Author: karenjoh

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.

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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.

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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/

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Health Informatics Online Graduate Program Ranked Best in the Midwest, 11th in Nation

The Michigan Tech online Master’s in Health Informatics has been ranked best in the midwest and 11th nationally by Intelligent.com, ahead of universities such as Stanford, Northwestern, and Boston University. Michigan Tech’s 2020 ranking rose from 17th nationally in 2019.

See the full rankings here.

According to their website, Intelligent.com is a free, editorially independent, privately-supported website. It aims to “connect students to the best schools that meet their needs” through “unbiased, accurate, and fact-based information on a wide range of issues.” Their rankings are based on aggregated publicly available data about colleges and programs across the country.

In November 2019, the website OnlineSchoolsCenter.com ranked Michigan Tech’s online Health Informatics M.S. program among the 20 finest online colleges and universities. Michigan Tech was the only school from Michigan to make the list. 


Computing’s CMH Division Adds Academic Advisor

The College of Computing is pleased to welcome Kathryn (Kay) Oliver as our newest academic advisor effective February 10, 2020. Oliver will have primary responsibility for advising undergraduate students in the CNSA, EET, and Cybersecurity programs. She’ll also assist in managing the graduate programs in Mechatronics and Health Informatics, and the advising of other undergraduate students in the College of Computing, as needed.

Oliver has an M.A. in educational technology from Michigan State University and a B.S. in physics from Western Michigan University. For more than 20 years she worked with the Department of Defense Education Activity, a government agency responsible for K-12 education of children of American citizens working internationally for the DoD. For most of that time she was responsible for the professional development of teachers with education technology; the past two years she taught AP Computer Science to American high school students in South Korea.

“The search committee was very impressed with Kay’s background and her communication skills,” said Dan Fuhrmann, director of the CMH Division. “She is going to do an outstanding job, connecting with our students and providing information and support. It’s great to have her on board.


Two Papers by Yakov Nekrich Accepted by SoCG 2020 Conference

Yakov Nekrich, associate professor, Department of Computer Science, has been notified that two scholarly papers he has authored were accepted by the 36th International Symposium on Computational Geometry (SoCG 2020), which takes place June 23-26, 2020, in Zurich, Switzerland.

The two papers are “Further Results on Colored Range Searching,” by Timothy M. Chan, Qizheng He, and Nekrich, and “Four-Dimensional Dominance Range Reporting in Linear Space” by Nekrich alone.

The Annual Symposium on Computational Geometry (SoCG) is an academic conference in computational geometry. Founded in 1985, it was originally sponsored by the SIGACT and SIGGRAPH Special Interest Groups of the Association for Computing Machinery (ACM). It dissociated from the ACM in 2014. Since 2015 the conference proceedings have been published by the Leibniz International Proceedings in Informatics Since 2019 the conference has been organized by the Society for Computational Geometry. (Wikipedia)

Visit the SoCG 2020 website.


Faculty Candidate Chensheng Wu to Present Lecture March 4

The Colleges of Computing and Engineering invite the campus community to a lecture by faculty candidate Chensheng Wu on Wednesday, March 4, 2020, at 3:00 p.m. in Chem Sci 101. (In the original announcement, the date of the talk was incorrect.) Wu’s talk is titled, “Design and implementation of computational optics: perception, control, and processing of light-field information and future challenges.”

Dr. Wu is an assistant research scientist in the Department of Electrical and Computer Engineering at the University of Maryland College Park, where he received a Ph.D. degree in ECE.  His doctoral thesis, “the plenoptic sensor,” was was awarded distinguished dissertation honors. Wu also has a B.E. degree in micro-electronics and B.S. in economy, both from Tsinghua University, Beijing, China. 

The emerging field of computational optics is growing rapidly, and it constantly requires newer sensors and computational architectures to satisfy the exploding needs in data collection and processing. Many other research disciplines, such as machine learning, the internet of things, data privacy, and security have also added great challenges to the means of collecting, processing and transmitting data.

The concept of using special optical structures or coded lenses to perform the computation along with data collection, encryption or transmission is becoming a favorable solution in countless applications.

In his talk, Wu will discuss his recent work on the use of new computational optics hardware in solving difficult problems in wavefront sensing, adaptive laser beam formation and correction, imaging through turbulence, detecting hidden objects through scattering media, and space optics. He will discuss how these recent discoveries reveal the potential of specially designed optical structures for computing, and share examples of how future computational optics will take part in sensing, communication, and computation. Wu will conclude his talk with a monologue on predicting the future of computational optics. 

Wu is an advocator for computational sensing using optical and photonics approaches. He is a leading scientist on multiple projects funded by the Office of Naval Research (ONR) and the Directed Energy Joint Technology Office (DE-JTO) Wu’s innovations of the plenoptic sensor, multi-aperture laser transmissometer, computational beam shaping with two deformable mirrors, and lossy sensing-based adaptive optics correction have become well-known. 

Wu has also worked with the Naval Air Warfare Center Aircraft Division (NAWCAD) to configure a new approach to identify and profile hidden objects in murky water environments. He is recognized as a key contributor to NASA’s next generation lunar reflector (NGLR) task to put three new retro-reflectors on the Moon for lunar laser ranging experiments in the 21st Century. Wu is also a team member in the joint collaboration of the Lunar Geophysical Network.