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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261005T161500
DTEND;TZID=America/Los_Angeles:20261005T171500
DTSTAMP:20260910T053858Z
CREATED:20260910T053858Z
LAST-MODIFIED:20260910T053858Z
UID:10002255-1791216900-1791220500@colleges.claremont.edu
SUMMARY:If a Statistical Model Predicts That Common Events Should Occur Only Once in 10\,000 Elections\, Maybe it’s the Wrong Model (Danny Ebanks\, Cal Tech)
DESCRIPTION:Political scientists forecast elections\, not primarily to satisfy public interest\, but to validate statistical models used for estimating quantities of scholarly interest. Although scholars have learned a great deal from these models\, they can be embarrassingly overconfident: Events that should occur once in 10\,000 elections occur almost every year\, and even those that should occur once in a five-quadrillion elections are sometimes observed. We develop the first generative statistical model of all US federal legislative elections for the U.S. House (1946–2024) and Senate (1954–2024) and validate it with extensive out-of-sample tests. We find that even as the incumbency advantage rises and falls\, voting patterns nationalize\, and heresthetic maneuvering remake candidacies and campaigns\, the fundamental quantities of interest related to American legislative elections remain constant over eighty years\, including but not limited to the probability of incumbent defeat\, the magnitude and dispersion of candidate effects\, the midterm penalty\, and the partisan bias of electoral maps. Most striking\, we show that the same set of structural parameters describes both U.S. House and Senate elections\, implying a universal data-generation process for American legislative elections in the postwar era.
URL:https://colleges.claremont.edu/ccms/event/if-a-statistical-model-predicts-that-common-events-should-occur-only-once-in-10000-elections-maybe-its-the-wrong-model-danny-ebanks-cal-tech/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Ami Radunskaya":MAILTO:aradunskaya@pomona.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260928T161500
DTEND;TZID=America/Los_Angeles:20260928T171500
DTSTAMP:20260913T232258Z
CREATED:20260913T232258Z
LAST-MODIFIED:20260913T232258Z
UID:10002330-1790612100-1790615700@colleges.claremont.edu
SUMMARY:Brain Imaging and Mathematical Modeling of Alzheimer's Disease (Peter Hinow\, U. Wisconsin\, Milwaukee)
DESCRIPTION:A wide variety of medical imaging methods exist for research and diagnostic procedures on the Central Nervous System (CNS)\, among them Magnetic Resonance Imaging (MRI) and Optical Imaging. Mathematical modeling and simulation contribute significantly to an improved understanding of image data and the intricate transport\, diffusion\, and metabolic processes in the brain. This is of particular importance in the study of pathologies such as Alzheimer’s Disease\, which\, 125 years after its description\, remains poorly understood and for which only moderate success has been made in its treatment. In the first work to be presented\, we investigate tracer diffusion and transport in the glymphatic system by combining optical imaging in rats with a partial differential equation of reaction-advection-diffusion type. In a second work\, we collect observations on the accumulation of amyloid-β\, changes in neuronal density\, and a decline in cognitive performance in TgF344-AD and wild-type rats. We develop a compartmental ordinary differential equation model and determine its parameters by fitting the output to the experimental observations. In the long run\, our mathematical modeling effort is intended to bridge AD research in rodent models and the human condition of AD. This is joint work with Dr. Muna Aryal (North Carolina Agricultural and Technical State University) and Micah Hesketh\, MS (graduate student\, UWM).
URL:https://colleges.claremont.edu/ccms/event/brain-imaging-and-mathematical-modeling-of-alzheimers-disease-peter-hinow-u-wisconsin-milwaukee-2/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Ami Radunskaya":MAILTO:aradunskaya@pomona.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260921T161500
DTEND;TZID=America/Los_Angeles:20260921T171500
DTSTAMP:20260913T231319Z
CREATED:20260913T231319Z
LAST-MODIFIED:20260913T231319Z
UID:10002329-1790007300-1790010900@colleges.claremont.edu
SUMMARY:Number Theory meets Differential Equations: Using Homotopy Continuation to Compute Shabat Polynomials
DESCRIPTION:A Belyĭ pair \(\bigl( S\,\\, z(w) \bigr)\) is a compact\, connected Riemann surface \(S\) together with a rational function \(z \colon S \to \mathbb{P}^1(\mathbb{C})\) which has at most three critical values \(\bigl\{ 0\,\\, 1\,\\, \infty \bigr\}\). The preimage \(z^{-1}\bigl( [0\,1] \bigr) \subseteq S \hookrightarrow \mathbb{R}^3\) is a bipartite graph called a Dessin d’Enfant. When \(S = \mathbb{P}^1(\mathbb{C}) \simeq S^2(\mathbb{R})\) is the Riemann sphere\, a tree—namely\, a planar graph with one face—can be realized as the Dessin d’Enfant of a polynomial. Named in honor of Georgii Borisovich Shabat\, a Belyĭ map \(z \colon S \to \mathbb{P}^1(\mathbb{C})\) which is also a polynomial is called a Shabat polynomial. \nIn this project\, we seek to compute more examples of Shabat polynomials. We introduce a trick which reduces the computation of such polynomials to finding solutions to a system of polynomial equations. We explore computing these solutions via two methods: (1) Newton’s method\, to find approximate values\, and (2) the homotopy continuation method\, to deform known solutions into desired yet unknown ones. Simply put\, in this talk we give an introduction to using differential equations to answer questions in number theory. \nThis project was completed through the Research Experience for Undergraduate Faculty (REUF) at AIM/ICERM in Summers 2025 and 2026 (DMS‑2015462).
URL:https://colleges.claremont.edu/ccms/event/number-theory-meets-differential-equations-using-homotopy-continuation-to-compute-shabat-polynomials/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Ami Radunskaya":MAILTO:aradunskaya@pomona.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260914T161500
DTEND;TZID=America/Los_Angeles:20260914T171500
DTSTAMP:20260910T052954Z
CREATED:20260910T052954Z
LAST-MODIFIED:20260910T052954Z
UID:10002252-1789402500-1789406100@colleges.claremont.edu
SUMMARY:Adaptive Experimental Design using Shrinkage Estimators (Evan Rosenman\, Claremont McKenna College)
DESCRIPTION:In multi-armed trials\, adaptive designs are a popular way to increase estimation efficiency or identify optimal treatments. Many recent papers have proposed adaptive methods for minimizing the error of unbiased estimators that consider each treatment arm in isolation. This approach may be inefficient\, because it fails to borrow shared information across the treatment arms.\nWe consider adaptivity in a sequential trial with K active treatments and a control\, and suggest the use of Stein-like shrinkage estimators to obtain the final causal estimates. These estimators share information\, yielding reductions in expected estimation error\, relative to estimating each causal effect in isolation. Moreover\, for a group of candidate estimators\, the expected error can be expressed as the expectation of ratios of Gaussian quadratic forms\, and can thus be computed efficiently. Hence\, we suggest a simple algorithm for sequential adaptivity: assign each new arrival to the arm that will minimize the estimated shrinker loss.\nThrough simulations\, we demonstrate that this approach reduces estimation error\, especially in the low signal-to-noise regime. We also characterize how our adaptive algorithm assigns treatments differently than would a classical Neyman allocation and suggest a method for constructing shorter confidence intervals at the conclusion of the trial.
URL:https://colleges.claremont.edu/ccms/event/adaptive-experimental-design-using-shrinkage-estimators-evan-rosenman-claremont-mckenna-college/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Ami Radunskaya":MAILTO:aradunskaya@pomona.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250425T131500
DTEND;TZID=America/Los_Angeles:20250425T141500
DTSTAMP:20250423T051555Z
CREATED:20250423T051049Z
LAST-MODIFIED:20250423T051555Z
UID:10002135-1745586900-1745590500@colleges.claremont.edu
SUMMARY:Data Science / Statistics Seminar: Ana Maria Kenney (UC Irvine)
DESCRIPTION:Speaker: Ana Maria Kenney\, Assistant Professor\, Department of Statistics\, UC Irvine \nTitle: Distilling heterogeneous treatment effects: Stable subgroup estimation in causal inference \nAbstract: Recent methodological developments have introduced new black-box approaches to better estimate heterogeneous treatment effects; however\, these methods fall short of providing interpretable characterizations of the underlying individuals who may be most at risk or benefit most from receiving the treatment\, thereby limiting their practical utility. In this work\, we introduce a novel method\, causal distillation trees (CDT)\, to estimate interpretable subgroups. CDT allows researchers to fit any machine learning model of their choice to estimate the individual-level treatment effect\, and then leverages a simple\, second-stage tree-based model to “distill” the estimated treatment effect into meaningful subgroups. As a result\, CDT inherits the improvements in predictive performance from black-box machine learning models while preserving the interpretability of a simple decision tree. We derive theoretical guarantees for the consistency of the estimated subgroups using CDT\, and introduce stability-driven diagnostics for researchers to evaluate the quality of the estimated subgroups. We illustrate our proposed method on a randomized controlled trial of antiretroviral treatment for HIV from the AIDS Clinical Trials Group Study 175 and show that CDT out-performs state-of-the-art approaches in constructing stable\, clinically relevant subgroups. \nBio: Ana Maria Kenney is an Assistant Professor in the Department of Statistics at UC Irvine. She works at the interface of statistics\, interpretable machine learning\, and large-scale optimization to advance biomedical research. She has been on several interdisciplinary teams across institutions spanning cardiovascular genetics\, “Omics” contributions to early infant growth\, and early cancer screening. She completed a postdoc at UC Berkeley and previously received a dual title Ph.D. at Penn State in Statistics and Operations Research. There she was a Biomedical Big Data to Knowledge Training Fellow and Alfred P. Sloan Ph.D. Scholar.
URL:https://colleges.claremont.edu/ccms/event/data-science-statistics-seminar-ana-maria-kenney-uc-irvine/
LOCATION:Roberts North 15\, CMC\, 320 E. 9th St.\, Claremont\, 91711\, United States
CATEGORIES:Special Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190408T161500
DTEND;TZID=America/Los_Angeles:20190408T171500
DTSTAMP:20190401T035013Z
CREATED:20190311T221343Z
LAST-MODIFIED:20190401T035013Z
UID:10001591-1554740100-1554743700@colleges.claremont.edu
SUMMARY:Models of Biological Tissue Electrostatics and Molecular Transport (Jim Sterling\, KGI)
DESCRIPTION:In this presentation\, some fundamentals of electrostatics in biology will be discussed with focus on the fact that most biological macromolecules including nucleic acids\, carbohydrates\, and proteins are negatively-charged. Electroneutrality requires cations to move toward the macromolecules where they both screen and bind to the negatively-charged groups. An important class of mathematical models of species-flux and electrostatics are known as the Poisson-Nernst-Planck\, or PNP equations. These are partial differential equations describing some important biophysical consequences.
URL:https://colleges.claremont.edu/ccms/event/models-of-biological-tissue-electrostatics-and-molecular-transport-jim-sterling-kgi/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190401T161500
DTEND;TZID=America/Los_Angeles:20190401T171500
DTSTAMP:20190312T223842Z
CREATED:20190307T230118Z
LAST-MODIFIED:20190312T223842Z
UID:10001590-1554135300-1554138900@colleges.claremont.edu
SUMMARY:Applied Math Talk: Repurposing FDA-approved drugs as host-oriented therapies against infectious diseases (Prof. Mikhail Martchenko\, KGI)
DESCRIPTION:The traditional method of treating most human diseases is to direct a therapy against targets in the host patient\, whereas conventional therapies against infectious diseases are directed against the pathogen. Unfortunately\, the efficacy of pathogen-oriented therapies and their ability to combat emerging threats such as genetically engineered and non-traditional pathogens and toxins have been limited by the occurrence of mutations that render pathogen targets resistant to countermeasures. Our work shows that host proteins that are exploited by pathogens (Host Proteins Exploited by Pathogens; HPEPs) contribute to the severity of exposure to pathogenic agents. We find that pathogens recruit HPEPs to bind to\, enter\, reproduce in\, exit from\, and kill host cells. Thus\, HPEPs are potential targets for therapies. This presentation will discuss examples of our drug discovery efforts to identify host-oriented therapies.
URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-repurposing-fda-approved-drugs-as-host-oriented-therapies-against-infectious-diseases-prof-mikhail-martchenko-kgi/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190204T161500
DTEND;TZID=America/Los_Angeles:20190204T171500
DTSTAMP:20190117T015941Z
CREATED:20181008T181051Z
LAST-MODIFIED:20190117T015941Z
UID:10001577-1549296900-1549300500@colleges.claremont.edu
SUMMARY:Estimating the physical location of Twitter users with the von Mises-Fisher distribution (Mike Izbicki\, UC Riverside)
DESCRIPTION:Approximately 500 million tweets are sent everyday.  Scientists monitor these tweets to predict the spread of disease\, better allocate social welfare services\, help first responders during natural disasters\, and many other important tasks.  A key step in each of these tasks is estimating the location the tweet was sent from.  In\nthis talk\, I discuss how to combine machine learning and the von Mises-Fisher distribution to estimate this location.  The von Mises-Fisher distribution is the spherical analog of the Gaussian distribution\, and this distribution lets us exploit the earth’s non-Euclidean geometry to improve estimation accuracy.
URL:https://colleges.claremont.edu/ccms/event/tba-mike-izbicki-uc-riverside/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181210T161500
DTEND;TZID=America/Los_Angeles:20181210T171500
DTSTAMP:20181116T192815Z
CREATED:20180921T221142Z
LAST-MODIFIED:20181116T192815Z
UID:10001575-1544458500-1544462100@colleges.claremont.edu
SUMMARY:Transfinite $\zeta$-metrics (Zair Ibragimov\, CMC)
DESCRIPTION:I will discuss the concept of transfinite ζ-metrics. In some details I will discuss transfinite Apollonian metric in the settings of semi-metric spaces. I will discuss specific examples of domains where the transfinite Apollonian metric can be computed explicitly. This is a preliminary work.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-given-by-prof-ibragimov-zair-cmc/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181203T161500
DTEND;TZID=America/Los_Angeles:20181203T171500
DTSTAMP:20181106T161858Z
CREATED:20180921T215624Z
LAST-MODIFIED:20181106T161858Z
UID:10001573-1543853700-1543857300@colleges.claremont.edu
SUMMARY:A Martingale Approach to the Question of Fiscal Stimulus (Michael Imerman\, CGU)
DESCRIPTION:Joint work with Larry Shepp & Philip Ernst \nIn this paper we develop a mathematical model to address an ongoing politico-economic debate between Democrats and Republicans. Democrats in the US say that government spending can be used to “grease the wheels’ of the economy\, create wealth\, and increase employment; the Republicans say that government spending is wasteful\, discourages investment\, and so increases unemployment. These arguments cannot both be correct\, but both arguments seem meritorious. We address this economic question of fiscal stimulus as a new optimal control problem extending the model of Radner-Shepp (1996). A unique solution is found using traditional martingale methods for stochastic optimization along with a numerical procedure to solve a non-homogeneous ODE as the root of an implicit function. Specifically\, we find that there exists an optimal strategy with interesting mathematical properties.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-given-by-prof-michael-imerman-cgu/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181112T161500
DTEND;TZID=America/Los_Angeles:20181112T171500
DTSTAMP:20181101T041237Z
CREATED:20180910T183619Z
LAST-MODIFIED:20181101T041237Z
UID:10001569-1542039300-1542042900@colleges.claremont.edu
SUMMARY:Digital sequences for frequency hopping CDMA systems (Lenny Fukshansky\, CMC)
DESCRIPTION:Frequency hopping is a method of transmitting signals by rapidly switching between many frequency channels\, following some sequence of frequencies known to the transmitter and the receiver. This technique is used in the CDMA (code division multiple access) systems\, and has many civilian and military applications. For successful transmission minimizing signal interference\, we want to use sets of digital frequency sequences with minimal Hamming cross-correlation\, which measures frequency overlaps with time shifts between two different sequences. We discuss a construction of a new family of one-coincidence sequences like this coming from some basic arithmetic of finite fields\, which have some nice properties. This is joint work with Adib Shaar\, and this talk is dedicated to his memory.
URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-given-by-prof-lenny-fukshansky/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181029T161500
DTEND;TZID=America/Los_Angeles:20181029T171500
DTSTAMP:20181016T222630Z
CREATED:20180910T073543Z
LAST-MODIFIED:20181016T222630Z
UID:10001567-1540829700-1540833300@colleges.claremont.edu
SUMMARY:Minimal Gaussian Partitions\, Clustering Hardness and Voting (Steven Heilman\, USC)
DESCRIPTION:A single soap bubble has a spherical shape since it minimizes its surface area subject to a fixed enclosed volume of air.  When two soap bubbles collide\, they form a “double-bubble” composed of three spherical caps.  The double-bubble minimizes total surface area among all sets enclosing two fixed volumes.  This was proven mathematically in a landmark result by Hutchings-Morgan-Ritore-Ros and Reichardt using the calculus of variations in the early 2000s.  The analogous case of three or more Euclidean sets is considered difficult if not impossible.  However\, if we replace Lebesgue measure in these problems with the Gaussian measure\, then recent work of myself (for 3 sets) and of Milman-Neeman (for any number of sets) can actually solve these problems.  We also use the calculus of variations.  We will discuss applications of this Gaussian “multi-bubble” problem to optimal clustering of data and to designing elections that are resilient to hacking.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-given-by-prof-steven-heilman/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181015T161500
DTEND;TZID=America/Los_Angeles:20181015T171500
DTSTAMP:20180927T002145Z
CREATED:20180911T004755Z
LAST-MODIFIED:20180927T002145Z
UID:10001571-1539620100-1539623700@colleges.claremont.edu
SUMMARY:Agent-Based and Continuous Models of Locust Hopper Bands: The Role of Intermittent Motion\, Alignment\, Attraction and Repulsion (Andrew J. Bernoff\, HMC)
DESCRIPTION:Locust swarms pose a major threat to agriculture\, notably in northern Africa and the Middle East. In the early stages of aggregation\, locusts form hopper bands. These are coordinated groups that march in columnar structures that are often kilometers long and may contain millions of individuals. We propose a model for the formation of locust hopper bands that incorporates intermittent motion\, alignment with neighbors\, and social attraction\, all behaviors that have been validated in experiments. Using a particle-in-cell computational method\, we simulate swarms of up to a million individuals\, which is several orders of magnitude larger than what has previously appeared in the locust modeling literature. We observe hopper bands in this model forming as a fingering instability. Our model also allows homogenization to yield a system of partial integro-differential evolution equations. We identify a bifurcation from a uniform marching state to columnar structures\, suggestive of the formation of hopper bands.
URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-given-by-prof-andrew-j-bernoff-hmc/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180917T161500
DTEND;TZID=America/Los_Angeles:20180917T171500
DTSTAMP:20180926T235724Z
CREATED:20180828T201223Z
LAST-MODIFIED:20180926T235724Z
UID:10001565-1537200900-1537204500@colleges.claremont.edu
SUMMARY:Diffusion\, Social Networks\, and Logic (Pavel Naumov\, CMC)
DESCRIPTION:Once a new commercial product\, technology\, political opinion\, or social norm is adopted by a few people\, these few often put peer pressure on others to consider adopting it as well. Those who adopt next put even more pressure on the rest of the population. This cascading “epidemic” effect is often called diffusion in social networks. There are many natural questions that can be asked about diffusion. Which initial group of people should get “infected” by a new product to ensure its adoption by the largest possible group? Which group should be convinced that an idea is bad\, in order to avoid its wide spread? How does marketing affect the diffusion? In this talk I will introduce the most commonly used mathematical model of diffusion and talk about several of my papers on logical systems that capture properties of this model.
URL:https://colleges.claremont.edu/ccms/event/applied-math-talk-given-by-prof-pavel-naumov-cmc/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
GEO:34.099908;-117.7142522
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Emmy Noether Room Millikan 1021 Pomona College 610 N. College Ave. Claremont California 91711;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142522,34.099908
END:VEVENT
END:VCALENDAR