Assistant Professor Weihua Zhou, Applied Computing, will present a Chemistry department seminar on Friday, February 12, 2021, from 3:00 to 4:00 p.m. He will present ” Artificial intelligence for medical image analysis: our approaches.”
by Career Services
Michigan Tech’s Spring Career Fair is next week. We have 166 recruiting organizations registered so far. The event will be held virtually from 10 a.m. to 7 p.m. on Wednesday, Feb. 17.
Students can start registering for time slots to meet with company reps starting at 12:05 a.m. tomorrow (Feb. 11) on CareerFair Plus. We also encourage our first-year students to check out the group meetings at the fair, which are similar to company information sessions.
In preparation for the big day, we are hosting career fair prep workshops and events this week and next. Please pass this information on to your students and encourage them to register, as we have staff and recruiters who are eager to help prepare students for the fair.
Preparing for a Virtual Career Fair
- Wednesday, Feb. 10 | 4 to 5 p.m. via Zoom (passcode MTUPrepare)
Resume and Interview Blitz
What: Info Session: ICPC Programming Competition
When: Thursday, February 11, 6:00 to 7:00 p.m.
An information session about the ICPC Programming Competition will take place this Thursday, February 11, from 6:00 to 7:00 p.m.
ICPC Programming Competition, North America North Central Regionals, will be held, Saturday, February 27, 2021. The contest will be held remotely using the Kattis contest system and Zoom for team communication.
Practice contests will be organized prior to the event.
Please contact Associate Professor Laura Brown (email@example.com), Computer Science, with questions.
What are programming competitions?
Programming competitions are team events (groups of 3 students) that test student knowledge through the answering of programming questions, correctly and quickly. Top teams at the various events can go on to compete against top teams in the world.
Why do you want to participate?
The programming contest tests your skills against other teams and universities, helps in developing problem solving skills, and can aid in preparation for job interviews, offering practice in solving problems quickly.
When and how you can participate?
The programming contest is usually held in the Fall, but runs virtually in spring 2021. Student eligibility rules are listed here: https://icpc.baylor.edu/regionals/rules, which basically indicate that the student 1) can compete a maximum of five times at the regional levels, 2) started college in 2016 or later, and 3) was born 1997 or later. First year graduate students may be able to participate under these rules.
Students who are interested and eligible may sign up to form teams of up to three students.
If you are unable to attend the information session, please complete the form linked to below to indicate your interest, register teammates, or notify organizers that you are looking for teammates.
Fine more information and resources at https://bit.ly/3aLiu1O.
“My goal — nay our goal — is to make the College of Computing a place where everyone feels welcome and can thrive. And admittedly, I don’t know how to do that, which is why I am asking for your help.”
Dean Dennis Livesay wants to hear your story. What has your experience been with regard to diversity and inclusion at Michigan Tech?
What does the Dean need to be aware of as he starts his new position? What is working? What needs to change? How can we improve?
“My commitment to you, in this request and as dean, is that you will always have a forum to speak and be heard on topics of concern to you and our educational community,” Livesay says. “I will ask questions, listen to your responses, seek to understand your experiences, and proactively address your concerns.
Please reach out to Dean Livesay via email (firstname.lastname@example.org) if you’d like to schedule a time to talk.
“I know that speaking truth to power can be uncomfortable, so please feel free to bring a friend. Our conversation will be completely confidential,” Livesay stresses.
The paper, “Optimal-Time Dynamic Planar Point Location in Connected Subdivisions,” describes an optimal-time solution for the dynamic point location problem and answers an open problem in computational geometry.
The data structure described in the paper supports queries and updates in logarithmic time. This result is optimal in some models of computation. Nekrich is the sole author of the publication.
The annual ACM Symposium on Theory of Computing (STOC), is the flagship
conference of SIGACT, the Special Interest Group on Algorithms and
Computation Theory, a special interest group of the Association for
Computing Machinery (ACM).
by Graduate Student Government
Registration for this year’s virtual Graduate Research Colloquium (GRC) is open. Due to the continuation of the SARS-CoV-19 pandemic, the GRC will be held virtually on Thursday and Friday, April 1and 2.
The GRC is a great opportunity to work on your presentation skills and prepare for upcoming conferences. Students are free to give an oral presentation, a poster talk, or both. All talks will be scored by judges from the same field as the presenter.
Cash prizes are available for the top three places in both oral and poster presentations (1st – $300, 2nd – $200, and 3rd – $100). Registration closes Tuesday March 2, at 11:59 PM. Register today.
Poster presentations will take place in a pre-recorded video style. The deadline for video submission is Monday, March 22. A short Q&A session will take place with judges between 4-6 p.m. on April 1. Oral presentations are limited to 12 minutes plus a Q&A session.
The GRC will be capped off with a virtual awards ceremony. All participants and judges are invited to attend. The ceremony will be held on April 2, from 5-7 pm. Full information can be found on our website.
Feel free to contact Sarvada Chipkar if you have any questions or concerns.
by University Marketing and Communications
Read the Michigan Tech press release here. (Published Feb. 8, 2021)
Michigan Technological University has appointed Dennis Livesay to hold the inaugural Dave House Deanship in the College of Computing effective February 1, 2021.
Michigan Tech launched the College in 2019 to meet the technological, economic and social needs of the 21st century, and answer industry demand for talent in artificial intelligence (AI), software engineering, data science and cybersecurity. In doing so, Tech became the first University in the state with a college of computing.
The gift from Dave House ’65 to endow the dean position reinforces the University’s commitment to computing.
“The College of Computing is central to the future of Michigan Tech. Thanks, in part, to Dave’s visionary gift and Dennis’s leadership, the college is poised for tremendous success on both the national and international stage,” said Rick Koubek, President.
House, whose many career accolades include growing Intel’s microprocessor product business from $40 million to $4 billion per year, has championed Michigan Tech’s efforts in computing.
“Computing is centric to all disciplines, and Michigan Tech has been wise to move forward with a focus on computing,” said House. “This endowed position will allow the new college to attract the best faculty and the brightest students and the University to continue to be the leader in computing education.”
Livesay, who most recently served as dean of the College of Engineering at Wichita State University, brings 20 years of experience in higher education to Michigan Tech. With a diverse background spanning the biomedical sciences, computing and engineering, he plans to work with partners across campus to address the digital transformation happening in every discipline.
Provost Jackie Huntoon stated she is very happy that Livesay is joining Michigan Tech. “His deep understanding of computing and its impact on all aspects of modern life make him well suited for the deanship of the College of Computing,” she said. “He brings an entrepreneurial perspective to the dean’s role that will enhance efforts currently underway in the College of Computing and across campus.”
Livesay shares House’s conviction that computing is fundamental to all disciplines.
“Every discipline is a computing discipline,” said Livesay. “When I first started saying this a decade ago, it was more of a tagline, but it is absolutely true today. The modern economy is defined by our ability to create data, transmit it in a secure way and then translate it into action. This is particularly true in science, engineering and business, but also in the social sciences, humanities and the arts. Going forward, we want to be a critical partner in all of those areas.”
The Dave House Dean of Computing is Michigan Tech’s first endowed deanship. The University has nine endowed department chairs and dozens of endowed faculty positions, allowing it to maintain a world-class faculty.
“We thank Dave again for his vision and commitment to Michigan Tech’s future. We are indeed fortunate to have alumni like him who care so deeply for our students,” said Bill Roberts, Vice President for Advancement and Alumni Engagement.
View the announcement below about the new deanship from a recent meeting of the Michigan Tech Alumni Board.
Dave House Deanship in the College of Computing Announced
Her talk is titled, “Multiple Instance Learning for Plant Root Phenotyping.”
Dr. Zare is a professor in the Electrical and Computer Engineering department at University of Florida. She teaches and conducts research in the areas of pattern recognition and machine learning.
Multiple Instance Learning for Plant Root Phenotyping
In order to understand how to increase crop yields, breed drought tolerant plants, investigate relationships between root architecture and soil organic matter, and explore how roots can play in a role in greenhouse gas mitigation, we need to be able to study plant root systems effectively. However, we are lacking high-throughput, high-quality sensors, instruments and techniques for plant root analysis. Techniques available for analyzing root systems in field conditions are generally very labor intensive, allow for the collection of only a limited amount of data and are often destructive to the plant. Once root data and imagery have been collected using current root imaging technology, analysis is often further hampered by the challenges associated with generating accurate training data.
Most supervised machine learning algorithms assume that each training data point is paired with an accurate training label. Obtaining accurate training label information is often time consuming and expensive, making it infeasible for large plant root image data sets. Furthermore, human annotators may be inconsistent when labeling a data set, providing inherently imprecise label information. Given this, often one has access only to inaccurately labeled training data. To overcome the lack of accurately labeled training, an approach that can learn from uncertain training labels, such as Multiple Instance Learning (MIL) methods, is required. In this talk, I will discuss our team’s approaches to characterizing and understanding plant roots using methods that focus on alleviating the labor intensive, expensive and time consuming aspects of algorithm training and testing.
Dr. Zare earned her Ph.D. in December 2008 from the University of Florida. Prior to joining the faculty at the University of Florida in 2016, she was a faculty member at the University of Missouri.
Zare’s research has focused primarily on developing machine learning and pattern recognition algorithms to autonomously understand and process non-visual imagery. Her research work has included automated plant root phenotyping using visual and X-ray imagery, 3D reconstruction and analysis of X-ray micro-CT imagery, sub-pixel hyperspectral image analysis, target detection and underwater scene understanding using synthetic aperture sonar, LIDAR data analysis, Ground Penetrating Radar analysis, and buried landmine and explosive hazard detection.
by Center for Educational Outreach
Since 1972, Summer Youth Programs (SYP) at Michigan Tech has offered students in grades 6-11 a variety of hands-on explorations in engineering, science, technology, computer science, business, design, and the humanities.
From college and career discovery to academic immersion, SYP is a fantastic mini college experience that packs a ton of learning, experimenting, and fun into each day.
Around 50 programs are offered, along with several scholarship opportunities, and run weekly from June 20-Aug. 7.
In addition, if any Michigan Tech staff or faculty have children in college (other universities welcome) that are interested in learning more about our summer staffing opportunities on campus please visit the employment page of our website.
The Department of Computer Science will present a lecture by Dr. Elizabeth Veinott on Friday, February 12, 2021, at 3:00 p.m.
Veinott is an associate professor in the Cognitive and Learning Sciences department. She will present, “Beyond the system interface: Using human-centered design to support better collaborative forecasting.”
Elizabeth Veinott is a cognitive psychologist working in technology-mediated environments to improve decision making, problem solving and collaboration. She directs Michigan Tech’s Games, Learning and Decision Lab and is the lead for the Human-Centered Computing group of Michigan Tech’s Institute of Computing and Cybersystems (ICC).
She has been active in the ACM’s SIGCHI and on the conference organizing committees for CHI Play and CSCW. Prior to joining Michigan Tech in 2016, she worked as a principal scientist in an industry research and development lab and as a contractor at NASA Ames Research Center. Her research has been funded by NIH, Army Research Institute, Army Research Lab, Air Force Research Laboratory, and IARPA.
Teams use technology to help them make judgments in a variety of operational environments. Collaborative forecasting is one type of judgment performed by analyst teams in weather, business, epidemiology, and intelligence analysis. Research related to collaborative forecasting has produced mixed results.
In her talk, Veinott will describe a case of using cognitive task analysis to develop and evaluate a new forecast process and tool. The method captured analysts’ mental models of game-based forecasting problems, and allowed the process to co-evolve with the system design. The tool was tested in a simulation environment with expert teams conducting analyses over the course of hours and compared to a control group. Challenges and lessons learned will be discussed, including implications for human-centered design of collaborative tools.