All posts by karenjoh

ACSHF Forum Monday

Beth Veinott

One challenge affecting a variety of teams, such as software development, engineering, military, and crisis management, is overconfidence in the effectiveness of their plans.  Referred to as the planning fallacy, Buehler et al. (1994) suggests that ignoring past failures is a key cognitive element in this phenomenon. This talk summarizes recent experiments examinin the effect of counterfactual reasoning strategies, thinking about what might have happened under different circumstances, on people’s reasons, confidence and predictions.

Leveraging a collaborative, structured analytic technique called the Premortem, this project extends research on counterfactual reasoning to estimates in planning. The results will be discussed in the context of advances in machine learning, AI, and crowdsourcing that have changed the information available to teams.


Chee-Wooi Ten is PI of R and D Agreement with University of California Riverside

Chee-Wooi Ten

Chee-Wooi Ten (ECE), a member of Michigan Tech’s Center for Agile and Interconnected Microgrids and the ICC’s Center for Cyber-Physical Systems, is the principal investigator on a 17-month project that has received a $99,732 research and development cooperative agreement with the University of California Riverside. The project is entitled, “Discovery of Signatures, Anomalies, and Precursors in Synchrophasor Data with Matrix Profile and Deep Recurrent Neural Networks.”


“The Bit Player,” a documentary about Claude Shannon, Is Sunday, November 3

The College of Computing, the Institute of Computing and Cybersystems, and the Department of Electrical and Computer Engineering are sponsors of a showing of the film, “The Bit Player,” during this week’s 41 North Film Festival at the Rozsa Center. The showing is this Sunday, November 3, at 3:30 pm. There is no charge to attend, but film-goers are encouraged to secure tickets online and at the Rozsa Center box office. (mtu.edu/rozsa/ticket/calendar/)
“The Bit Player” is a documentary about  Claude Shannon, the father of information theory and a hero to many in electrical engineering, computer engineering, and computer science. Claude Shannon was born in Gaylord, Michigan, on April 30, 1916. He attended University of Michigan, double majoring in mathematics and electrical engineering. His MIT master’s thesis was titled, “A Symbolic Analysis of Relay and Switching Circuits,” which related electric circuits and their on/off character to Boolean Algebra, the “Mathematics of Logical Thought,” laying the foundation for machines to make decisions — “to think.”
This was the first documentary film funded by the IEEE Foundation, and it was done in conjunction with the IEEE Information Theory Society (ITS). The ITS is the only IEEE society whose “basis” has a definitive starting date – the 1948 publication of Shannon’s A Mathematical Theory of Communication <http://math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf>
More information about this film can be found at http://41northfilmfest.mtu.edu/2019/the-bit-player/.
Claude Shannon

A description from the film’s official website https://thebitplayer.com): “In a blockbuster paper in 1948, Claude Shannon introduced the notion of a “bit” and laid the foundation for the information age. His ideas ripple through nearly every aspect of modern life, influencing such diverse fields as communication, computing, cryptography, neuroscience, artificial intelligence, cosmology, linguistics, and genetics. But when interviewed in the 1980s, Shannon was more interested in showing off the gadgets he’d constructed — juggling robots, a Rubik’s Cube solving machine, a wearable computer to win at roulette, a unicycle without pedals, a flame-throwing trumpet — than rehashing the past. Mixing contemporary interviews, archival film, animation and dialogue drawn from interviews conducted with Shannon himself, The Bit Player tells the story of an overlooked genius who revolutionized the world, but never lost his childlike curiosity.”


Bo Chen Weighs In on Identity Fraud in WalletHub Article

Bo Chen, Computer Science

Bo Chen (CS/CyberS) was featured in the article “2019’s States Most Vulnerable to Identity Theft & Fraud,” published October 16, 2019, in WalletHub.

Link to the article here:https://wallethub.com/edu/states-where-identity-theft-and-fraud-are-worst/17549/#expert=bo-chen

Based in Washington DC, WalletHub is the first-ever website to offer free credit scores and full credit reports that are updated on a daily basis. The company also hosts an artificially intelligent financial advisor that provides customized credit-improvement advice, personalized savings alerts, and 24/7 wallet surveillance, supplemented by reviews of financial products, professionals and companies.


Benjamin Ong Is PI on NSF Grant that Supports June 2020 Parallel-in-Time Conference

Benjamin Ong

Benjamin Ong (Math/ICC-DataS) is the principal investigator on a one-year project that has received a $36,636 other sponsored activities grant from the Mathematical Sciences Infrastructure Program at National Science Foundation. The project is entitled, “CBMS Conference: Parallel Time Integration.”

The award provides support for the NSF-CBMS Conference on Parallel Time Integration, to be held June 1-5, 2020, at Michigan Tech. The focus of the conference is to educate and inspire researchers and students in new and innovative numerical techniques for the parallel-in-time solution of large-scale evolution problems on modern supercomputing architectures, and to stimulate further studies in their analysis and applications.

Co-organizing the conference with Ong is Jacob B. Schroder, assistant professor in the Dept. of Mathematics and Statistics at University of New Mexico.

The conference will feature ten lectures by Professor Martin Gander, an expert in parallel time integration and a professor at the University of Geneva, Switzerland. Using appropriate mathematical methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretizations, integration techniques, and convergence analyses of these iterative methods, conference participants will be exposed to the numerical analysis of parallel-in-time methodologies and their implementations. The proposed topics include multiple shooting type methods, waveform relaxation methods, time-multigrid methods, and direct time-parallel methods. These lectures will be accessible to a wide audience from a broad range of disciplines, including mathematics, computer science and engineering.

Visit the conference website at http://conferences.math.mtu.edu/cbms2020/.


Benjamin Ong Awarded 2019-2020 Kliakhandler Fellowship

Benjamin Ong

Benjamin Ong (Math/ICC-DataS) has been awarded the Michigan Tech Department of Mathematics 2019-2020 Kliakhandler Fellowship, which will support two parallel-in-time conferences being held at Michigan Tech in June 2020.  As Kliakhandler Fellow, Ong will receive a $5,000 stipend, plus $10,000 to organize a workshop or conference at Michigan Tech.

The purpose of the Kliakhandler Fellowship is to stimulate research activity in the Michigan Tech Department of Mathematics. Awarded annually, the Kliakhandler Fellow is chosen based on a record of excellence in research and the potential of the proposed workshop to stimulate further research achievements and bring visibility to Michigan Tech and the Department of Mathematical Sciences.

Ong, along with Jacob B. Schroder, assistant professor in the Dept. of Mathematics and Statistics at University of New Mexico, is organizing two conferences to take place at Michigan Tech in June 2020. The first, “The CBMS Conference – Parallel Time Integration,” will take place June 1-5, 2020. The focus of this parallel-in-time workshop is to educate and inspire researchers and students in new and innovative numerical techniques for the parallel-in-time solution of large-scale evolution problems on modern supercomputing architectures, and to stimulate further studies in their analysis and applications.  The conference will feature ten lectures by Professor Martin Gander, an expert in parallel time integration and a professor at the University of Geneva, Switzerland.

The second conference, 9th Workshop on Parallel-in-Time Integration,” takes place June 8-12, 2020. The workshop the workshop will bring together an interdisciplinary group of experts to disseminate cutting-edge research and facilitate scientific discussions on the field of parallel time integration methods.
Igor Kliakhandler, a former Michigan Technological University mathematics faculty member, was born in Moscow, Russia in 1966. He graduated from the Moscow Oil and Gas Institute in 1983 and started his PhD studies there in 1988. He then emigrated with his family to Israel in 1991 and began his PhD at Tel-Aviv University under the guidance of Gregory Sivashinsky. He received his PhD in Applied Mathematics in 1997 from Tel-Aviv University. He held positions at Universidad Complutense de Madrid, Lawrence Berkeley National Laboratory and Northwestern University before joining Michigan Tech’s Department of Mathematical Sciences as an assistant professor in 2001. He was promoted to associate professor in 2005 and left the University in 2007 to work in the energy sector in Houston. He manages a group of companies that trade electric power across US, and is involved in a few start-up projects. Igor remained fond of Michigan Tech and its Math Department. Kliakhandler provides a generous gift to host the Kliakhandler Conference, an annual event at Michigan Tech to stimulate research activity in the mathematical sciences.

Link to more information about the two conferences at:

http://conferences.math.mtu.edu/cbms2020, June 1-5 2020

http://conferences.math.mtu.edu, June 8 – 12, 2020


TV6 Features Story on Computing Week October 17

WLUC TV6 aired the story, “Michigan Tech holds first Computing Week,” on October 17, 2019. College of Computing Dean Adrienne Minerick and Timothy Havens, the William and Gloria Jackson Associate Professor of Computer Systems and director the Institute of Computing and Cybersystems, were interviewed for the story, which includes film footage from the Computing Open House of Thursday, October 17.

View the video here: https://www.uppermichiganssource.com/content/news/Michigan-Tech-holds-first-Computing-Week-563325232.html.



MTRI to Present Research Seminars October 14

The Institute of Computing and Cybersystems will present four brief seminars by researchers from the Michigan Tech Research Institute (MTRI) on Monday, October 14, 2019, 11:00 a.m. to 12:00 p.m., in EERC 122.  MTRI research and outreach focuses on the development of technology to sense and understand natural and manmade environments.

Sarah Kitchen is a mathematician with background in algebraic geometry and representation theory. Her recent research interests include algebraic structures underlying optimization problems and applications of emerging statistical tools to signal processing and source separation problems. Her talk, “Collaborative Autonomy,” will discuss some considerations in centralized, semi-centralized, and decentralized decision-making methods for autonomous systems.

Susan Janiszewski is a mathematician specializing in graph theory and combinatorics. Her research interests lie in applying concepts from discrete mathematics to machine learning, computer vision, and natural language processing. Her talk, “Combining Natural Language Processing and Scalable Graph Analytics,” takes up the fast-growing field of Natural Language Processing (NLP), i.e. the development of algorithms to process large amounts of textual data. Janiszewski will discuss ways to combine common NLP and graph theoretic algorithms in a scalable manner for the purpose of creating overarching computational systems such as recommendation engines or machine common sense capabilities.

Joel LeBlanc has 10 years of experience in statistical signal processing. His research interests include information theoretic approaches to inverse imaging, and computational techniques for solving large inverse problems. LeBlanc’s talk, “Testing for Local Minima of the Likelihood Using Reparameterized Embeddings,” addresses the question: “Given a local maximum of a non-linear and non-convex log-likelihood equation, how should one test for global convergence?” LeBlanc will discuss a new strategy for identifying globally optimal solutions using standard gradient-based optimization techniques.

Meryl Spencer is a physicist with a background in complex systems and network theory. Her research interests include machine learning for image processing, applications of graph algorithms, and self-organization. Her talk, “Computational modeling of collaborative multiagent systems,” will discuss her previous work on modeling self organization in cellular networks, and some areas of interest for future work.

Download the event flyer.


Anna Little to Present Talk October 18, 1 p.m.

Anna Little

Dr. Anna Little, a postdoc in the Department of Computational Mathematics, Science, and Engineering at Michigan State University, will present her talk, “Robust Statistical Procedures for Clustering in High Dimensions,” on Friday, October 18, 2019, at 1:00 p.m., in Fisher Hall Room 327B.

Dr. Little completed a PhD in mathematics at Duke University in 2011. She has been at Michigan State since 2018.  Visit her website at www.anna-little.com.

Lecture Abstract: This talk addresses multiple topics related to robust statistical procedures for clustering in high dimensions, including path-based spectral clustering (a new method), classical multidimensional scaling (an old method), and clustering in signal processing. Path-based spectral clustering is a novel approach which combines a data driven metric with graph-based clustering. Using a data driven metric allows for fast algorithms and strong theoretical guarantees when clusters concentrate around low-dimensional sets.

Another approach to high-dimensional clustering is classical multidimensional scaling (CMDS), a dimension reduction technique widely popular across disciplines due to its simplicity and generality. CMDS followed by a simple clustering algorithm can exactly recover all cluster labels with high probability when the signal to noise ratio is high enough. However, scaling conditions become increasingly restrictive as the ambient dimension increases, illustrating the need for robust unbiasing procedures in high dimensions.  Clustering in signal
processing is the final topic; in this context each data point corresponds to a corrupted signal. The classic multireference alignment problem is generalized to include random dilation in addition to random translation and additive noise, and a wavelet based approach is used to define an unbiased representation of the target signal(s) which is robust to high frequency perturbations.

Download the event flyer.