Category: Announcements

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 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.

Play – 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. Keith Vertanen 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!

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.

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.

The Strategic Faculty Hiring Initiative (SFHI) candidates affected by this change are:

Briana Bettin, March 16-17, 2020 | View blog post
Zoom Meeting: https://michigantech.zoom.us/j/468935183

Leo Ureel, March 24-26 | View blog post
Zoom Meeting: https://michigantech.zoom.us/j/696407720

The Computer Science faculty candidates affected by this change are:

Junqiao Qiu, March 30-31, 2020 | View blog post
Zoom Meeting: https://michigantech.zoom.us/j/842795573

Teseo Schneider, March 23-24  | View blog post
Zoom Meeting: https://michigantech.zoom.us/j/519255087

Vidhyashree Nagaraju, March 20-21 | View blog post
Zoom Meeting: https://michigantech.zoom.us/j/636248962

Please note, two faculty candidates who requested that their time on campus not be publicized on this blog are not included here. Please contact Vicky Roy, director of administration, if you have questions about these candidates.

Instructions on how to use Zoom can be found here.

More information about Michigan Tech’s response to COVID-2019 can be found here.

Michigan Tech students are urged to register for summer 2020 Computing classes as soon as possible. Any course that does not have an enrollment of at least 5 students by April 17, 2020, may be canceled and not offered this summer. The classes are listed below.

Access the Summer 2020 full schedule of classes through the Registrar’s website: https://www.mtu.edu/registrar/. Please visit with an advisor if you have questions about what classes to take.

CS 1121 | Intro to Programming I
3 Credits | 05/11-06/25 | Instructed by: TBA

CS 1122 | Intro to Programming II
0-3 Credits | 05/11-06/25 | Instructed by: Pomerville 

CS 1142 | Programming at HW/SW Interface
3 Credits | 05/11-06/25 | Instructed by: Vertanen 

CS 4461 | Computer Networks
3 Credits | 05/11-06/25 | Instructed by: Jalooli 

CS 4710 | Model-Driven Software Development
3 Credits | 06/29-08/13 | Instructed by: Ebnenasir 

CS 4821 | Data Mining
3 Credits | 05/11-06/25 | Instructed by: Kakula 

EET 2233 | Electrical Machinery
4 Credits | 05/11-06/25 | Instructed by: Sergeyev 

EET 3373 | Intro to Prog Controllers
3 Credits | 05/11-06/25 | Instructed by: Sergeyev 

EET 4144 | Real-Time Robotics Systems
4 Credits | 05/04-05/15 | Instructed by: Sergeyev  

EET 4147 | Industrial Robotic Vision Syst
4 Credits | 06/29-08/13 | Instructed by: Sergeyev 

EET 4460 | Senior Project I
3 Credits | 05/11-08/13 | Instructed by: TBA

EET 4480 | Senior Project II
3 Credits | 05/11-08/13 | Instructed by: TBA

EET 5144 | Real-Time Robotics Systems
4 Credits | 05/04-05/15 | Instructed by: Sergeyev 

EET 5147 | Industrial Robotic Vision Syst
4 Credits | 06/29-08/13 | Instructed by: Sergeyev 

SAT 2343 | Network Administration I
4 Credits | 05/11-06/25 | Instructed by: TBA 

SAT 2511 | Microsoft System Administration
4 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 2711 | Linux System Administration
4 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3310 | Scripting Administration & Automation
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3611 | Infrastructure Service Administration
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3812 | Cyber Security I
3 Credits | 05/11-06/25 | Instructed by: Cai 

SAT 3820 | Wireless System Administration
4 Credits | 05/11-06/25 | Instructed by: TBA

SAT 4480 | Senior Project I
3 Credits | 05/11-08/13 | Instructed by: TBA

SAT 4812 | Cyber Security II
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 4816 | Digital Forensics
3 Credits | 05/11-06/25 | Instructed by: TBA

SAT 4880 | Senior Project II
3 Credits | 05/11-08/13 | Instructed by: TBA

SAT 4996 | Big Data: Tools & Techniques
3 Credits | 06/29-08/13 | Instructed by: Tang 

SAT 5990 | Big Data: Tools & Techniques
3 Credits | 06/29-08/13 | Instructed by: Tang 

SAT 5998 | Experience in Med Informatics
3 Credits | 06/29-08/13 | Instructed by: TBA

Tim Havens, associate dean for research, College of Computing, and director of the Institute of Computing and Cybersystems, was quoted in the article, “Data science vs. machine learning: What’s the difference?” published March 10, 2020, in the online publication, The Enterprisers Project.

Havens’s quotation concerns machine learning models, which the article explains are only as good as the quality of the data they learn from. Havens says, “Luckily, there are many types of problems for which lots of data exist.”

Link to the article here.

The Enterprisers Project is a community and online publication built to discuss the evolving role of the CIO and how IT leaders drive business value in a digital world. It is a collaborative effort between Harvard Business Review and Red Hat that delivers daily analysis and advice on topics ranging from emerging technologies to IT talent. Articles in the publication are written by CIOs, for CIOs and other IT executives, who share lessons learned from innovating in true partnership with the business. 

The Michigan Tech Provost has issued guidance that due to MTU’s new COVID-19 policy, all university learning centers must remain closed to physical sessions.

The College of Computing Learning Center will be available online and staffed by undergraduate coaches according to the Spring 2020 schedule (https://www.mtu.edu/computing/labs-facilities/cclc/).

We will maintain our online presence in two ways:

1. Zoom. We will use the following Zoom meeting as a landing point for students seeking help from Learning Center coaches: https://michigantech.zoom.us/j/654452233. In this space, coaches will assess a student’s needs and either provide quick pointers or invite the student(s) into a Zoom meeting room for more targeted tutoring.

2. Canvas. We are setting up a special Canvas page where we can share information with students. We plan on posting short tutorials and quizzes to help students review topics required for their courses. If you have information you would like posted on our Canvas page, please send it to myself or Bonnie Henderson (bhenders@mtu.edu).

Students can self-enroll in the CCLC Canvas page here: https://mtu.instructure.com/enroll/KWFTJ9

After that, link directly to the CCLC Canvas page here: https://mtu.instructure.com/courses/1265465

The CCLC coaches are looking forward to helping the campus community in new ways during this challenging time. Please be patient as we get things up and running.

Please direct questions to Leo Ureel (ureel@mtu.edu) or Bonnie Henderson (bhenders@mtu.edu).

Undergraduate researchers and scholars from all colleges—first-year students to soon-to-graduate seniors—will present a record 76 posters at the 2020 Undergraduate Research Symposium, Friday, March 27, 2020, in the lobby of the Rozsa Center. Two sessions will take place, from 11:00 a.m. to 1:00 p.m., and from 2:00 to 4:00 p.m.

The Symposium, hosted by the Pavlis Honors College, highlights the amazing cutting-edge research being conducted on Michigan Tech’s campus by some of our best and brightest undergraduate students.

All faculty, staff and students are encourage to attend and support our excellent undergraduate researchers. Faculty members who would like to serve as distinguished judges at this year’s symposium may complete this short form. 

Learn more about the Symposium here.

The College of Computing invites the campus community to a lecture by faculty candidate Teseo Schneider on Monday, March 23, 2020, at 3:00 p.m. The title of Schneider’s lecture is, “Robust Black-box Analysis.”

Link to the online Zoom meeting here.

Schneider is an assistant professor and faculty fellow in computer science at the Courant Institute of Mathematical Sciences at New York University. He holds a Ph.D. in computer science from the Universita della Svizzera Italiana (2017). His research interests are in finite element simulations, mathematics, discrete differential geometry, and geometry processing. 

Numerical solutions of partial differential equations (PDEs) are ubiquitous in many different applications, ranging from simulations of elastic deformations for manufacturing to flow simulations to reduce drag in airplanes, and to organs’ physiology simulations to anticipate and prevent diseases.

The finite element method (FEM) is the most commonly used discretization of PDEs due to its generality and rich selection of off-the-shelf commercial implementations. Ideally, a PDE solver should be a “black-box”: the user provides as input the domain’s boundary, the boundary conditions, and the governing equations, and the code returns an evaluator that can compute the value of the solution at any point of the input domain. This is surprisingly far from being the case for all existing open-source or commercial software, despite the many research efforts in this direction and the sustained interest from academia and industry.

To a large extent, this issues from treating meshing (and geometry more in general) and FEM basis construction as two disjoint problems. The FEM basis construction may make a seemingly innocuous assumption (e.g., on the geometry of elements), leading to exceedingly difficult requirements for meshing software.

This state of matters presents a fundamental problem for all applications, and is even more problematic in applications that require fully automatic, robust processing of large collections of meshes of varying sizes, which have become increasingly common as large collections of geometric data become available. Most importantly, this situation arises in the context of machine learning on geometric and physical data, where one needs to run large numbers of simulations to learn from, as well as solve problems of shape optimization, which require solving PDEs in the inner optimization loop on a constantly changing domain.

Schneider’s research presents recent advancements towards an integrated pipeline, considering meshing and element design as a unique challenge, leading thus to a black-box pipeline that can solve simulations on 10,000 in the wild meshes, without any parameter tuning.

Schneider earned a Postdoc.Mobility fellowship from the Swiss National Science Foundation (SNSF) to pursue his research aiming to bridge physical simulations and geometry.Teseo is also the main developer of Polyfem (https://polyfem.github.io/), a flexible and easy to use Finite Element Library. He is one of the maintainers of libigl (https://github.com/libigl/libigl), and a contributor to wild meshing (https://github.com/wildmeshing), a 2D and 3D robust meshing library.