor to the Computer Science Learning Committee in McNair Hall. 

Most notable among his accomplishments, Ureel’s student-centric efforts are increasing retention and diversifying the cohort of first-year Computing students. Further, his work, in coordination with many other valuable members of the College of Computing, has increased the visibility of Michigan Tech and the College of Computing, both on campus and in the community, and contributed substantially to sustained enrollments in Computer Science and other College of Computing programs.

“What becomes apparent immediately when thinking about Leo’s contributions is how much Leo cares about and invests into his student’s learning,” says Dean Minerick. “Student success is at the heart of all that he does.”  

Ureel’s work has provided him the opportunity to develop rich collaborations with researchers across the U.S. and in the U.K., Europe, and Africa, and he recently led an ITICSE working group of international researchers examining first year student experiences in CS. 

Ureel teaches CS 1121 and CS 1122 courses, primarily to first year students, in which he works to broaden students’ views of computing, ground them in a programming language, and teach them problem solving skills. His research has been supported by NSF, Google, and NCWIT. 

Ureel’s nomination emphasizes in particular his innovative and effective teaching of the entry-level programming classes in Computer Science, for which Ureel has developed a WebTA tool that gives students near real-time feedback on their programming code. 

“My classrooms are hands-on learning environments where I combine small hands-on projects with blended learning techniques to engage students and provide individual feedback” Ureel explains. “I’ve developed a software system, WebTA, that provides students with individualized feedback on their code while they are working on it – even when I am personally unavailable. (For example, at 2:00 a.m. when students are working on their programming assignments!)” 

“This engages students in the following programming practice: design, code, receive feedback, reflect, and repeat. The more I can engage the students in these tight cycles of programming and reflection, the better they learn to program.” 

Ureel’s adds that his research efforts focus on a constructionist approach to introductory computer science that leverages code critiquers to motivate students to learn computer programming. The critiquer systems engage students in test-driven agile development methods through small cycles of teaching, coding integrated with testing, and immediate feedback. 

This interest in student success was one component of Ureel’s close collaboration with Linda Ott, chair of the Computer Science department, in a project funded by the National Center for Women and Information Technology (NCWIT). As part of the collaboration focused on first-year student retention, a structure was developed to more effectively place students in their first programming course. 

“By improving the placement of students based on their previous programming experience, both students new to programming and those with experience are more satisfied and more successful in their first programming course at Michigan Tech” according to Dr. Ott. “Leo is constantly thinking about ways to engage students in programming”. 

Ureel is also part of a student and faculty team that regularly hosts community outreach and workshops for middle and high school students like Code Ninjas, Copper Country Coders, and numerous other programs. 

“My work with K-12 outreach activities, such as Code Ninjas and Copper Country Coders, benefits both the K-12 students, who are learning to program, and Michigan Tech undergraduate students, who volunteer as K-12 mentors,” Ureel says. “The undergraduate students benefit from the teaching process; learning more about computer science as they 

strive to articulate basic computer principles in simple language and entertaining memes for the K-12 students.” 

Ureel’s success teaching students with no coding experience also sparked the pilot of a foundational computing course for non-majors at Michigan Tech. Ureel was the key thought leader driving course structure and content for CS 1090, Computational Thinking, a course for non-Computing majors that teaches computing fundamentals using the Python language. 

“I am teaching the course in the context of several problem domains, including Big Data, Machine Learning, Image Processing, Simulation, and Video Game Design,” Ureel says. “As students tackle problems in these domains, I introduce the Python language structures required to construct a solution. Teaching programming in the context of larger problem domains gives students a way to ground their learning in practical applications.” 

The course, which could help instill computational thinking across campus, is being piloted this semester with students from outside the College of Computing. Designed to be compatible with the College Board AP Computer Science Principles course, the CS 1090 pilot is expected to be expanded through IDEA Hub continuation efforts. 

Ureel also leads the College of Computing Learning Center (CCLC), which has pivoted in a couple of ways over the last year, in step with the College of Computing. A cadre of 20 outstanding student coaches from both the Computer Science and Computer Network and System Administration majors have transformed the CCLC into an inclusive learning hub for all CC majors and courses, with students from across campus seeking out the CCLC. The number of students utilizing CCLC services has increased steadily over the past few years. 

Ureel also worked closely with Dr. Nilufer Onder (CS) to incorporate into CCLC services an upper-level Student Academic Mentors (SAM) program that Dr. Onder developed and spearheaded in Computer Science courses. Their vision is to expand the SAM program under the umbrella of the CCLC, increasing access and courses supported. 

And finally, in response to the recent COVID-19 pandemic, Ureel and his coaches have creatively and effectively coordinated the transition of CCLC services to an online format. 


Faculty / Researcher Profile: Weihua Zhou

Faculty/Researcher Profile: Weihua Zhou, Multi-Disciplinary Digital Healthcare Solutions

By Karen Johnson, Communications Director, College of Computing and Institute of Computing and Cybersystems

How can the cost-effectiveness of healthcare be improved, especially for complicated chronic diseases? This is the overarching question Dr. Weihua Zhou is seeking to answer with his research. The multi-disciplinary solutions he is investigating merge the fields of medical imaging and informatics, computer vision, and machine learning. 

An assistant professor in Michigan Tech’s Health Informatics program, and an affiliated associate professor in the Biomedical Engineering department, Zhou is working with students on a number of research projects in Michigan Tech’s Medical Imaging and Informatics Lab, which he directs. He is a member of the Institute of Computing and Cybersystems’s Center for Data Science.

Zhou says his research is driven by clinical significance, and he is especially interested in developing practical solutions to improve the cost-effectiveness of treating complicated chronic diseases, such as coronary artery disease, heart failure and senile dementia. 

He is excited about his career, his international research, and his work at Michigan Tech. “We have a very productive team, including dedicated Ph.D. students, self-motivated graduate and undergraduate students, and a lot of experienced clinical and technical collaborators,” he says of his colleagues and collaborators at Michigan Tech and around the world.

Zhou feels that he can be dedicated to both his research and teaching at Michigan Tech. “I joined the Health Informatics program at Michigan Tech, both because health informatics is my research focus, and because Michigan Tech’s leading reputation among engineering schools opens opportunities to find new and respected technical collaborators. 

Zhou often calls himself a salesman. “I sell techniques to our clinical collaborators and ask them to design the projects with me, provide the patient data, and test our tools,” he explains. “I also sell my ideas about clinical problems to technical collaborators and ask them to work with us to solve the important clinical problems.”

And when he communicates with his Ph.D. students, “sometimes I also consider them as my buyers and let them appreciate my ideas so that they can be really inspired.”

Primary Research

Zhou identifies two of his research projects of as primary. 

“This first is exploring image-guided approaches to improving the treatment of heart failure, which has been supported by AHA grants, and is now being supported by a new faculty startup grant,” Zhou says. “The second main project is seeking to employ machine learning to improve the risk stratification for osteoporosis, which is supported by a National Institutes of Health (NIH) subcontract award from Tulane University.”

On the NIH grant, awarded in December 2019, Zhou is working with internationally renowned researcher and educator Dr. Hong-Wen Deng, an endowed chair and professor in the School of Public Health and Tropical Diseases at Tulane University, New Orleans, La. Zhou and Deng are studying trans-omics integration of multi-omics studies for male osteoporosis.

Zhou is also co-PI with Jinshan Tang, professor of Applied Computing (eff. 7/1/20) at Michigan Tech, on a Portage Health Foundation Infrastructure Enhancement Grants titled, “High Performance Graphics Processing Units.” The project is focused on building big data computing capabilities toward advancing research and education. Several additional proposals are under review and revision. Zhou’s past research support includes an American Heart Association award, which studied a new image-guided approach for cardiac resynchronization therapy.

Teaching and Mentoring

Zhou, who started at Michigan Tech in fall 2019, instructed Introduction to Health Informatics in the fall semester, and Applied Artificial Intelligence in Health this spring.  He says that in the Medical Informatics program, the subjects he teaches are very practical.

“I believe the following strategies are very important and I practice them in my classes every day: 1) Make the class interactive; 2) Make the assignments and projects practical; 3) Emphasize the learning process; and 4) Keep the teaching materials up to date,” Zhou says.

Zhou supervises two Ph.D. candidates in the Department of Applied Computing, and a Health Informatics master’s student.

Applied Computing Ph.D. candidate Zhuo He’s primary research project concerns information fusion between electrical signal propagation and mechanical motion to improve the treatment of heart failure. Ph.D. candidate Chen Zhao’s primary research concerns using image fusion and computer vision to improve interventional cardiology. And Zhou’s Health Informatics master’s student, Rukayat Adeosun, is studying nuclear image-guided approaches to improving cardiac resynchronization therapy.

Education and Post-Doc

Zhou was awarded his Ph.D. in computer engineering by the Department of Electrical and Computer Engineering at Southern Illinois University Carbondale in 2012; his dissertation is titled, “Image reconstruction and imaging configuration optimization with a novel nanotechnology enabled breast tomosynthesis multi-beam X-ray system.”

Following, Zhou was a post-doctoral researcher in the Department of Radiology and Imaging Sciences at Emory University, Atlanta, Georgia, then he was appointed a Nina Bell Suggs Endowed Professor at University of Southern Mississippi, where he was a tenure-track assistant professor. Zhou also completed an MSc.-Ph.D. in computer science (2007) and a B.E. in computer science and technology (2003), both at Wuhan University, China.

Achievement

Zhou received the USM College of Arts and Sciences Scholarly Research Award in March 2019, participated in the AHA Research Leaders Academy of the American Heart Association in September 2017 and August 2018, and received the USM Butch Oustalet Distinguished Professorship Research Award in April 2018.

University and Professional Service

Zhou serves on Michigan Tech’s Review Committee for Graduate Dean’s Awards Advisory Committee, and in October 2019 he served on the Review Committee for Research Excellence Fund (REF) – Research Seed Grants (RS).

He was an invited speaker at the Machine Learning in SPECT MPI Applications session at the Annual Scientific Session of the American Society of Nuclear Cardiology in Washington, D.C., in 2009.

Zhou is a member of the American Heart Association (AHA) and the American Society of Nuclear Cardiology (ASNC).

Peer-Review

Since Zhou joined Michigan Tech in August 2019, he has published five scholarly papers, in Journal of Nuclear Cardiology and the IEEE Journal of Translational Engineering in Health and Medicine. Two additional articles are under revision with Journal of Nuclear Cardiology and the journal Medical Physics, and one is under review by the Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference 2020.

Since 2007, he has published more than 80 peer-reviewed journal and conference papers and book chapters in publications including JACC: Journal of The American College of Cardiology: Cardiovascular Imaging, Journal of Nuclear Cardiology, and IEEE Journal of Translational Engineering in Health and Medicine.

Zhou is a translator of featured papers and abstracts for the Journal of Nuclear Cardiology, and a paper reviewer for the Journal of Nuclear Cardiology, JACC: Journal of The American College of Cardiology, and JACC: Cardiovascular Imaging. He is a reviewer for American Heart Association data science grants. 

Commercial Success

Zhou holds a number of patents and invention disclosures, including new methods to 1) diagnose apical hypertrophic cardiomyopathy from gated single-photon emission computed tomography (SPECT), and 2) measure right-ventricular and interventricular mechanical dyssynchrony from gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI); and 3) the integration of fluoroscopy venogram and myocardial perfusion SPECT image with left-ventricular contraction sequence and scar distribution to guide the real-time surgery of cardiac resynchronization therapy. 

He and his colleagues have developed a number of software tools, some of which are being used in hospitals for research purposes, and he believes that the tools can be successfully validated and become commercially available. For example, Zhou’s nuclear image-guided software toolkit to improve cardiac resynchronization therapy is being validated by a large clinical trial. 

A personal note.

Zhou loves independent thinking, facts and exact numbers, and he values persistence, all of which express themselves in his teaching and research, and his life.

Follow Weihua Zhou on Twitter: @LabMiil

The College of Computing Department of Applied Computing will officially replace the CMH Division effective July 1, 2020.


Faculty Candidate Kahlid Miah to Present Lecture April 3

The College of Computing’s Department of Applied Computing invites the campus community to a lecture by faculty candidate Kahlid Miah on Friday, April 3, 2020, at 3:30 p.m., via an online Zoom meeting. The title of Miah’s lecture is, “Fiber-Optic Distributed Sensing Technology: Applications and Challenges.”

Link to the Zoom meeting here.

Dr. Miah is currently a visiting faculty member in the ECE department at Indiana University – Purdue University Indianapolis (IUPUI). He received his Ph.D. and M.S. in electrical engineering from University of Texas at Austin, and a B.S. in aerospace engineering, also from Indiana University. His research interests are in computational geophysics, signal and image processing, instrumentation, and fiber-optic distributed sensing system development.

Lecture Abstract: In distributed fiber-optic sensing systems, a fiber-optic cable itself acts as an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial resolution over a long sensing distance. There are many applications, especially in geophysical, geotechnical, and mining engineering where simultaneous multiparameter measurements are essential. Data deluge, difficulty in multicomponent measurements, and poor sensor-medium coupling are key challenges, and thus provide opportunities for future research and development.  

Dr. Miah’s past teaching and research experience includes a faculty position in the Geophysical Engineering department at Montana Technological University. He has held a postdoctoral research position at University of Alberta and a visiting fellowship position at the Geological Survey of Canada. He has also worked as a process engineer for a semiconductor equipment manufacturer in Austin, Tex.

Note: The College of Computing Department of Applied Computing is a new administrative unit replacing the CMH Division; its official start date is July 1, 2020. Applied Computing academic programs include Computer Network and System Administration (CNSA), Cybersecurity, Electrical Engineering Technology (EET), Health Informatics, and Mechatronics.


ROTC Cybersecurity Training for Tomorrow’s Officers

The U.S. Department of Defense, Office of Naval Research, has awarded Michigan Tech faculty researchers a $249,000 grant that supports the creation of an ROTC undergraduate science and engineering research program at Michigan Tech. The primary goal of the program is to supply prepared cadets to all military branches to serve as officers in Cyber commands.

The principal investigator (PI) of the project is Andrew Barnard, Mechanical Engineering-Engineering Mechanics. Co-PIs are Timothy Havens, College of Computing; Laura Brown , Computer Science, and Yu Cai, Applied Computing. The title of the project is, “Defending the Nation’s Digital Frontier: Cybersecurity Training for Tomorrow’s Officers.”

The curriculum will be developed over the summer, and instruction associated with the award will begin in the fall 2020 semester. Cadets interested in joining the new program are urged to contact Andrew Barnard.

Initially, the program will focus on topics in cybersecurity, machine learning and artificial intelligence, data science, and remote sensing systems, all critical to the The Naval Science and Technology (S&T) Strategic Plan and the Navy’s Force of the Future, and with equal relevance in all branches of the armed forces.

The plan of work focuses on on engaging ROTC students in current and on-going Cyber research, and supports recruitment of young ROTC engineers and scientists to serve in Navy cybersecurity and cyber-systems commands. The program will compel cadets to seek positions within Cyber commands upon graduation, or pursue graduate research in Cyber fields.

“Our approach develops paid, research-based instruction for ROTC students through the existing Michigan Tech Strategic Education Naval Systems Experiences (SENSE) program,” said principal investigator Andrew Barnard, “ROTC students will receive one academic year of instruction in four Cyber domains: cybersecurity, machine learning and artificial intelligence (ML/AI), data science, and remote sensing systems.”

Barnard says the cohort-based program will enrich student learning through deep shared research experiences. He says the program will be designed with flexibility and agility in mind to quickly adapt to new and emerging Navy science and technology needs in the Cyber domain.

Placement of officers in Cyber commands is of critical long-term importance to the Navy (and other DoD branches) in maintaining technological superiority, says the award abstract, noting that technological superiority directly influences the capability and safety of the warfighter.

Also closely involved in the project are Michigan Tech Air Force and Army ROTC officers Lt. Col. John O’Kane and LTC Christian Thompson, respectively.

“Unfortunately, many ROTC cadets are either unaware of Cyber related careers, or are unprepared for problems facing Cyber officers,” said Lt. Col. O’Kane. “This proposal aims to provide a steady flow of highly motivated and trained uniformed officers to the armed-services, capable of supporting the warfighter on day-one.”

Andrew Barnard is director of Michigan Tech’s Great Lakes Research Center, an associate professor of Mechanical Engineering-Engineering Mechanics, and faculty advisor to the SENSE Enterprise.

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

Laura Brown is an associate professor, Computer Science, director of the Data Science graduate program, and a member of the ICC’s Center for Data Sciences.

Yu Cai is a professor of Applied Computing, an affiliated professor of Computational Science and Engineering, a member of the ICC’s Center for Cybersecurity, and faculty advisor for the Red Team, which competes in the National Cyber League (NCL).

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.

The Army and Air Force have active ROTC programs on Michigan Tech’s campus.

The Office of Naval Research (ONR) coordinates, executes, and promotes the science and technology programs of the United States Navy and Marine Corps.


Welcome to Spring 2020 Preview Day!

Welcome prospective students and friends and families! The Michigan Tech College of Computing is pleased to welcome you to Spring 2020 Preview Day.

Since you’re at home instead of on campus, we’ve prepared a special video to share with you today. Well, actually our academic advisor Kay Oliver produced the video. Thanks, Kay! (Scroll down to play the video.)

In the video, Kay will tell you about our undergraduate and graduate degree programs, and show you lots of photos of Michigan Tech students, faculty, labs, and classrooms.

Kay, along with Denise Landsberg, our second academic advisor, are standing by to answer your questions. You can email Kay and Denise at csadvisor@mtu.edu.

Please read more below the video.

College of Computing Preview Day: Spring 2020

On the virtual tour, you’ll also hear from Dr. Linda Ott, chair of the Computer Science department, who’ll fill you in on the Computer Science and Software Engineering degree programs, concentrations, and minors and go over some of the first-year Computing courses.

And you’ll learn a little bit about our Applied Computing degrees:

Computer Network and System Administration (CNSA)
Cybersecurity
Electrical Engineering Technology (EET)
Mechatronics

And if you’re still exploring which Computing degree is the right one for you, check out our General Computing major, which gives you a little time and space to make this important decision.

Finally, Computer Science prof Dr. Chuck Wallace will tell you about Michigan Tech’s unique student Enterprise program, where Computing students are working on real computing solutions for real clients. The Computing-focused student Enterprises are:

Husky Games
HIDE (Human Interface Development Enterprise)
IT Oxygen Enterprise.

Please enjoy the video. Contact us anytime with your questions, large or small, and be sure to visit our website (mtu.edu/computing), our news blog, and visit, share, connect, and like us on social media.

We hope to see you on campus this fall!


Article by Tim Havens in IEEE Transactions on Fuzzy Systems

An article co-authored by Tim Havens, associate dean for research, College off Computing, “Soft Overlapping Community Detection in Large-Scale Networks via Fast Fuzzy Modularity Maximization,” was published in the March 2020 issue of IEEE Transactions on Fuzzy Systems.

Havens’s co-authors are Audrey Yazdanparast (ECE) and Mohsen Jamalabdollahi of Cisco Systems.

Article Abstract: Soft overlapping clustering is one of the notable problems of community detection. Extensive research has been conducted to develop efficient methods for non-overlapping and crisp-overlapping community detection in large-scale networks. In this paper, Fast Fuzzy Modularity Maximization (FFMM) for soft overlapping community detection is proposed.

FFMM exploits novel iterative equations to calculate the modularity gain associated with changing the fuzzy membership values of network vertices. The simplicity of the proposed scheme enables efficient modifications, reducing computational complexity to a linear function of the network size and the number of communities. Moreover, to further reduce the complexity of FFMM for very large networks, Multi-cycle FFMM (McFFMM) is proposed.

The proposed McFFMM reduces complexity by breaking networks into multiple sub-networks and applying FFMM to detect their communities. Performance of the proposed techniques are demonstrated with real-world data and the Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks. Moreover, the performance of the proposed techniques is eval- uated versus some state-of-the-art soft overlapping community detection approaches. Results show that the McFFMM produces a remarkable performance in terms of overlapping modularity with fuzzy memberships, computational time, number of detected overlapping nodes, and Overlapping Normalized Mutual Informa- tion (ONMI).

View more info here.


Todd Arney Receives Elite New Teaching Award

The Office of the Provost and the William G. Jackson Center for Teaching and Learning have announced that Todd Arney, lecturer in the College of Computing’s Department of Applied Computing, is one of four instructors who will receive The Provost’s Award for Sustained Teaching Excellence, a new teaching award that celebrates the work of individuals whose teaching consistently and dramatically benefits students.

Had this been a normal year, Arney would have again qualified as a finalist for the annual Distinguished Teaching Award, which he has been awarded three times. But because this was Arney’s fourth nomination, the Provost, academic deans, and the Center for Teaching and Learning agreed that Arney deserves special recognition that goes beyond consideration as a finalist.

Provost Huntoon, in collaboration with the Academic Deans, initiated this award because “It became clear that we had a group of instructors consistently delivering exceptional instruction to their students over many years, who are worthy of special recognition,” said a March 18, 2020, Tech Today news item.

“The intent in establishing this new award is to acknowledge that anyone named a finalist more than three times has been consistently exceptional,” wrote Michael Meyer, director of the William G. Jackson Center for Teaching and Learning, in Arney’s award letter. “Your commitment to excellence is worthy of significant recognition.”

The award, which consists of a plaque and $1000 in additional compensation, will be presented at the Academy of Teaching Excellence banquet on April 14, 2020. Each of the recipients of the new award will continue to be honored on an annual basis as members of Michigan Tech’s Distinguished Teaching Academy, an elite group with an established reputation for excellent teaching.

Arney is a lecturer in the Computer Network and System Administration (CNSA) program, Applied Computing. He teaches courses in Linux system administration, Microsoft system administration, infrastructure system administration, scripting administration and automation, data center engineering, cybersecurity, and cyber ethics.  In addition, he supervises CNSA Senior Design projects. He was also nominated for the Dean’s Teaching Award in spring 2019.  

“Todd’s energy and his rapport with the students creates a community within CNSA that promotes student success,” said Adrienne Minerick, dean of the College of Computing. “He is accessible and dedicated to the students, always encouraging them to try projects that lie outside of their comfort zones.”

“I am delighted, but not 100% surprised, that Todd Arney was selected as one of the inaugural recipients for this award,” said Dan Fuhrmann, chair of the Applied Computing department. “‘Sustained teaching excellence’ is a perfect description of Todd’s contributions to the CNSA program.  Our students are his number one priority, and in return he is respected and well-liked by his students. Todd represents the very best that Michigan Tech offers in undergraduate education.”

“I am very pleased to be part this award’s initiation, and to be associated with a place where there’s so much good instruction going on that we need to expand the ways we recognize people,” wrote Meyer. “Your [Arney’s] efforts motivated the creation of this award, and that alone is an outstanding professional accomplishment! On behalf of the students, staff, and faculty at Michigan Tech, I offer my sincerest congratulations and appreciation to you for your dedicated efforts and willingness to go the extra mile to connect with your students.”

As is the case for those that have won the Distinguished Teaching Award, recipients of the Provost’s Award for Sustained Teaching Excellence are members of an elite group with an established reputation for teaching excellence. Recipients of the new Provost’s award are ineligible to be named as a finalist in the future, but membership in the elite group is permanent.

Finalists for the 2020 teaching awards were selected based on the spring and fall 2019 semester teaching evaluations.