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    Hoda Hatoum to Present Biological Sciences Seminar September 16


    by Biological Sciences

    Hoda Hatoum (BioMed, ICC-BDH) will present Thursday (Sept. 16) at 3 p.m. as part of the Biological Sciences Seminar Series. The presentation will be held virtually on Zoom.

    From the abstract: Transcatheter aortic valve replacement (TAVR) is a non-invasive valve replacement therapy that has been recently FDA approved for low-risk patients. Despite the importance of this therapy, TAVR has been associated with several adverse effects and long-term adverse outcomes such as short durability and thrombus formation. Several clinical studies showed that the incidence of leaflet thrombosis (LT) post-TAVR ranges between 8 to 24% overall, with increasing incidences from 30 day to 1-year timepoints, which makes leaflet thrombosis a highly important concern. … The purpose of this study is to present a semi-empirical, mathematical model that links patient-specific anatomic, valve, and flow parameters to predict leaflet thrombosis. This tool will be essential in clinical pre-procedural planning. To this end, we used a combination of experimental, analytical, and computational fluid dynamic studies along with patient-specific data.


    Open House for Centers, Institutes and Shared Facilities

    by Office of the Vice President for Research

    On behalf of the Associate Vice President for Research Development (AVPRD) Office, we invite scholars, creators and researchers to attend the upcoming Open House for Centers, Institutes and Shared Facilities on Sept. 10 from 1-5 p.m. in MUB Ballroom A.

    The open house will immediately follow the President’s Welcome Back Picnic at the Rozsa Center. People are welcome to bring their lunches over from the picnic and finish them in the ballroom.

    The event will feature two-minute “Tech Talks” from center, institute and shared facility directors, providing attendees with an opportunity to learn about the mission and research interests of Michigan Tech’s variety of research areas and facilities.

    After the introductions, guests will have the opportunity to tour the centers, institutes or shared facilities that interest them; meet with other members and users; and learn more about how these organizations can support their work.

    The afternoon will conclude with an informal reception at Rovano Plaza (the outdoor area next to the Library) from 4-5 p.m. where researchers and directors can continue conversations.

    For more information or a calendar invitation, please contact Brent Burns at bburns@mtu.edu.

    Thank you for considering attending this important event, which is intended to help you network with others on campus and assist you with gaining access to the resources and assistance that Michigan Tech’s centers, institutes and shared facilities provide.


    ICC Distinguished Lecture: Dr. Doina Caragea, Kansas State University

    The Institute of Computing and Cybersystems will present a Distinguished Lecture by Dr. Doina Caragea on Friday, October 29, 2021, at 3:00 p.m. Dr. Caragea is a professor and the Michelle Munson-Serban Simu Keystone Research Scholar in the Computer Science department at Kansas State University. Her talk is itiled, “Mining Social Media to Aid Disaster Response.”

    Join the Zoom lecture here: https://michigantech.zoom.us/j/81088119467

    Dr. Caragea has expertise in machine learning and data mining, with applications to data intensive problems in recommender systems, text analytics, security informatics, and bioinformatics. In recent years, she has focused on semi-supervised and domain adaptation algorithms, under the assumption that labeled data for a domain of interest is limited, if available at all.

    Lecture Title: Mining Social Media to Aid Disaster Response

    Lecture Abstract: Disaster-affected communities are increasingly becoming the source of big (crisis) data during and following major disasters. At the same time, big data have the potential to become an integral source of information for response organizations, as they can help enhance the situational awareness and facilitate faster response where it is most needed. Despite such benefits, the challenges presented by big data preclude organizations from using them routinely. Manually sifting through voluminous streaming data to filter useful information in real time is inherently impossible. We study machine learning solutions to help emergency response organizations deal with the overload of relevant information, and improve situational awareness and crisis response. Our proposed machine learning solutions have the potential to transform the way in which crisis response organizations operate and, in turn, to provide better support to the victims of disasters in a timely fashion.

    Speaker Bio: Doina Caragea, Ph.D., is a Professor at Kansas State University. Her research and teaching interests are in the areas of machine learning and data science, with applications to crisis informatics, security informatics, and bioinformatics. Her projects build upon close collaborations with social scientists, security experts and life scientists, and aim to provide practical computational approaches to address real-world challenges. Dr. Caragea received her PhD in Computer Science from Iowa State University in August 2004, and was honored with the Iowa State University Research Excellence Award for her work. She has published more than 150 refereed conference and journal articles. She has a strong track record of extramural funding, with $12M+ total funding as PI, co-PI or senior personnel from NSF and industry.

    Please note that this lecture was originally scheduled for October 22, 2021.


    MTRAC Info Seminar Is Sept. 10

    by Office of Innovation and Commercialization

    For several years, Michigan Tech has partnered with the State of Michigan and other stakeholders to create an entrepreneurial and innovation ecosystem. Members of the community at large can participate in this process at an event on the Michigan Tech campus.

    Michigan Tech hosts one of five hubs that make up the Michigan Translational and Research Commercialization (MTRAC), funded by the state’s Michigan 21st Century Jobs fund through the Michigan Strategic Fund. MTRAC-supported projects have secured more than $315 million in follow-on funding.

    Join us at noon on September 10, 2021 in GLRC 202 to hear directly from the program directors of each hub to learn about program requirements and what makes for a competitive proposal. Directors will have a few appointments on a first come, first serve availability following the seminar for one-on-one meetings with prospective principal investigators.

    MTRAC provides matching funds for researchers to accelerate the transfer of new technologies from universities, hospital systems, and nonprofit research centers into the commercial market. Funding is available under any of the five statewide hub programs organized around the following technology areas:

    • Ag Bio Innovation Hub (managed by Michigan State University)
    • Life Sciences Innovation Hub (managed by the University of Michigan)
    • Advanced Transportation Innovation Hub (managed by University of Michigan)
    • Advanced Materials Innovation Hub (managed by Michigan Tech)
    • Advanced Computing Innovation Hub (managed by Wayne State University)

    Prospective entrepreneurs will learn about moving technology from lab to market. Program objectives, goals and scope will be discussed by representatives from the five MTRAC hubs and representatives from the Michigan Economic Development Corporation (MEDC).

    Please RSVP to the event.


    PinT 2021 – 10th Workshop on Parallel-in-Time Integration

    August 2-6, 2021. PinT 2021 will be offered in a virtual-format. 

    Register online on the Registration Page.

    Computer models and simulations play a central role in the study of complex systems in engineering, life sciences, medicine, chemistry, and physics. Utilizing modern supercomputers to run models and simulations allows for experimentation in virtual laboratories, thus saving both time and resources. Although the next generation of supercomputers will contain an unprecedented number of processors, this will not automatically increase the speed of running simulations. New mathematical algorithms are needed that can fully harness the processing potential of these new systems. Parallel-in-time methods, the subject of this workshop, are timely and necessary, as they extend existing computer models to these next generation machines by adding a new dimension of scalability. Thus, the use of parallel-in-time methods will provide dramatically faster simulations in many important areas, such as biomedical applications (e.g., heart modeling), computational fluid dynamics (e.g., aerodynamics and weather prediction), and machine learning. Computational and applied mathematics plays a foundational role in this projected advancement.

    The primary focus of the proposed parallel-in-time workshop is to disseminate cutting-edge research and facilitate scientific discussions on the field of parallel time integration methods. This workshop aligns with the National Strategic Computing Initiative (NSCI) objective: “increase coherence between technology for modeling/simulation and data analytics”. The need for parallel time integration is being driven by microprocessor trends, where future speedups for computational simulations will come through using increasing numbers of cores and not through faster clock speeds. Thus as spatial parallelism techniques saturate, parallelization in the time direction offers the best avenue for leveraging next generation supercomputers with billions of processors. Regarding the mathematical treatment of parallel time integrators, one must use advanced methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretization and integration, convergence analyses of iterative methods, and the development and implementation of new parallel algorithms. Thus, the workshop will bring together an interdisciplinary group of experts spanning these areas.