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 (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.
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:
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.
The Daily Mining Gazette, Houghton, MI, ran the article, “MTU launches College of Computing,” on the front page of the paper on October 18, 2019. The article quotes Dean Adrienne Minerick and alumnus Dave House.
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.
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.
Dr. Timothy Wilkin, associate professor of computer science and associate head of school (student learning) within the School of Information Technology, Deakin University, Australia, will present a talk at Michigan Tech on Monday, October 7, from 4:00-5:00 p.m., in ME-EM 112. A reception and refreshments will follow.
Dr. Wilkin’s talk, “Adventures of a Cyber-Physical Cow,” will present findings from his recent industry-based research into the use of wearable technologies in livestock farming.
Talk Abstract: Fitness and activity trackers, and other wearable sensors have revolutionised both professional sports and the general health & wellbeing market. On the other hand, wearables to support precision livestock farming and general animal health and wellbeing tracking are virtually non-existent. There are significant opportunities to support and grow concepts such as “paddock to plate” food provenance, particularly in the meat and livestock sector, through the use of wearable technologies. In this talk I will present some recent industry-based research between Deakin University and Agersens Pty Ltd, an Australian manufacturer of a world-leading geofencing technology for livestock. Real-time behaviour classification and analytics were used to both improve the existing product, as well as to create new data products for farmers and a greatly enhanced marketability for their smart collar. I will also highlight how this industry-based research has led to several interesting and challenging research questions that have driven ongoing fundamental research in data science at Deakin.
Dr. Wilkin’s Bio: Dr Wilkin’s research interests cover problems in computational and artificial intelligence to support sensor and data analytics, with applications in intelligent control for robotics and autonomous systems, embedded/edge AI, and intelligent sensing. His research has been applied in diverse areas, from marine ecology to childhood health, farming, defence and commercial robotics. Dr Wilkin is also an innovative, award-winning teacher and academic leader. As Associate Head of School he overseas teaching and learning activities of over 100 full-time academic staff and 3500 students enrolled in 16 undergraduate and postgraduate programs.
Charles Wallace, Associate Professor of Computer Science and member of the ICC’s Center for Human-Centered Computing, has been appointed Associate Dean for Curriculum and Instruction for the College of Computing, effective immediately. Wallace has been teaching in the Department of Computer Science for 19 years, and he has a long track record of education research and building collaboration with Cognitive & Learning Sciences, Engineering, Humanities, and Social Sciences.
“Chuck brings to his new role an extensive breadth of experience that spans from outreach to curricular development to collaborations with multiple units across campus,” says Adrienne Minerick, dean of the College of Computing. “In this new role, he will help build campus collaborations to create additional pathways for Michigan Tech students to engage with computing curricula, and facilitate conversations within the College of Computing that enable creative, agile options for our students.”
“Barriers between computing and other disciplines are artificial and unproductive,” Wallace says. “Computing competencies are essential for Michigan Tech graduates in all fields, and the College and University should commit to building educational options housed in the College of Computing but available and accessible to all students.”
Wallace adds that students in the College of Computing should be free – and actively encouraged – to explore application areas where their skills can be used. He also wants to explore ways to build flexibility into Computing academic programs, maintaining the solid technical core that Michigan Tech graduates are known for, but also allowing students to pursue applications of their computing competencies in other disciplines.
Vision Statement from Charles Wallace:
Here are a few points that I consider vital to the future of computing education, based on 19 years of experience in the Computer Science Department, a long track record of education research, and extensive collaboration with Cognitive & Learning Sciences, Engineering, Humanities, and Social Sciences.
Barriers between computing and other disciplines are artificial and unproductive. Computing competencies are essential for Michigan Tech graduates in all fields. The College and University should commit to building educational options housed in the College of Computing but available and accessible to all students. This will require an earnest and focused investment in personnel – we cannot do it solely with the current cohort of instructors, who are already stretched thinly with increased enrollment in core computing programs.
Conversely, students in the College of Computing should be free and even encouraged to explore application areas where their skills can be brought to bear. Complex degree requirements can hinder such exploration. We should explore ways to build flexibility into our programs, maintaining the solid technical core that Michigan Tech graduates are known for, but also allowing students to pursue applications of their computing competencies in other disciplines.
Computing students are citizens, not just producers. The degree programs in Michigan Tech’s Computer Science Department have a long and venerable tradition of preparing students who can “produce” – hit the ground running in the workplace and build high quality solutions. That is a precious gift, and we should not deprive future students of it – but the future demands more. Our world is increasingly dominated by computing – and by extension, dominated by human beings who understand computing. Michigan Tech graduates of the College of Computing must be known not only for the technical “value” that they produce, but also the ability to question and critique digital technology, to be empathetic and articulate ambassadors and leaders in the new digital order of the future.
There are two promising ways in which we can build better computing citizens. First, an awareness of the social and ethical consequences of computing must be woven into our curricula, not just taught as external service courses. Second, service learning is a way to expose students to the human contexts of computing technology. There are many ways to get students involved in our community, but these have not been harnessed outside of ad hoc outreach efforts. Interaction with the community should be built into the academic experience of computing students.
Computing competencies include values and attitudes, not just skills and knowledge. Alumni of our degree programs acknowledge that collaboration and communication are essential components of their professional lives. These competencies involve not only skills but also values and attitudes – willingness and even eagerness to engage with others, resilience in the face of uncertainty or ambiguity, and adaptability in the face of changing requirements. To prepare students for the highly collaborative computing workplace, courses in the College of Computing should embrace the opportunities and challenges of working in diverse teams. As with ethics, issues of teamwork and communication must be integrated into “disciplinary” courses, not left to service courses or external experiences like internships.
These curricular pathways hold promise not only to develop competent computing professionals of the future, but also to attract a more diverse constituency to the College of Computing student body.
An article by Mark Rouleau, associate professor of social sciences and member of the ICC’s Center for Data Sciences, was recently published in the journal Landscape and Urban Planning, published by Elsevier. The article, titled, “Agent-based modeling for bioenergy sustainability assessment,” is co-authored by Robert J. Zupko II.
Article Abstract: Woody biomass bioenergy is an important renewable alternative to conventional fossil fuels. However, the negative land-use change impacts of biomass harvesting necessary for bioenergy production can potentially outweigh its positive benefits if poorly managed. In this paper, we explain how Agent-Based Modeling (ABM), a form of computer simulation, can be used to conduct a comprehensive bioenergy sustainability assessment to identify possible gains and trade-offs necessary to develop bioenergy in regions with large numbers of private family forest owners or smallholders who own a significant share of available biomass. We discuss how ABM simulation can overcome the barriers of existing sustainability assessment tools and provide a demonstration of the sustainability assessment capabilities of an ABM using a hypothetical case study that explores the introduction of a bioenergy conversion facility in the Western Upper Peninsula of Michigan, United States. We conduct a series of alternative futures scenarios and compare the sustainability outcomes of three alternative policy regimes using voluntary incentive programs to encourage smallholders to harvest biomass.