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X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences
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DTSTART;TZID=America/Los_Angeles:20220202T161500
DTEND;TZID=America/Los_Angeles:20220202T173000
DTSTAMP:20260412T193012
CREATED:20220128T183638Z
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SUMMARY:Exploiting metric structure for more accurate classification (Prof. Mike Izbicki)
DESCRIPTION:Title: Exploiting metric structure for more accurate classification \nSpeaker: Mike Izbicki\, Department of Mathematical Sciences\, Claremont McKenna College \nAbstract: Classification problems often have many semantically similar classes.  For example\, the famous ImageNet dataset contains classes for 80 different dog breeds\, 40 different bird species\, and 25 types of vehicles.  This semantic structure can be formalized using a metric space\, with semantic similarity of classes encoded by the distance function.  In this talk\, I’ll describe the “tree loss”\, which is the first technique with provable performance guarantees for exploiting this metric structure.  I’ll also show that the tree loss has better empirical performance than competing algorithms on image\, text\, and vector data. \n\nMike studies machine learning theory\, focusing on applications to natural language and social media.  He has been at CMC for 3 years now\, where he teaches computer and data science classes.  Prior to his academic career\, Mike spent 7 years in the US Navy.  Highlights include converting >10g of Uranium into pure energy as a nuclear submarine officer\, and doing [redacted] for the NSA.  After leaving the navy\, Mike went to North Korea to teach computer science as part of an academic exchange program designed to improve relations between the US and North Korea.  He earned his phd from UC Riverside.
URL:https://colleges.claremont.edu/ccms/event/exploiting-metric-structure-for-more-accurate-classification-prof-mike-izbicki/
LOCATION:Zoom meeting\, United States
CATEGORIES:Colloquium
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220209T161500
DTEND;TZID=America/Los_Angeles:20220209T173000
DTSTAMP:20260412T193012
CREATED:20220131T170105Z
LAST-MODIFIED:20220131T170634Z
UID:2588-1644423300-1644427800@colleges.claremont.edu
SUMMARY:Modeling the waning and boosting of immunity (Prof. Lauren Childs)
DESCRIPTION:Title: Modeling the waning and boosting of immunity\n\n\nSpeaker: Dr. Lauren Childs\nAssistant Professor and the Cliff and Agnes Lilly Faculty Fellow\nVirgina Tech\n\n \nAbstract: Infectious disease often leads to significant loss of life and burden on society. Understanding disease dynamics is essential to the development and implementation of earlier and more effective interventions. Traditionally\, perfect\, long-lasting protection against disease is assumed to be acquired\, but this need not always be the case. Immunity following natural infection (or immunization) may wane\, increasing susceptibility with time since exposure. In this talk\, we begin by examining a classic model of waning and boosting immunity with a focus on the bifurcation structure and how it changes as reinfection is considered. Then\, we discuss an extension of this framework with an age- and immune status-dependent model of disease transmission. In this model\, susceptibility\, infectiousness\, and symptom severity all vary with immune status\, while age affects contacts and vaccination.  We examine applications of this model to two diseases: pertussis\, commonly known as whooping cough\, and COVID-19. For pertussis\, we examine age-specific incidence and prevalence and find vaccination leads to a resurgence of immunity-modified pertussis in older children\, as observed with effective vaccination programs. For COVID-19\, we examine the role of waning and boosting immunity to estimate seroprevalence in Canada and to evaluate vaccination strategies. We find a large fraction of the Canadian population with some immunity following infection or vaccination\, but that the quality and longevity of this immunity decreases with time. Using contact and demographic data from specific locations coupled with disease-specific parameterization\, our model has the potential to assist in the development and optimization of vaccination schedules. This is important to mitigate resurgence of immunity-modified disease due to natural boosting.\n\n\nDr. Lauren Childs is an Assistant Professor in the Department of Mathematics and the Cliff and Agnes Lilly Faculty Fellow in the College of Science at Virginia Tech. Her research focuses on developing and analyzing mathematical and computational models for a better understanding of the dynamics of infectious diseases\, in particular vector-borne diseases such as malaria. Her research emphasizes the interactions within a host organism\, such as between an invading pathogen and the immune response\, and the impacts of such interactions on transmission between individuals in the population.
URL:https://colleges.claremont.edu/ccms/event/modeling-the-waning-and-boosting-of-immunity-prof-lauren-childs/
LOCATION:Zoom
CATEGORIES:Colloquium
ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220216T161500
DTEND;TZID=America/Los_Angeles:20220216T173000
DTSTAMP:20260412T193012
CREATED:20220128T164956Z
LAST-MODIFIED:20220214T180454Z
UID:2577-1645028100-1645032600@colleges.claremont.edu
SUMMARY:Solving the Race in Backgammon (Prof. Arthur Benjamin)
DESCRIPTION:Title: Solving the Race in Backgammon\n \nSpeaker: Prof. Arthur Benjamin\nSmallwood Family Professor of Mathematics\nHarvey Mudd College\n \nAbstract: Backgammon is perhaps the oldest game that is still played today. It is a game that combines luck with skill\, where two players take turns rolling dice and decide how to move their checkers in the best possible way. It is the ultimate math game\, where players who possess a little bit of mathematical knowledge can have a big advantage over their opponents.  Players also have the opportunity to double the stakes of a game using something called the doubling cube\, which—when used optimally—leads to players winning more in the long run. Optimal use of the doubling cube relies on a player’s ability to estimate their winning chances at any stage of the game.\n\nWhen played to completion\, every game of backgammon eventually becomes a race\, where each player attempts to remove all of their checkers before their opponent does. The goal of our research is to be able to determine the optimal doubling cube action for any racing position\, and approximate the game winning chances for both sides. By calculating the Effective Pip Count for both players and identifying the positions’ Variance Types\, we arrive at a reasonably simple method for achieving this which is demonstrably superior to other popular methods.\n\n\n\n\nArthur Benjamin\, PhD\, Smallwood Family Professor of Mathematics\, is recognized nationally for his ability to perform rapid mental calculations. In 2020 he won the inaugural American Backgammon Tour Online (ABTO) with the best overall performance in a series of 17 national tournaments.  He has published several books on how to make math both fun and easy.  He is also a professional mathemagician and frequently performs at the Magic Castle in Hollywood and nationwide.
URL:https://colleges.claremont.edu/ccms/event/solving-the-race-in-backgammon-prof-arthur-benjamin/
LOCATION:Zoom meeting\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220223T161500
DTEND;TZID=America/Los_Angeles:20220223T173000
DTSTAMP:20260412T193012
CREATED:20220216T183109Z
LAST-MODIFIED:20220217T003329Z
UID:2626-1645632900-1645637400@colleges.claremont.edu
SUMMARY:Modeling  Zoonotic Infectious Diseases from Wildlife to Humans (Prof. Linda J. S. Allen)
DESCRIPTION:Title: Modeling  Zoonotic Infectious Diseases from Wildlife to Humans \nSpeaker: Prof. Linda J. S. Allen\, P. W. Horn Distinguished Professor Emeritus Texas Tech University \nAbstract: Zoonotic infectious diseases are diseases transmitted from animals to humans. It is estimated that over 60% of human infectious diseases are zoonotic. The Centers for Disease Control and Prevention has identified eight priority zoonoses in the US. Three of the priority zoonoses are avian influenza\, Lyme disease\, and emerging coronaviruses. Spillover of infections from animals to humans depends on a complex pathway from the natural wildlife reservoir.  The natural reservoir for avian influenza virus is wild birds but it is spread to humans from infected chickens. The natural reservoir for the bacterial pathogen causing Lyme disease is mice but it is transmitted to humans through the bite of an infected tick vector.    In this presentation\, we discuss a few of the modeling efforts to better understand the spread of infection in the natural reservoir and the spillover to humans as well as the impacts of demographic and environmental variability on timing of spillover.  \n___________________________________________________________________________________________________ \nLinda J. S. Allen received her PhD in Mathematics from University of Tennessee and was a Professor of Mathematics at Texas Tech University until 2019.  She is currently an Adjunct  Graduate Faculty at Texas Tech University. Her research interests are in mathematical ecology\, epidemiology\, and immunology.\nhttps://www.math.ttu.edu/~lallen/\nhttps://www.depts.ttu.edu/provost/scholars/lindaallen.php\n\nResearch Experiences for Undergraduates at Texas Tech University “Mathematical\, Statistical\, and Computational Methods for Problems in the Life Sciences”\n June 6-July 20\, 2022\n\nREU Applications Due: March 6\, 2022:\nhttps://www.math.ttu.edu/undergraduate/reu2022/
URL:https://colleges.claremont.edu/ccms/event/modeling-zoonotic-infectious-diseases-from-wildlife-to-humans-prof-linda-j-s-allen/
LOCATION:Zoom meeting\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Andrew Bernoff":MAILTO:ajb@hmc.edu
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