Category: News

Dr. Dukka KC, Wichita State, to Present Talk May 5


Dr. Dukka KC, Electrical Engineering and Computer Science, Wichita State University, will present a talk on Wednesday, May 5, 2021, at 3:00 p.m.

Dr. KC will discuss some past and ongoing projects in his lab related to machine learning/deep learning-based approaches for an important problem in Bioinformatics: protein post-translational modification.

Join the virtual talk here.

Talk Title

Bioinformatics as an emerging field of Data Science: Protein post-translation modification prediction using Deep Learning

Talk Abstract

In this talk, I will be presenting about some of the past and ongoing projects in my lab especially related to Machine Learning/Deep Learning based approaches for one of the important problems in Bioinformatics – protein post-translational modification.

Especially, I will focus on our endeavors to get away from manual feature extraction (hand-crafted feature extraction) from protein sequence, use of notion of transfer learning to solve problems where there is scarcity of labeled data in the field, and stacking/ensemble-based approaches.

I will also summarize our future plans for using multi-label, multi-task and multi-modal learning for the problem. I will highlight some of the ongoing preliminary works in disaster resiliency. Finally, I will provide my vision for strengthening data science related research, teaching, and service for MTU’s college of computing.

Biography

Dr. Dukka KC is the Director of Data Science Lab, Director of Data Science Efforts, Director of Disaster Resilience Analytics Center and Associate Professor of Electrical Engineering and Computer Science (EECS) in the Department of EECS at Wichita State University. His current efforts are focused on application of various computing/data science concepts including but not limited to Machine Learning, Deep Learning, HPC, etc. for elucidation of protein sequence, structure, function and evolution relationship among others.

He has received grant funds totaling $4.25M as PIs or Co-PIs, spanning 17 funded grants. He was the PI on the $499K NSF Excellence in Research project focused on developing Deep Learning based approaches for Protein Post-translational modification sites.

He received his B.E. in computer science in 2001, his M.Inf. in 2003 and his Ph.D. in Informatics (Bioinformatics) in 2006 from Kyoto University, Japan. Subsequently he did a postdoc at Georgia Institute of Technology working on refinement algorithms for protein structure prediction. He then moved to UNC-Charlotte and did another postdoc working on functional site predictions in proteins. He was a CRTA Fellow in National Cancer Institute at National Institutes of Health where he was working on intrinsically symmetric domains.

Prior to his arrival at WSU, he was associate professor and graduate program director in the Department of Computational Science and Engineering at North Carolina A&T State University.

Dr. KC has published more than 30 journal and 20 conference papers in the field and is associate editor for two leading journals (BMC Bioinformatics and Frontiers in Bioinformatics) in the field. He also dedicates much of his efforts to K-12 education, STEM workforce development, and increasing diversity in engineering and science.


Students Place in ICPC Programming Championships


A team of Michigan Tech students competed last week in the International Collegiate Programming Contest (ICPC) North America Division Championships, placing 28th out of 42 teams in the Central Division.

To qualify for the Championships, a Michigan Tech student team placed 14th out of more than 80 teams in the regional ICPC contest this February. Students on that team were Alex Gougeon (Software Engineering), Ben Wireman (Mathematics), and Dominika Bobik.

Students interested in the programming competitions are encouraged to contact Dr. Laura Brown, Computer Science. Additional programming contests and events take place throughout the year.

The International Collegiate Programming Contest is the premier world-wide, algorithmic programming contest for college students.

In ICPC competitions, teams of three students work to solve the most real-world problems efficiently and correctly. Teams represent their university in multiple levels of competition: regionals, divisionals, championships, and world finals.


Dr. Ali Yekkehkhany to Present Talk May 6


Dr. Ali Yekkehkhany, a postdoctoral scholar at the University of California, Berkeley, will present a talk on Thursday, May 6, 2021, at 3:00 p.m.

He will discuss adversarial attacks on the computation of reinforcement learning and risk-aversion in games and online learning.

Dr. Yekkehkhany’s research interests include machine/reinforcement learning, queueing theory, applied probability theory and stochastic processes.

Join the virtual talk here.

Talk Title

Adversarial Reinforcement Learning, Risk-Averse Game Theory and Online Learning with Applications to Autonomous Vehicles and Financial Investments

Talk Abstract

In this talk, we discuss:

  • a) Adversarial attacks on the computation of reinforcement learning: The emergence of cloud, edge, and fog computing has incentivized agents to offload the large-scale computation of reinforcement learning models to distributed servers, giving rise to edge reinforcement learning (RL). By the inherently distributed nature of edge RL, the swift shift to this technology brings a host of new adversarial attack challenges that can be catastrophic in safety-critical applications. A natural malevolent attack could be to contaminate the RL computation such that the contraction property of the Bellman operator is undermined in the value/policy iteration methods. This can result in luring the agent to search among suboptimal policies without improving the true values of policies. We prove that under certain conditions, the attacked value/policy iteration methods converge to the vicinity of the optimal policy with high probability if the number of value/policy evaluation iterations is larger than a threshold that is logarithmic in the inverse of a desired precision.
  • b) Risk-aversion in games and online learning: The fast-growing market of autonomous vehicles, unmanned aerial vehicles, and fleets in general necessitates the design of smart and automatic navigation systems considering the stochastic latency along different paths in a traffic network. To our knowledge, the existing navigation systems including Google Maps, Waze, MapQuest, Scout GPS, Apple Maps, and others are based on minimizing the expected travel time, ignoring the path delay uncertainty. To put the travel time uncertainty into perspective, we model the decision making of risk-averse travelers in a traffic network by an atomic stochastic congestion game and propose three classes of risk-averse equilibria. We show that the Braess paradox may not occur to the extent presented originally and the price of anarchy can be improved, benefiting the society, when players travel according to risk-averse equilibria rather than the Wardrop/Nash equilibrium. Furthermore, we extend the idea of risk-aversion to online learning; in particular, risk-averse explore-then-commit multi-armed-bandits. We use data from the New York Stock Exchange (NYSE) to show that the classical mean-variance and conditional value at risk approaches can come short in addressing risk-aversion for financial investments. We introduce new venues to study risk-aversion by taking the probability distributions into account rather than the summarized statistics of distributions.

Biography

Ali Yekkehkhany is a postdoctoral scholar with the Department of Industrial Engineering and Operations Research, University of California, Berkeley. He received his PhD and MSc degrees in Electrical and Computer Engineering from the University of Illinois, Urbana-Champaign (UIUC) in 2020 and 2017, respectively, and BSc degree in Electrical Engineering from Sharif University of Technology in 2014.

He is the recipient of the “best poster award in recognition of high-quality research, professional poster, and outstanding presentation” in the 15th CSL Student Conference, 2020, and the “Harold L. Olesen award for excellence in undergraduate teaching by graduate students” in the 2019-2020 academic year at UIUC. He was chosen as “teachers ranked as excellent” twice and “teachers ranked as excellent and outstanding” twice at UIUC.

His research interests include machine/reinforcement learning, queueing theory, applied probability theory and stochastic processes.


EET Senior Design Project on TV 6


The Senior Design project completed this semester by four senior-level Electrical Engineering Technology (EET) is the topic of a news story that was aired on WLUC-TV6 (Marquette) on Friday, April 23, 2021. The project was to design and produce a motorized swing set that will help a disabled child enjoy herself and sleep comfortably.

Read an article about the EET students’ project here.

View the TV6 news story here.

The students are Joe Barbercheck, Seth Cherry, Heather Harris, and Cole Kubick.

Tackling the project top to bottom, the students designed the electrical system, control and drive systems, and portions of the mechanical design. Their top priority was making sure the systems and mechanical structure are safe.

Specifications for the swing include that it be lightweight, reliable, and portable. The unit is battery-operated with a rechargeable lithium-ion battery. The swing will both rock the child to sleep and serve as a play toy for three to four years, although the actual lifetime of the swing will be much longer.

Professor Alex Sergeyev and Lecturer Paniz Hazaveh are co-advisors to the team. “The students are very excited about the project,” Sergeyev says. “It’s very meaningful to them.”

“The skills that we are teaching in the EET and Mechatronics undergraduate programs makes students able to just jump on these kinds of projects,” Sergeyev says. “It’s great to see that their learning can be applied to a project as complex as this one.”



Fall Career Fair Will Be Virtual

by Career Services

Michigan Tech’s 2020 Fall Career Fair was—literally—a virtual success. We’re carrying forward the convenience, safety and ease of participation for employers and students with a virtual format in Fall 2021.

We’ll be hosting it on Career Fair Plus again, with registration through Handshake.

Registration for employers will open in June.


Spend 1010 with Dr. Brian Yuan, April 29


You are invited to spend one-zero-one-zero—that is, ten—minutes with Dr. Brian Yuan on Thursday, April 29, at 4:30 p.m. EST.

Dr. Yuan is an assistant professor in both the Applied Computing and Computer Science departments. His areas of expertise include machine learning, security and privacy, and cloud computing.

Yuan will discuss his research, the Applied Computing and Computer Science departments, and answer questions.

Dr. Yuan earned his PhD in Computer Science at University of Florida.

We look forward to spending 1010 minutes with you!

Visit the 1010 with … webpage here.