Category: Events

To help faculty prepare for Flex Fall, IDEA Hub and the William G. Jackson Center for Teaching and Learning have organized a series of events, each including Flex Fall Q&A sessions and discussions about teaching.

Click the below links to register and receive a Google calendar invitation and the Zoom link. Questions? Email margaret@mtu.edu.

Session #2: Wednesday, June 17, 3:00 – 4:30 pm. Online Teaching Showcase
Teaching, Q&A: 3 – 3:30 pm; Teaching Showcase, Discussion: 3:30-4:30 pm)

Session #3, Wednesday, June 24, 3-5 pm: Develop Innovative Solutions
(Teaching, Q&A: 3 – 3:30 pm, Design Thinking Workshop: Develop Innovative Solutions: 3:30 – 5 pm)

Session #4: Wednesday, July 1, 3 to 5 pm: Prototype Your Innovative Solutions
(Teaching, Q&A: 3 to 3:30 pm; Design Thinking Workshop–Prototype Your Innovative Solutions: 3:30 – 5 pm)

Read the full story in Monday’s Tech Today.

The Graduate Student Government (GSG) Professional Development Committee has organized a free webinar series in Computer Programming, which begins Tuesday, July 14, 2020.

July 14: “Introduction to Machine Learning with Python,” by Timothy Havens (CC)

July 15: “Managing Data” (Data Mining)” by MS Data Science candidate Sneha Nimmagadda

July 16: “Introduction to Deep Learning,” by Timothy Havens (CC)

Seats are not limited, but participants are asked to register so webinar organizers know how many attendees to expect.

Find more information, including links to register and join Zoom meetings, visit the GSG website.

from the Michigan Tech Office of Admissions

Michigan Tech Admissions is excited to welcome back prospective students and their families for campus tours starting Monday, June 22.

After months of thoughtful planning, we are looking forward to implementing solutions to create a fun and robust experience for visitors while being extremely mindful of everyone’s health and safety.

Below are some of the ways in which tours will be modified:

• Total visit group size will be limited in both the morning and afternoon to 25 people, with tour groups at 1-2 families per guide
• Visitors and tour guides will be required to wear face coverings at all times when indoors and when maintaining a minimum distance of six feet is not possible outdoors
• Student tour guides will follow a modified tour route that will avoid tight spaces, elevators, etc.
• All visitors are being asked to monitor their symptoms consistent with CDC guidelines; all guests will be required to complete a symptom monitoring form prior to arriving on campus

We are excited to get back into the business of showing off our world-class campus, and appreciative of the academic department faculty and staff members who will be meeting with visitors, either in person, following social distancing practices, or virtually.

Plan your campus visit here. (https://www.mtu.edu/admissions/visit/plan)

College of Computing Professor Yu Cai, Applied Computing, has arranged for a special guest lecture on penetration testing by security expert Josh Little of zombietango.

The free, 60-minute technical lecture will take place on Thursday, June 11, 2020, at 2:00 p.m., via an online Microsoft Team meeting.

Join the lecture here. The conference ID: 164 473 926#.

Students enrolled in the summer section of SAT 3812, Cybersecurity I, are required to attend the lecture. All students are welcome and encouraged to join.

Contact Professor Yu Cai for additional information.

The International Graduate Student Communication and Culture Center (IGSC3) is hosting a weekly Conversation Circle on Thursdays at 10:00 a.m. through June 26, 2020.

The aim of the conversation circles is to give international students opportunities to practice conversational English in an informal setting.

International students will discuss a range of topics selected by IGSC3 coaches, as well as students. Topics often include American culture, popular culture, travel, and history.

The meetings will be hosted through an online Zoom meeting. Sign up to participate here.

The College of Computing presented a Convocation Ceremony on May 1, 2020, to honor and recognize Spring and Summer 2020 graduates. At the virtual event, undergraduate student achievement awards were announced, graduates were congratulated, and faculty and staff congratulatory videos were viewed.

Michigan Tech Computer Science alumnus Brian VanVoorst ’93 presented the Convocation address. VanVoorst is a Lead Scientist at BBN Technologies, a member of BBN’s Distinguished Scientists, and a Raytheon Technologies Fellow.

The College’s inaugural class of 109 graduates comprises 5 doctor of philosophy, 14 master of science, and 90 bachelor of science degrees. The College of Computing Class of 2020 is nearly 20% women, 27% of the class graduated with honors, and the average undergraduate GPA is 3.28.

View the Convocation video below and on YouTube.

Play – College of Computing Convocation 2020

See a lists of all the graduates here. Two undergraduates completed dual majors: Lucas Catron, who majored in Computer Science and Humanities, and Mark Heinonen, Electrical Engineering Technology and Audio Productions and Technology.

View faculty and staff congratulatory videos, read student and faculty profiles, and discover all things Class of 2020, on the College of Computing webpage: mtu.edu/computing/class-of-2020.

The Department of Computer Science awarded Class of 2020 undergraduate awards to the following Computer Science (CS) and Software Engineering (SE) graduates:
Christina Anderson, CS: Award for Excellence in Teaching
Keith Atkinson, CS: Award for Exceptional Community Service and Leadership
Dean Bassett, CS: Award for Excellence in Teaching
Jack Bergman, CS: Award for Exceptional Leadership
Lucas Catron, CS: Award for Excellence in Teaching
Crystal Fletcher, CS: Award for Excellence in Teaching
Chris Holmes, CS: Award for Excellence in Teaching
Mads Howard, CS: Award for Excellence in Teaching
Jacob Jablonsky, SE: Award for Excellence in Teaching, Award for Excellence in Teaching
Maddie Le Clair, SE: Award for Exceptional Leadership
Amy Slabbekoorn, CS: Award for Excellence in Teaching
Emily Winkleman, CS: Award for Excellence in Teaching
Parker Young, SE: Award for Exceptional Leadership and Teaching, Award for Excellence in Teaching

Award for Exceptional Community Service and Leadership: Keith Atkinson
Keith has helped older adults in the Houghton community become comfortable with digital technology through one on one tutoring through the BASIC (Building Adult Skills in Computing) program. He taught several cohorts of middle school students about computer programming through the Copper Country Coders organization, and served as president of that organization. Keith developed and deployed a food inventory system for the Husky Food Access Network, which helps combat hunger issues on Tech’s campus.

Award for Exceptional Leadership: Jack Bergman
Jack has served as the president of MTU RedTeam, a student organization dedicated to promoting cybersecurity education among Tech students. Under his leadership, RedTeam organized students to participate in national cybersecurity competitions. In Fall 2019, the MTU Red Team was ranked 8th out of 689 in the NCL cyber competition. Jack led RedTeam to host a cybersecurity competition at MTU in Spring 2020, which attracted 35 students competing on 15 different teams.

Award for Exceptional Leadership: Maddie LeClair
Maddie has been a highly effective leader of the Women in Computing Sciences (WiCS) student organization.  Under her leadership, the group has increased its visibility, holding regular events on campus to highlight the opportunities for women in computing fields.  She led the effort for the WiCS group to become affiliated as an ACM-W chapter, and she has been active in supporting departmental efforts to diversify our undergraduate student body, both individually and as a leader of WiCS.

Award for Exceptional Leadership and Teaching: Parker Young
Parker served as president of not one, but two student organizations: Copper Country Coders and the Michigan Tech Pep Band.  Under his leadership, the Coders group made great strides in its organization and sustainability through revising its charter. Parker is passionate about teaching others, whether it is young students learning to mod Minecraft at Copper Country Coders or older adults learning to Zoom with their families in the BASIC program.  His leadership skills also facilitated his Senior Design team’s  successful completion of the Dragonfly app, an offline app developed for the North Carolina Natural History Museum’s after-school program to assist children monitoring the weather and counting dragonflies.

Award for Excellence In Teaching: Christina Anderson, Crystal Fletcher, Chris Holmes | Mads Howard, Jacob Jablonsky, Parker Young
Christina, Crystal, Chris, Mads, Jacob, and Parker have been mainstays at the College of Computing Learning Center, which provides peer assistance for Michigan Tech students in their computing studies. Learning Center coaches help students from a wide range of backgrounds in a wide array of topics, and must be able to quickly assess and deploy the right tutoring strategy for the situation.

Award for Excellence In Teaching: Dean Bassett, Lucas Catron, Jacob Jablonsky, Amy Slabbekoorn, Emily Winkleman
Dean, Lucas, Jacob, Amy, and Emily have served as lab assistants for our introductory courses. These programming labs are where some of the most important learning moments happen for our beginning students. Lab assistants play a crucial role in providing peer support and guidance. These four individuals have shown great commitment, compassion, and patience in this role.

The CMH Division presented Class of 2020 undergraduate awards to the following students:
Michael Dabish: Outstanding CNSA Graduate Award for exceptional performance as a research and laboratory assistant.
Bernard Kluskens: Outstanding CNSA Graduate Award for exceptional performance as a teaching assistant.
Gary Tropp: Outstanding CNSA Graduate Award, for excellent student academic mentoring in the College of Computing Learning Center.
Emma Davidson: Outstanding EET Graduate Award for exceptional service as a laboratory assistant and grader.
Mark Heinonen: Outstanding EET Graduate Award for an exceptional Senior Design project in audio system design.
Spencer Thompson: Outstanding EET Graduate Award for exceptional service as a teaching assistant in the transition to remote instruction.

Outstanding CNSA Graduate Award: Michael Dabish
For exceptional performance as a research and laboratory assistant. 
Michael’s work in the lab has been very helpful in fulfilling our needs to provide the best lab environment for students. He has shown that he is always willing to put in the work necessary to get the job done.
In 2018 Michael became a research/teaching assistant, working with the CNSA faculty on two NSA grants to create and update course content regarding cyber ethics and cybersecurity.
Michael is constantly collaborating with CNSA faculty and students to discover new ways to implement popular technologies in system administration and security.
He has even created a YouTube channel to document and share methods of implementing these technologies.
What Michael learned in these jobs has inspired him to pursue graduate school in the hope of becoming a teacher right here at Michigan Tech.

Outstanding CNSA Graduate Award: Bernard Kluskens
For exceptional performance as a teaching assistant.
Bernard was teaching assistant for four classes taught by Todd Arney, who nominated Bernard for this award.  Arney says Bernard took the lead on answering lab questions, and then even made calendar appointment slots for students to get one-on-one help using Zoom online. Arney says he would not have been able to manage his  classes with Bernard’s help with grading, fielding questions, and reviewing material before posting to Canvas.

Outstanding CNSA Graduate Award: Gary Tropp
For excellent student academic mentoring in the College of Computing Learning Center.
Gary is the first CNSA student to work as a “Student Academic Mentor” (SAM) in the new “College of Computing Learning Center” (CCLC), offering in person one-on-one help with two of the lab intensive classes in the CNSA program and then even continuing to offer online personalized help for students.

Outstanding EET Graduate Award: Emma Davidson
For exceptional service as a laboratory assistant and grader.
Emma has been helping faculty and students in the lab for over three years, and she also helped with “texting day” to reach out to prospective students.

Outstanding EET Graduate Award: Mark Heinonen
For an exceptional Senior Design project in audio system design.
Mark designed a 4-way passive electrical circuit specifically tuned for a pair of loudspeakers he created as part of his Audio Production and Technology degree.  He started out with a design based on the latest in digital signal processing, but in the end he discovered the value in “old school” analog electrical circuits built from resistors, capacitors, and inductors – what used to be considered mainstream electrical engineering but is now something of a lost art.

Outstanding EET Graduate Award: Spencer Thompson
For exceptional service as a teaching assistant in the transition to remote instruction.
Spencer has been lab assistant for most, if not all of the EET labs. He was nominated for this award by new faculty member Jungyun Bae, who pointed out his dedication to helping students with labs and homework in the EET data acquisition course. After mid-semester, Spencer actively helped the students during lab hours through emails and Zoom meetings. He also took videos of all the labs left within the semester when we transferred into remote instruction and, thanks to him, the course went smoothly even after the campus was locked down.

Honors Graduates: These Department of Computer Science students graduated with honors.
Christina Anderson, CS, Magna Cum Laude
Isaac Appleby, CS, Magna Cum Laude
Daniel Carrara, CS, Magna Cum Laude
Lucas Catron, CS, Magna Cum Laude
Zach Dill, CS, Cum Laude
Peter Dukes, CS, Magna Cum Laude
Trevor Good, CS, Magna Cum Laude
Ethan Hegg, CS, Cum Laude
Mads Howard, CS, Magna Cum Laude
Sophia Jensen, CS, Cum Laude
Derek Kamin, CS, Magna Cum Laude
Alex Larkin, CS, Cum Laude
Maddie LeClair, SE, Cum Laude
James Michniewicz, CS, Summa Cum Laude
Michael Munoz, CS, Summa Cum Laude
Dante Paglia, CS, Summa Cum Laude
Brandon Paupore, SE, Cum Laude
Elijah Potter, CS, Cum Laude
Emily Winkleman, CS, Cum Laude
Kieran Young, CS, Cum Laude
Parker Young, SE, Magna Cum Laude

Honors Graduates: These CMH Division students graduated with honors:
Dina Falzarano, CNSA, Cum Laude
Timothy Graham, CNSA, Cum Laude
Mark Heinonen, EET, Cum Laude
Andrew Hitchcock, CNSA, Magna Cum Laude
Chris Koch, CNSA, Summa Cum Laude
Zack Metiva, CNSA, Magna Cum Laude
Joshua Peter, CNSA, Magna Cum Laude
Spencer Thompson, EET, Cum Laude

This May, AVA Labs, a next-generation blockchain platform spun out of Cornell and led by Professor Emin Gün Sirer, is hosting a month-long virtual hackathon for the best and brightest computer science and engineering students in the world.

The event will focus on developing new applications for financial products and services, and infrastructure tools that could someday be used by millions of people on the AVA platform. In addition to opportunities for close mentorship with our engineering leadership and early exposure to the most anticipated blockchain launch of 2020, students will have the opportunity to compete for up to $50,000 in prizes.

More details on the event are in the note below, and linked here: https://www.avalabs.org/ava-x/hackathons/university-hackathon-may-2020

And here is a recent Bloomberg News article featuring AVA: New Startup Aims to Prove Blockchain Fast Enough for Finance

AVA is a leading blockchain platform spun out of Cornell and led by Professor Emin Gün Sirer. It is an open-source platform for launching highly decentralized applications, new financial primitives, and new interoperable blockchains.

All GenCyber 2020 summer programs will be deferred to 2021 due to the impact of the COVID-19 virus.

For a listing of those programs who are receiving funding to host a camp, please see gen-cyber.com.

For updates and questions regarding specific camps and/or outreach activities, please contact the host institution using the information found on gen-cyber.com.

Please direct questions about the Michigan Tech GenCyber program to gencyber@mtu.edu.

The College of Computing’s Department of Applied Computing invites the campus community to lecture by MERET faculty candidate Dr. Sidike Paheding, Friday, April 10, 2020, at 3:30 p.m., via an online Zoom meeting. The title of Paheding’s lecture is, “Machine Learning in Multiscale and Multimodal Remote Sensing: From Ground to UAV with a stop at Satellite through Different Sensors.”

Link to the Zoom meeting here.

Paheding is currently a visiting assistant professor in the ECE department at Purdue University Northwest. His research interests cover a variety of topics in image/video processing, machine learning, deep learning, computer vision, and remote sensing.

 Abstract: Remote sensing data provide timely, non-destructive, 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, machine learning for remote sensing has gained significant momentum due to advances in algorithm development, computing power, sensor systems, and data availability.

In his talk, Paheding will discuss the potential applications of machine learning in remote sensing from the aspects of different scales and modalities. Research topics such as multimodal data fusion and machine learning for yield prediction, plant phenotyping, augmented reality and heterogeneous agricultural landscape mapping will be covered.

Paheding earned his M.S. and Ph.D. degrees in electrical engineering at the University of South Alabama, Mobile, and University of Dayton, Ohio, respectively. He was a postdoctoral research associate and and assistant research professor in the Remote Sensing Lab at Saint Louis University from 2017 to 2019, prior to joining Purdue University Northwest.

He has advised students at the undergraduate, master’s, and doctoral levels, and authored or co-authored close to 100 research articles, including in several top peer-review journal papers.

He is an associate editor of the Springer journal Signal, Image, and Video Processing, a guest editor/reviewer for a number of reputed journals, and he has served on international conference committees. He is an invited member of Tau Beta Pi (Engineering Honor Society). 

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.