Author: karenjoh

Tim Havens Quoted in Enterprisers Project Article

Tim Havens, associate dean for research, College of Computing, was quoted in the story “Artificial intelligence (AI) vs. natural language processing (NLP): What are the differences?” published February 26, 2020, in the online publication, The Enterprisers Project.

With AI, computers can learn to accomplish a task without ever being explicitly programmed to do so, says Timothy Havens, the William and Gloria Jackson Associate Professor of Computer Systems in the College of Computing at Michigan Technological University and director of the Institute of Computing and Cybersystems.

For those who prefer analogies, Havens likens the way AI works to learning to ride a bike: “You don’t tell a child to move their left foot in a circle on the left pedal in the forward direction while moving your right foot in a circle… You give them a push and tell them to keep the bike upright and pointed forward: the overall objective. They fall a few times, honing their skills each time they fail. That’s AI in a nutshell.”

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. 


Capture the Flag Competition Incredibly Successful

The Capture the Flag competition at this year’s Winter Wonderhack, held the weekend of February 21-23, was incredibly successful, with a total of 35 students competing on 15 different teams.

The three top teams finished with 100% completion after 10+ hours of hard work, and the fourth place team was close behind with only two flags left. The entire competition was very competitive, with the top four teams constantly exchanging places throughout the weekend.

Winning teams:

First Place (Hak5 WiFi Pineapple and Manual) – Real Pineapple:
Eli Brockert, Cybersecurity, sophomore
Matthew Chau, Cybersecurity, freshman
Nathan Wichers, EE, freshman

Second Place  (Hak5 Packet Squirrel and Manual) – College Nerd Seeking Assets
Justin Bilan, CNSA, junior
Stuart Hoxie, CNSA, junior
Ben Kangas , CNSA, junior
Austin Clark, CNSA, junior
Nicklaus Finetti, CNSA, senior

Third Place (Hak5 USB Rubber Ducky and Manual)  – The Blue Tigers 21
Austin Doorlag, CS, sophomore
Harley Merkaj, CS, sophomore
Anthony Viola, CpE, sophomore

Fourth Place (Hak5 Sticker Packs and USB Rubber Ducky Manual)  – Fsociety
Sam Breuer, CpE, freshman
John Claassen, CS, sophomore
Samantha Christie, CS, freshman

All participants in the Capture the Flag Competition, February 21-23, 2020

Michigan Tech is #2 on WXYZ List of Highest-paid Grads

Michigan Tech is #2 on list of highest-paid grads in Michigan published recently by WXYZ Detroit (ABC-TV). The ratings are based on data from Payscale.com.

For Michigan Tech grads, the midpoint for early career salaries is $65,000 (five or fewer years on the job), and the midpoint for seasoned pros is more than $116,000 (10 years on the job). No school in Michigan awards a higher percentage of science, technology and engineering degrees that Michigan Tech.

Other schools on the list were Albion College (#7), University of Michigan Dearborn ( #6 ), Michigan State University (#5), Lawrence Technological University (#4), University of Michigan (#3), and Kettering University (#1). View the full story here.


Leidos Gift Equips EET, MET Lab with State-of-the-Art Learning Tools

Leidos representatives Matthew Luttinen, Jessica Hutchings, Kate Nowosad, Dale Rimmey, and Mike Cooney

It was five years ago, in 2015, when Leidos and Michigan Tech representatives started talking about equipping the Electrical Machinery and Controls Lab with new Amatrol learning stations.

It took some time, but in 2018 a generous gift from Leidos got things started. The lab space–on the 4th floor of the Electrical Energy Resources Center (EERC)–was expanded and refurbished, the electrical was upgraded, and the cost of the new work stations was considered.

“It wasn’t enough to do all we wanted to do,” said Dale Rimmey, director of college talent acquisition and solutions at Leidos, “so we talked some more, and eventually we were pleased to double our original gift.”

“This lab was a long time coming, and along the way we developed some great relationships with our industry partners,” said Adrienne Minerick, dean of the College of Computing. “Everything came together because Leidos and Eagle Mine believe in the quality of Michigan Tech education, and because an investment in qualified people assures a great future for our students and for all concerned.”

With the second Leidos gift in 2019, the EET and MET programs were able to complete the lab refurbishment and install six new state-of-the art learning stations in time for the fall 2019 section of Electrical Machinery (EET 2233).

Four of the learning stations and lab renovations were funded by Leidos, one station was funded by Eagle Mine, and one was purchased by the former Michigan Tech School of Technology.

This week, Leidos representatives were on campus to celebrate the completion of the Leidos Electrical Machinery and Controls Lab, and to participate in Career Fair. Leidos representatives attending were Dale Rimmey; Mike Cooney ’01 (BS, EET), project lead; Jessica Hutchings ’15 (BS, EE), controls engineer; Matthew Luttinen ’10 (MS, EE/Power Systems), electrical engineer; Kate Nowosad, ’17 (BS, EE), substation design engineer.

More than anything, Dale Rimmey is excited for the students who will benefit from the gift. “This is a great opportunity to support Michigan Tech students and at the same time build a larger pool of talented, well-trained future employees for Leidos and the industry as a whole,” he said.

Required for all EET and MET students, EET 2233 is a crucial building block in the study of electrical and mechanical engineering and mechatronics.

“In mechatronics, students learn to appreciate the electrical, mechanical and computing side of hardware equipment,” said assistant professor Nathir Rawashdeh, CMH Division. “Selecting and controlling electrical machines are prime examples of this, and the new learning units and exercises provide all the tools students need to thoroughly understand these subjects.”

Michigan Tech students and Leidos reps

Students in last fall’s section of the class were the first to use the new learning stations, thanks to EET senior Zarek Pirkola and his fellow lab assistants, who assembled and tested the machines in time for the second half of the fall 2019 semester.

The new equipment also led to revisions in the hands-on lab exercises that accompany the Electrical Machinery course; units related to emerging topics, motor control, and troubleshooting were added.

“It was a race against time to get the machines ready for the eight-week motors unit last fall,” Pirkola said, adding that the curricula included with the units helped a lot. Pirkola was among the last students to use the old lab and equipment.

“The new equipment and curricula broaden the scope of laboratory exercises, and allow us to cover the more advanced control circuits used in operating larger electrical machinery,” said Alex Sergeyev, CMH Division professor and director of the Mechatronics graduate program.

“The knowledge and experience students gain means better-educated graduates with more practical hands-on experience,” said Sergeyev. “The design, configuration, and troubleshooting of industrial control systems is central to today’s industry, and the new Amatrol work stations are key to building the foundational knowledge future leaders in the field will need … with obvious benefits to employers of our graduates.”

Before the new Leidos lab was outfitted, EET 2233 student exercises were conducted on outdated, unreliable equipment, noted lecturer Paniz Hazaveh, College of Computing. The new units are more compact and they’re equipped with a number of safety features, including lower voltage and an emergency shut off, she explained.

With an average of 45 students enrolling in EET 2233 each fall semester, there is more to be done. Leidos has already started the wheels turning for a third gift to purchase additional units, and now there is plenty of space in the new lab.

Also among those attending the celebration were Adrienne Minerick, dean, College of Computing; Dan Fuhrmann, chair of the CMH Division; Nathir Rawashdeh, assistant professor, CMH Division; Rick Berkey, professor of practice, Pavlis Honors College; Jim Desrocher, director of advancement; Cody Kangas, director of industry engagement; and a number of graduate and undergrad students.

Nathir Rawashdeh demonstrates the learning unit

About the Partners

Serving the business intelligence, health, IT, defense, and civil sectors and with more than 400 locations in 30 countries, Leidos is a global leader in the integration and application of information technology, engineering, and science.

Amatrol designs, develops and manufactures technical training systems and simulators for industry and academia to teach technical and workplace skills ranging from entry level basic technical skills to advanced technology troubleshooting for degree and certification preparation.

Amatrol’s Basic Electrical Machines Learning System teaches electric machines commonly found in industrial, commercial, and residential applications: single phase AC motors, three-phase AC electric motors, and DC electric motors. Learners practice industry-relevant skills including operation, installation, analyzing performance, industrial motor wiring, and selecting electric machines for various applications.

Eagle Mine, a subsidiary of Lundin Mining, is an underground, high-grade nickel and copper mine located in western Marquette County of Michigan’s Upper Peninsula. Lundin Mining is a diversified base metals mining company with operations and projects around the world.

The Michigan Tech College of Computing prepares students for lifelong prosperity and employability through relevant, contemporary academic programs in computing and cyber-technologies. The College offers graduate degrees in Computer Science, Cybersecurity, Health Informatics, and Mechatronics; and undergraduate degrees in Computer Network System Administration (CNSA), Computer Science, Cybersecurity, Electrical Engineering Technology (EET), and Software Engineering.

The College of Computing’s CMH Division–Computer Network and System Administration/Mechatronics, Electrical, and Robotics Engineering Technology/Health Informatics Division–brings together faculty and programs in the College of Computing that share a common interest in applied aspects of computing.  The areas of study within the Division–computer networks, cybersecurity, robotics, big data–provide Michigan Tech graduates skills that are in high demand, now and in the future.

Enjoy the photo gallery below.

(L to R) Adrienne Minerick, Paniz Hazaveh, Dan Fuhrmann, Mike Cooney, Nathir Rawashdeh, Zarek Pirkola

Leidos representatives Jessica Hitchungs, Dale Rimmey, and Mike Cooney

Leidos representatives Matthew Luttinen, Jessica Hitchungs, Kate Nowosad, Dale Rimmey, and Mike Cooney

Nathir Rawashdeh demonstrates the learning system

Amatrol Basic Electrical Machines Learning System

Amatrol Basic Electrical Machines Learning System

Dan Fuhrmann (L) and Nathir Rawashdeh

Celebration attendees

Nathir Rawashdeh demonstrates the Amatrol learning system

Nathir Rawashdeh demonstrates the Amatrol learning system

Nathir Rawashdeh demonstrates the Amatrol learning system

Nathir Rawashdeh demonstrates the Amatrol learning system

Nathir Rawashdeh demonstrates the Amatrol learning system

Nathir Rawashdeh demonstrates the Amatrol learning system

Amatrol Basic Electrical Machines Learning System

Amatrol Basic Electrical Machines Learning System

Amatrol Basic Electrical Machines Learning System

Amatrol Basic Electrical Machines Learning System

Zarek Pirkola


RedTeam to Host Capture the Flag Competition, Feb. 21-23

In conjunction with the 36-hour Winter WonderHack, February 21-23, 2020, on Michigan Tech’s campus, the Michigan Tech RedTeam is running a Capture the Flag cybersecurity competition. The competition is designed to appeal to both beginners and the more experienced competitors. Everyone is welcome, especially undergraduates. Free swag and prizes will be awarded. Register at winterwonderhack.com. Email jrbergma@mtu.edu with questions.

About the Capture the Flag competition:
What: Jeopardy-style cybersecurity competition with questions broken down by category and difficulty.
When: All weekend, February Compete at your convenience.
Who: Students from any major in teams up to 5. No prior experience is necessary.
Win: Hak5 prizes including a WiFi Pineapple, Packet Squirrel, USB Rubber Ducky, and Sticker Packs.


Winter WonderHack, Capture the Flag Competition are Feb. 21-23

Winter Wonderhack will take place on the Michigan Tech campus February 21-23. The free 36-hour event is for all students to work on technical projects. get free swag, and win prizes. Register at winterwonderhack.com.

Also part of the Winter WonderHack, the Michigan Tech RedTeam is running a Capture the Flag cybersecurity competition. The competition is designed to appeal to both beginners and the more experienced competitors. Everyone is welcome, especially undergraduates.

About the Winter WonderHack:
WHAT DO I DO? Whatever you can dream up! A hackathon; A makeathon; an inventathon – whatever your take on it, this is about using your passion to learn and create something new.
WHO IS ELIGIBLE? If you are a current student, or if you have graduated in the last 12 months, you are eligible. If you are a high-school student and want to attend, great! Contact us below.
DO I NEED ANY PARTICULAR SKILLS? IS THIS FOR ME? You don’t need anything except your brain and passion. Everyone of all fields of study and levels of experience is welcome. You don’t have to be an engineer or a programmer or designer to belong here. Additionally, we will have multiple workshops, crash-courses and mentors to kick-start and guide you to where you want to be.
DO I HAVE TO BE ON A TEAM, OR CAN I FLY SOLO? Either is fine; you can go solo or be in a team of up to four people. Note: Competing alone does not mean you get four times the prizes, sorry 🙁
HOW MUCH DOES IT COST? Nothing! We will provide everything – food, sleeping space, power, internet, snow…
WILL THERE BE PRIZES? SWAG? FOOD? Yes, yes, and yes. This event is about learning and fun, but we’ve partnered with our sponsors to bring some awesome prizes to WWH, including some surprises.
I DON’T HAVE ANYTHING TO DO! Not a problem! Many people don’t have plans down when they arrive. There will be time and space to get together with students from other schools and get some ideas flowing. Meeting new people, being exposed to new ideas, and learning new things is one of the best things about coming, and many people also often end up creating great things, making friends, or even starting companies.
WHAT SHOULD I BRING? WILL THERE BE ANYTHING AVAILABLE TO USE? Bring whatever you need, but keep it light. This probably means a laptop, a change of clothes and other basics, and whatever you plan on using for your project. Make sure you bring a student ID (and a photo ID if your student ID does not have a photo). We’ll have some hardware available for the duration of the event as well as tools, 3d printers, materials like wood and foam, and a few freebies like free web domains.
WILL I BE COLD? No, you will not be cold (it doesn’t get that cold here… relatively speaking); if anything you’ll be quite toasty inside. Do dress appropriately though (mittens!), especially bearing in mind that you might want to do something happening outside, where while not overly cold, it will be a winter wonderland with MTU’s 300+ inch-per-year snowfall and plentiful ice sculptures from the Winter Carnival.
HOW DO I GET THERE? Directions to the venue can be found here.
WHEN IS THE DEADLINE TO REGISTER? The first round of decisions will be made in early February. This isn’t a deadline, and if we don’t have room for you at first, we may accept you later; it is common to be accepted off the waitlist after the first round of decisions.
ARE THERE ANY RULES? You must abide by our Code of Conduct. You don’t necessarily have to start your project from scratch, but you can’t submit anything you did before the start of the event. All work must be done at the event.

About the Capture the Flag competition:
What: Jeopardy-style cybersecurity competition with questions broken down by category and difficulty.
When: All weekend, February Compete at your convenience.
Who: Students from any major in teams up to 5. No prior experience is necessary.
Win: Hak5 prizes including a WiFi Pineapple, Packet Squirrel, USB Rubber Ducky, and Sticker Packs.


Faculty Candidate Songtao Lu to Present Lecture March 2

The Colleges of Computing and Engineering invite the campus community to a lecture by faculty candidate Songtao Lu, Monday, March 2, 2020, at 3:00 p.m., in Chem Sci 102. Lu’s talk is titled, “Nonconvex Min-Max Optimization for Machine Learning.”

Songtao Lu is an AI resident at IBM Research AI, IBM Thomas J. Watson Research Center. His research interests include optimization, artificial intelligence, machine learning, and neural networks. Lu received his Ph.D. degree in electrical and computer engineering from Iowa State University in 2018, and he was a post-doctoral associate with the ECE department at the University of Minnesota Twin Cities from 2018 to 2019.

We live in an era of data explosion. Rapid advances in sensor, communication, and storage technologies have made data acquisition more ubiquitous than ever before. Making sense of data at such a scale is expected to bring ground-breaking advances across many industries and disciplines. 

However, to effectively handle data of such scale and complexity– and to better extract information from quintillion of bytes of data for inference, learning, and decision-making—increasingly complex mathematical models are needed. These models, often highly nonconvex, unstructured, and with millions or even billions of variables, render existing solution methods inapplicable.

Lu will present work that designs accurate, scalable, and robust algorithms for solving nonconvex machine learning problems. He will discuss the theoretical and practical properties of a class of gradient-based algorithms for solving a popular family of min-max non-convex problems.

Finally, Lu will showcase the practical performance of these algorithms in applications such as poisoning attacks to neural nets, decentralized neural nets training, and constrained Markov decision processes. He will briefly introduce ideas for the possible extension of his framework to other areas.

Lu is a recipient of the Iowa State University Graduate and Professional Student Senate Research Award (2015), the Research Excellence Award from the Graduate College of Iowa State (2017), and student travel awards from ICML and AISTATS.

Download

Faculty Candidate Tao Li to Present Lecture February 27

The Colleges of Computing and Engineering invite the campus community to a lecture by faculty candidate Tao Li on Thursday, February 27, 2020, at 3:00 p.m. in. Fisher 325. His talk is titled, “Security and Privacy in the Era of Artificial Intelligence of Things.”

Tao Li is a Ph.D. candidate in computer engineering in the School of Electrical, Computer and Energy Engineering at Arizona State University. He received an M.S. in somputer science and technology from Xi’an Jiaotong University in 2015, and a B.E. in software engineering from Hangzhou Dianzi University in 2012. His research focuses on cybersecurity and privacy, indoor navigation systems for visually impaired people, and mobile computing. 

AIoT—Artificial Intelligence of Things (AIoT)—combines artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure. By 2025, the number of IoT devices in use is estimated to reach 75 billion.

And as AIoT plays an incrreasingly significant role in our everyday lives, the security and privacy of AIoT has become a critical concern for the research community and the public and private sectors. 

In his talk, Li will introduce his recent research focused on the protection of AIoT devices. A novel system that can automatically lock mobile devices against data theft will be introduced, and a touchscreen key stroke attack (based on a video capturing the victim’s eye movements) will be discussed. Li will briefly introduce additional projects of interest.

Li has served as a reviewer for journals and conferences including IEEE TMC, IEEE TWC, ACM MobiHoc, and IEEE INFOCOM.

Download

Faculty Candidate Brian Yuan to Present Lecture February 26

The Colleges of Computing and Engineering invite the campus community to a lecture by faculty candidate Xiaoyong (Brian) Yuan on Wednesday, February 26, 2020, at 3:00 p.m. in Chem Sci 101. Yuan’s talk is titled, “Secure and Privacy: Preserving Machine Learning, A Case Study on Model Stealing Attacks Against Deep Learning.”

Brian Yuan is a computer science Ph.D. candidate at the University of Florida. He received an M.E. degree in computer engineering from Peking University in 2015, and a B.S. degree in mathematics from Fudan University in 2012. His research interests span the fields of deep learning, machine learning, security and privacy, and cloud computing.

In his talk, Yuan will provide an overview of security and privacy issues in deep learning, then focus on his recent research on a data-agnostic model stealing attack against deep learning.  He will conclude with a discussion of some future research directions to address security and privacy concerns in deep learning and potential countermeasures.  

Due to recent breakthroughs, machine learning, especially deep learning, is pervasively serving areas such as autonomous driving, game playing, and virtual assistants. Recently however, significant security and privacy concerns have been raised in deploying deep learning algorithms. 

On one hand, deep learning algorithms are fragile and easily fooled by attacks. For example, an imperceptible perturbation on a traffic sign can mislead the autonomous driving systems. On the other hand, with the increasing use of deep learning in personalization, virtual assistants, and healthcare, deep learning models may expose users’ sensitive and confidential information. 

With important business value, deep learning models have become essential components in various commercialized machine learning services, such as Machine Learning as a Service (MLaaS). Model stealing attacks aim to extract a functionally equivalent copy of deep learning models and cause a breach of confidentiality and integrity of deep learning algorithms. Most existing model stealing attacks require private training data or auxiliary data from service providers, which significantly limits the attacking impact and practicality. Yuan proposes a much more practical attack without the hurdle of training data, and its effectiveness will be showcased in several widely used datasets. 

Yuan has published 17 papers in top-tier journals and conferences, such as IEEE Transactions on Neural Networks and Learning Systems (TNNLS) and the AAAI Conference on Artificial Intelligence (AAAI). He has served as reviewer for several leading journals and conferences, such as IEEE Transactions on Neural Networks and Learning Systems (TNNLS), International Conference on Learning Representations (ICLR), IEEE Transactions on Dependable and Secure Computing (TDSC), and IEEE Transactions on Parallel and Distributed Systems (TPDS).

Read the blog post here: https://blogs.mtu.edu/computing/2020/02/12/faculty-candidate-brian-yaun-to-present-lecture/

Download