Day: January 28, 2020

CNSA Major Vies for Winter Carnival Queen Honors

Zack Metiva, a fourth-year Computer Network and System Administration (CNSA) major, is running for Winter Carnival Queen. Michigan Tech students can vote for Metiva on the Winter Carnival website at Voting closes on Friday, January 31.

“I’d love to be your Winter Carnival Queen. I’m President of IT Oxygen Enterprise and the social chair of the drumline at Michigan Tech. I’m a fourth-year Computer Network and System Administration major and over the years I’ve grown to enjoy the snow. I love waking up in the morning and seeing a fresh dusting everywhere I look. My favorite winter activity is skiing and that constant supply of fresh powder makes Mont Ripley one of the best places to ski north of The Mighty Mac. Winter Carnival is a celebration of that snow as well as all of the great feats students at Michigan Tech can accomplish with it during some of the most brutal months of the year. I think that as long as they use their head and eat some bread, watch out for their friends, and stay hydrated — that means water — anyone should be able to feel like royalty during Winter Carnival. If you agree, vote for me. I’d like to thank the Huskies Pep Band, the most progressive drumline in the Keweenaw, for sponsoring me in this competition.”

Metiva’s candidacy is sponsored by the Huskies Pep Band and Swift True Value Hardware, Houghton.

Faculty Candidate Lan Zhang to Present Lecture February 5

The Colleges of Computing and Engineering invite the campus community to a lecture by faculty candidate Lan Zhang on Wednesday, February 5, 2020, at 3:00 p.m., in Chem. Sci. 101. Zhang’s lecture is titled, “Machine Learning Enabled Better Cyber-Physical Systems: A Case Study on Better Networking for Connected Vehicles.”

Bio: Lan Zhang is a Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of Florida. She received the B.Eng. and M.S. degrees in telecommunication engineering from the University of Electronic Science and Technology of China, in 2013 and 2016, respectively. Zhang’s research interest spans across the fields of big data, cyber-physical systems, machine learning, wireless communications, and cybersecurity. She has published 15 technical papers in top-tier journals and conference venues, such as IEEE Transactions on Vehicular Technology, Proceedings of the IEEE, and IEEE Transactions on Wireless Communication.

Zhang has served as a technical program committee (TPC) member for several high-quality conferences, such as the 2020 IEEE INFOCOM poster/demo section and the 2018 International Conference on Computing, Networking and Communications. She also serves as reviewer for several leading journals, such as IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Mobile Computing, and IEEE Transactions on Wireless Computing. Zhang was the speaker at several flagship celebrations and conferences, such as IEEE Global Communications Conference 19, Grace Hopper Celebration 19, and the IEEE International Conference on Communications 19.

Lecture Abstract: With the recent success of big data analytics, machine learning is being used in various Cyber-Physical Systems (CPS) applications, such as smart transportation, smart healthcare, and industrial automation. As a highly interdisciplinary field, the CPS applications require the machine learning-enabled wireless communication strategies to facilitate information exchanges, and meanwhile call for secure and private learning pipelines to manage information exchanges.

In her talk, Zhang focuses on connected vehicles, aiming at supporting the demand for multi-Gbps sensory data exchanges through millimeter-wave bands for enhancing (semi)-autonomous driving. Unlike most traditional networking analysis that manipulates end devices to adapt to the transmission environments, i.e., fight against any transmission obstacles, we propose an innovative idea to proactively manipulate, reconfigure, and augment the transmission environments for better communications.

Without damaging the aesthetic nature of environments, we deploy multiple small-piece controllable reflecting surfaces, and adaptively manipulate the angle of the used reflecting surfaces to address the vulnerability of blockages in mmWave vehicular communications by creating alternative indirect line-of-sight connections. To autonomously and efficiently augment the highly dynamic vehicular environments in real-time, deep reinforcement learning techniques are implemented. Effectiveness of our proposal is showcased on the traffic at the City of Luxembourg using a traffic simulation toolkit, Simulation of Urban MObility (SUMO). 


Computing Majors on GLIAC All-Academic Team

Congratulations to College of Computing grad student Bernard Kluskens, Cybersecurity, and senior Robbie Watling, Computer Science, who are among 18 Michigan Tech students recognized on the 2019 GLIAC Men’s Cross Country All-Academic Excellence Team.

Bernard Kluskens

Robbie Watling