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DTSTART;TZID=America/Los_Angeles:20211004T161500
DTEND;TZID=America/Los_Angeles:20211004T171500
DTSTAMP:20260418T161104
CREATED:20210908T152516Z
LAST-MODIFIED:20210928T171304Z
UID:2313-1633364100-1633367700@colleges.claremont.edu
SUMMARY:Applied Math Seminar -- Manuchehr Aminian (Cal Poly Pomona)
DESCRIPTION:Title: Traditional Applied Math\, and then\, Working with High Dimensional Biological Data \nAbstract: \n\nI will give an overview of my interests in two parts. The first part will be on passive tracer problems – with the goal of finding formulas of descriptive statistics (mean\, variance\, skewness) for a solute distribution advected by a smooth flow in a tube with arbitrary cross-section. We found explicit formulas which predict these statistics relying ultimately only on the cross-section of the tube\, and see agreement with numerical simulation as well as experiment. Some partial derivatives and pretty pictures from simulations will be shown.  \n\n\nIn the second part\, I’ll talk about my projects outside of partial differential equations. The main thrust of my (pre-pandemic) postdoctoral project was applying math and machine learning approaches to identify biomarkers predictive of pre-symptomatic infection in “omics” data sets from human challenge studies of influenza-like illnesses. I’ll define the jargon\, and talk about our successes* in answering a few questions: \n\n\n\nGiven a collection of blood samples from study participants\, can one identify (classify) a new blood sample as coming from a “shedder” (one who may be expected to be contagious) in the first 24 hours after exposure? \n\n\nGiven a collection of granular blood samples from study participants over the first week of infection\, and given a blood sample from someone already known to be infected\, can one predict how long it has been since the exposure event? \n\n\n*Our research did not result in technologies which stopped the pandemic; so in that sense\, we were not successful.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-manuchehr-aminian-cal-poly-pomona/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
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DTSTART;TZID=America/Los_Angeles:20211005T123000
DTEND;TZID=America/Los_Angeles:20211005T132000
DTSTAMP:20260418T161104
CREATED:20210906T215040Z
LAST-MODIFIED:20210906T215040Z
UID:2301-1633437000-1633440000@colleges.claremont.edu
SUMMARY:Critical points of toroidal Belyi maps (Edray Goins\, Pomona)
DESCRIPTION:A Belyi map $\beta: \mathbb{P}^1(\mathbb{C}) \to \mathbb{P}^1(\mathbb{C})$ is a rational function with at most three critical values; we may assume these values are $\{ 0\, \\, 1\, \\, \infty \}$.  Replacing $\mathbb{P}^1$ with an elliptic curve $E: \ y^2 = x^3 + A \\, x + B$\, there is a similar definition of a Belyi map $\beta: E(\mathbb{C}) \to \mathbb{P}^1(\mathbb{C})$.  Since $E(\mathbb{C}) \simeq \mathbb T^2(\mathbb {R})$ is a torus\, we call $(E\, \beta)$ a Toroidal \Belyi pair. \n\n\nThere are many examples of Belyi maps $\beta: E(\mathbb{C}) \to \mathbb P^1(\mathbb{C})$ associated to elliptic curves; several can be found online at LMFDB. Given such a Toroidal Belyi map of degree $N$\, the inverse image $G = \beta^{-1} \bigl( \{ 0\, \\, 1\, \\, \infty \} \bigr)$ is a set of $N$ elements which contains the critical points of the \Belyi map. In this project\, we investigate when $G$ is contained in $E(\mathbb{C})_{\text{tors}}$. \n\n\nThis is work done as part of the Pomona Research in Mathematics Experience (NSA H98230-21-1-0015).
URL:https://colleges.claremont.edu/ccms/event/critical-points-of-toroidal-belyi-maps-edray-goins-pomona/
LOCATION:On Zoom
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211005T150000
DTEND;TZID=America/Los_Angeles:20211005T160000
DTSTAMP:20260418T161104
CREATED:20210914T225152Z
LAST-MODIFIED:20210914T230121Z
UID:2354-1633446000-1633449600@colleges.claremont.edu
SUMMARY:Topology Seminar -- Jim Hoste
DESCRIPTION:Jim Hoste will do an interpretive knot dance.
URL:https://colleges.claremont.edu/ccms/event/topology-seminar-2021-09-21-2021-10-05/
LOCATION:Zoom meeting\, United States
CATEGORIES:Topology Seminar
ORGANIZER;CN="Helen Wong":MAILTO:hwong@cmc.edu
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211006T163000
DTEND;TZID=America/Los_Angeles:20211006T174500
DTSTAMP:20260418T161104
CREATED:20210831T035746Z
LAST-MODIFIED:20210831T035746Z
UID:2257-1633537800-1633542300@colleges.claremont.edu
SUMMARY:Interrupted Time Series Models for Assessing Complex Health Care Interventions (Maricela Cruz\, PhD)
DESCRIPTION:Title: Interrupted Time Series Models for Assessing Complex Health Care Interventions \nMaricela Cruz\, PhD\nAssistant Investigator\nBiostatistics Unit\nKaiser Permanente Washington Health Research Institute \nAbstract:  Assessing the impact of complex interventions on measurable health outcomes is a growing concern in health care and health policy. According to the 2018 Annual Review of Public Health\, interrupted time series (ITS) designs may be the only feasible recourse for studying the impacts of large-scale public health policies. Statistical models used to analyze ITS data a priori restrict the interruption’s effect to a predetermined time point or censor data for which the intervention effects may not be fully realized\, and neglect changes in the temporal dependence and variability. In addition\, current methods limit the analysis to one hospital unit or entity and are not well specified for discrete outcomes (e.g.\, patient falls). In this talk\, I present novel ITS methods based on segmented regression that address the aforementioned limitations and provide a testing paradigm for the existence of a change point in the time series. The methodology is illustrated by analyzing patient centered data from a hospital that implemented and evaluated a new care delivery model in multiple units.\n  \nMaricela Cruz is an Assistant Investigator and Biostatistician at Kaiser Permanente Washington Health Research Institute and Affiliate Assistant Professor at the University of Washington Department of Biostatistics.  She received her PhD in statistics from the University of California Irvine and was a National Science Foundation Graduate Research Fellowship awardee and Eugene Cota-Robles fellow during her time there. Maricela’s research primarily focuses on developing novel statistical methods to assess and evaluate the impact of complex health interventions.
URL:https://colleges.claremont.edu/ccms/event/interrupted-time-series-models-for-assessing-complex-health-care-interventions-maricela-cruz-phd/
LOCATION:Zoom meeting\, United States
CATEGORIES:Colloquium
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