Computer Science in Top 18 in Nation

homepage_clouds_lgPayScale, a compensation analysis web site, has announced the top 25 university computer science programs in the country and Michigan Tech placed 18th.

In its 2016-2017 College Salary Report, Payscale ranked 171 colleges and universities with computer science programs based on the median early-career and mid-career pay of the schools’ computer science alumni. Tech’s early-career computer science salaries are listed at $63,900. Mid-career median pay is $126,000.

“This is great news. It is the best indicator of the quality of our programs,” said Min Song, chair of Computer Science.

Stanford University ranked number one in the nation, with its computer science graduates reporting a median early-career salary of $99,500 and mid-career salary of $168,000. Read the full report.

By Jenn Donovan


Alex Larkin, CS undergrad, achieves a national NCL ranking

FB_IMG_1525454724440Alex Larkin. Computer Science undergrad. Outstanding achievement.

Alex placed 36th out of 3,350 students/players in the 2018 National Cyber League (NCL) cyber competition!  CS Assistant Professor, Bo Chen, is the faculty coach.

The NCL was founded in May 2011 to provide an ongoing virtual training ground for collegiate students to develop, practice, and validate their cybersecurity skills. It is a defensive and offensive puzzle-based, capture-the-flag style cybersecurity competition. Its virtual training ground helps high school and college students prepare and test themselves against cybersecurity challenges that they will likely face in the workforce. All participants play the games simultaneously during Preseason, Regular Season and Postseason.

Way to go Alex!

 


Undergraduate Programming Competition Win

18th Annual NMU Invitational Programming Contest Logo with 95 Students, 6 Schools, 34 TeamsComputer science undergraduate students received top honors at the 19th Annual Northern Michigan University Invitational Programming Contest held March 24, 2018. Tony Duda, Justin Evankovich, and Nicholas Muggio took first place; Michael Lay, Parker Russcher, and Marcus Stojcevich took second. Michigan Tech earned the highest program count and No. 1 ranking.

Congratulations!

“We are proud of our students for representing Husky values of possibility and tenacity.” —Min Song, Chair, Computer Science



Research Excellence Fund (REF) Award Announced

Keith VirtanenThe Vice President for Research Office announced the 2018 Research Excellence Fund (REF) awards and thanked the volunteer review committees, as well as the deans and department chairs, for their time spent on this important internal research award process.

Keith has received a Research Excellence Fund (REF) seed grant from Michigan Tech for his project entitled “Automatic Speech Recognition using Deep Neural Networks”. This one-year project has a budget of $45,421. This project will create a state-of-the-art speech recognition engine based on deep neural networks. The recognizer will be used to investigate speech-based interactive systems for instrumented physical environments (e.g. cars) and person-centric devices (e.g. augmented reality smartglasses). The recognizer will also be used to investigate the input of Java source code by voice.

Congratulations Keith!

 

 

 


Webinar to Discuss Cyber-physical Security

The USDOT ITS Professional Capacity Building Program is hosting a webinar, free and open to all interested, on the topic “Transportation Cyber-physical Security: Things We Should Know,” from 1-2 p.m. May 10.

Threats to cyRoom full of computer servers going around in a curve.ber-physical systems are targeting institutions and infrastructures around the world, and the frequency and severity of attacks are on the rise. Industries considered the most lucrative targets include healthcare manufacturing, financial services, education, government and transportation. Hacking is about more than companies, organizations and banks—it also affects transportation-critical infrastructure (e.g., automotive systems and field devices).

Webinar registration and additional information can be found here.


Keith Vertanen Receives NSF CAREER Award

Keith VirtanenKeith Vertanen(HCC), has been award a 2018 NSF CAREER Award for his project entitled, “Technology Assisted Conversations”. This 5-year award has a total budget of $538,799.

In this project, Keith will create new real-time communication solutions for people who face speaking challenges, including those with physical or cognitive disabilities.The primary goal of this project is to develop technology that improves upon the Augmentative and Alternative Communication (AAC) devices currently available to help people speak faster and more fluidly.

Keith and his team will expand resources for research into conversational interactive systems, and will create a probabilistic text entry toolkit, AAC user interfaces, and an augmented reality conversation assistant.

https://www.mtu.edu/news/stories/2018/may/keith-vertanen-wins-career-award.html



Computer Science Faculty Awarded ICC Seed Grant

Computer Science faculty members Keith Vertanen, Scott Kuhl, and Myounghoon “Philart” Jeon, were recently awarded the 2018 Paul Williams Seed Grant from the Institute of Computing and Cybersystems (ICC). The grant will give the researchers the opportunity to develop a research program that could be eligible and attractive for long-term and higher-level funding from external grants and contracts.

The projectCS_Fac_ICC_SeedGrant entitled, “Sensing and Feedback for On-Body Input,” will investigate how to appropriate everyday surfaces, including one’s own body, as an input device for interactive systems. In a series of user studies, they will compare the performance of the on-body sensing approach with vision-based hand tracking.

 


Dean’s Teaching Showcase: Ruihong Zhang

Per the article in Tech Today, this week, College of Sciences and Arts Dean Bruce Seely recognizes Ruihong Zhang, lecturer in Computer Science for more than 13 years, as the newest member of the Deans’ Teaching Showcase. Seely selected Zhang for her role in delivering foundational CS courses while enrollment has increased dramatically.

Asked to discuss her approach to teaching, Zhang says she finds herself balancing four pairs of ideas: her teaching goals vs. student learning goals; what she wants to teach vs. what students want to learn; her teaching style vs. student learning styles; and self-evaluation of teaching vs. student evaluations.

Zhang recently offered three foundational courses for CS majors: Data Structures, Databases and Introduction to Programming. None are easy. With its focus on different algorithms for structuring data, for example, Data Structures challenges students.

“During class, I constantly ask motivational questions, encouraging students to have short discussions with each other before presenting answers,” Zhang says.

The goal is to promote student engagement. Databases are equally essential, but this class is more practical and requires attention to detail. She relies upon lab sessions, not lectures, to “help students troubleshoot problems. They like these sessions and feel they learn a lot in one class period.”

Growing enrollment and larger class sections over the past three years have created serious teaching challenges, but Zhang has adapted in several ways. First, she begins the semester by asking students to introduce themselves and find a team partner. This enhances small-group work and short discussions. In each session, “I ask three to five interesting, but not too difficult, questions for students to approach as a team.”

After a few minutes, depending upon the problem, “I go over the answers or ask for responses from the teams. Many students actively participate and feel no pressure about giving wrong answers in front of the class.”

Zhang also has cut back on detailed PowerPoints, asking students to take their own notes. “Research shows that writing notes with paper and pencils helps people to retain knowledge.” Coincidentally, students must set aside electronic distractions to follow the discussion.

Because studeRuihong Zhangnts will not always ask questions in large classes, Zhang holds extra office hours and evening study sessions led by herself, student mentors or teaching assistants. “This semester we offered four weekly study sessions for Data Structures, led by mentors from the Computer Science Department’s new Student Academic Mentor (SAMs) program.”

Finally, Zhang is aware that different students have different skills and learning approaches and considers these when designing homework problems. “The problems have different levels of difficulty. I strive to use real life problems whenever it is appropriate. I often include challenging problems with extra points for students willing to study and work more after class.”

In summary, Seely indicates “This is the picture of a committed teacher constantly adjusting to changing conditions in her classes. The idea of balancing the potentially competing factors she identifies seems to be serving Ruihong’s students well.”

Zhang will be recognized at an end-of-term luncheon with other showcase members, and is now eligible for one of three new teaching awards to be given by the William G. Jackson Center for Teaching and Learning this summer, recognizing introductory or large-class teaching, innovative or outside-the-classroom teaching methods, or work in curriculum and assessment.