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DTSTART;TZID=America/New_York:20240405T170000
DTEND;TZID=America/New_York:20240407T170000
DTSTAMP:20231108T150613Z
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LAST-MODIFIED:20231108T150613Z
UID:306-1712336400-1712509200@pages.vassar.edu
SUMMARY:DataFest 2024
DESCRIPTION:Save the date for DataFest 2024 @ Vassar: April 5-7\, 2024.  This is our annual data competition open to all Vassar students\, as well as neighboring schools by invitation.  For more details about DataFest\, including past DataFests at Vassar\, visit: https://pages.vassar.edu/datafest/
URL:https://pages.vassar.edu/mathstats/event/datafest-2024/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240408T170000
DTEND;TZID=America/New_York:20240408T180000
DTSTAMP:20240408T004629Z
CREATED:20240404T171805Z
LAST-MODIFIED:20240408T004629Z
UID:560-1712595600-1712599200@pages.vassar.edu
SUMMARY:(DSS Colloquium) Thomas Schmickl\, University of Graz\, Austria
DESCRIPTION:Data Science & Society (DSS) Colloquium Talk with Thomas Schmickl\, University of Graz\, Austria\, on Monday April 8 at 5PM in Rocky 300.  \nTitle: Can Robots Save Nature? \nAbstract: Our planet is on the brink of the 6th mass extinction\, as our ecosystems are rapidly losing both\ndiversity and biomass. As intra- and inter-specific interaction networks weaken\, ecosystems\nbecome increasingly unstable\, setting off on a downward trajectory along a deadly spiral. I\nexplore how robotic systems can play a crucial role in supporting ecosystems and communities.\nI will show three levels of agency and how a “tech for good” approach might be helpful to\nfight ecosystem decay: monitoring\, intervention and restoration. By mitigating ecosystem\ndecay\, robots may buy us precious time to address the root causes of environmental crises. I\nwill show innovative systems that we’ve developed over recent years — the initial strides toward going beyond mere animal-interaction systems by establishing eco-effective robotics. \nPoster Link: https://pages.vassar.edu/dss/files/2024/03/Schmickl.presentation.8April2024.pdf
URL:https://pages.vassar.edu/mathstats/event/dss-colloquium-thomas-schmickl-university-of-graz-austria/
LOCATION:Rockefeller Hall 300
CATEGORIES:DSS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240409T150000
DTEND;TZID=America/New_York:20240409T160000
DTSTAMP:20240908T234154Z
CREATED:20240316T135634Z
LAST-MODIFIED:20240908T234154Z
UID:520-1712674800-1712678400@pages.vassar.edu
SUMMARY:(Colloquium) Anna Pun 4/9
DESCRIPTION:The Magic of Tableaux: Exploring the Wonders of Algebraic Combinatorics \nAnna Pun\nCUNY Baruch College \nTuesday\, April 9th\n3pm Rocky 312 \nTableaux are one of the most fundamental and versatile objects in algebraic combinatorics\, as they can encode and connect various concepts and structures in the field. In this talk\, we will start with the definition and properties of Young tableaux\, which are graphical representations of partitions of integers. We will then see how tableaux can be used in algebra: their connection to symmetric functions and partition algebras; how they can be related to various combinatorial operations\, such as the RSK-algorithm and the Jeu-de-taquin procedure; and how they can give rise to various combinatorial structures\, such as lattice paths\, vacillating tableaux\, and parking functions. We will also explore some variations of tableaux\, such as composition tableaux and set-valued tableaux\, and discuss some interesting problems and conjectures that arise from them. We will conclude with some open questions and directions for future research on tableaux and their applications in algebraic combinatorics.
URL:https://pages.vassar.edu/mathstats/event/colloquium-anna-pun-4-9/
CATEGORIES:Colloquium
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240409T173000
DTEND;TZID=America/New_York:20240409T183000
DTSTAMP:20240408T005157Z
CREATED:20240404T172243Z
LAST-MODIFIED:20240408T005157Z
UID:562-1712683800-1712687400@pages.vassar.edu
SUMMARY:(DSS Event) Lens Media Lab\, Yale University
DESCRIPTION:Data Science & Society (DSS) Event with the Yale University Lens Media Lab on Tuesday April 9 with Thomas Schmickl\, University of Graz\, Austria\, on Monday April 8 (multiple times; see below). \nPlease join us at 5:30PM\, Tuesday\, April 9 in Taylor Hall Room 102. Paul Messier\, Kappy Mintie\, and Damon Crockett from the Lens Media Lab at Yale University will participate in a panel titled \n“Characterizing Twentieth-Century Photographic Papers: A Multidisciplinary Approach.” \nThe panel will describe how the Paperbase project was conceived\, the interdisciplinary work required to develop it\, and how it can be used by scholars interested in the history of photography. Each of the panelists\, who come from different disciplinary backgrounds\, will also describe how they came to work at the Lens Media Lab and how their specialized knowledge contributed to the production of Paperbase. \nThe panel will be followed by a hands-on demonstration of some of the Lens Media Lab’s data collection tools at 6:30 PM in the Taylor Hall Jade Room. \nVassar students have the chance to meet with the panelists to discuss data science\, art\, and photography\, among other topics\, between 12PM and 2PM on April 9 in College Center 240. Food will be provided. Students are directed to sign up at this link. \nThis event is sponsored by Vassar’s Data Science and Society initiative\, the Department of Art\, and the Frances Lehman Loeb Art Center. \n \n 
URL:https://pages.vassar.edu/mathstats/event/dss-event-lens-media-lab-yale-university/
LOCATION:Taylor Hall
CATEGORIES:DSS
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240412T150000
DTEND;TZID=America/New_York:20240412T160000
DTSTAMP:20240412T025330Z
CREATED:20240205T185551Z
LAST-MODIFIED:20240412T025330Z
UID:472-1712934000-1712937600@pages.vassar.edu
SUMMARY:(LAVA) Kai Matheson\, VC '19
DESCRIPTION:LAVA Talk on Data Science for Social Good: From Academia to Federal Consulting\, with Kai Matheson (VC ’19)\, Accenture.\nFriday\, April 12\, 2024 at 3PM in Rocky 310. \n \nAbout Kai:\nKai works at Accenture as a data analytics consultant for the USDA. They build interactive data visualizations for national food insecurity programs and spearhead USDA’s Data Science Training Program. Kai is passionate about utilizing quantitative methods for social good. At Vassar\, they made an effort to weave together their own “quantitative social science” curriculum: majoring in math\, minoring in urban studies\, and housing their thesis in the economics department along with a computer science advisor. Among their favorite experiences at Vassar was working as a Q-Tutor and SI. After graduation\, Kai worked as a predoctoral research fellow at Harvard\, contributing to academic papers on economic mobility and inequality. However\, as life happens\, they made a major pivot by going into consulting next. In the process\, they learned how to prioritize mental health and balance. They aspire to return to academia later in their career.
URL:https://pages.vassar.edu/mathstats/event/lava-kai-matheson-vc-19/
LOCATION:Rockefeller Hall 310
CATEGORIES:LAVA
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240422T170000
DTEND;TZID=America/New_York:20240422T180000
DTSTAMP:20240411T022158Z
CREATED:20230926T031022Z
LAST-MODIFIED:20240411T022158Z
UID:148-1713805200-1713808800@pages.vassar.edu
SUMMARY:(Henry Seely White Lecture I)\, Bhramar Mukherjee\, University of Michigan
DESCRIPTION:Join us on Monday April 22 at 5PM in Rocky 300 for the first of two Henry Seely White Lectures delivered by Professor Bhramar Mukherjee\, University of Michigan. \nNote: This is the first of two lectures in the Henry Seely White Lecture Series. The second lecture is on Tuesday April 23 at 3PM. \nTitle: The Data Struggle of the Unseen \nAbstract: Despite several proposed roadmaps to increase diversity in scientific research\, most of the world’s research data are collected on people of European ancestry. We rely on summary statistics from historically privileged populations and then devise clever statistical methods to transfer/transport them for cross-ancestry use. In this talk\, I would first argue the obvious: for building fair algorithms we need fair training datasets. However\, till we have reached the dream of equitable big data at a global scale\, statisticians have an important role to play. In fact we have the perfect tools to study the “unobserved” through modeling of missing data\, selection bias and alike. I will share examples from my personal journey as a statistician where doing good and timely statistical work with imperfect data quantified important disparity in health outcomes and led to policy impact. I will conclude the talk with a call to arms for statisticians to lead efforts for creating\, curating\, collecting data and pioneering new scientific studies\, not just remain on the design and analytic fringes. As public health statisticians\, our job is not just to predict\, but to prevent. The talk is based on years of work with my students and colleagues at the Department of Biostatistics\, University of Michigan and inspired by the transformative experience we shared as a statistical team working on the COVID-19 pandemic.
URL:https://pages.vassar.edu/mathstats/event/henry-seely-white-lecture1/
LOCATION:Rockefeller Hall 300
CATEGORIES:Annual,HSW
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240423T150000
DTEND;TZID=America/New_York:20240423T160000
DTSTAMP:20240411T022047Z
CREATED:20240321T162134Z
LAST-MODIFIED:20240411T022047Z
UID:537-1713884400-1713888000@pages.vassar.edu
SUMMARY:(Henry Seely White Lecture II)\, Bhramar Mukherjee\, University of Michigan
DESCRIPTION:Join us on Tuesday April 23 at 3PM in Rocky 300 for the second of two Henry Seely White Lectures delivered by Professor Bhramar Mukherjee\, University of Michigan. \nNote:  This is the second of two lectures in the Henry Seely White Lecture Series. The first lecture is on Monday April 22 at 5PM. \nTitle: Analysis of “Big” Real-World Health Care Data: Promises and Perils \nAbstract: Using administrative patient-care data such as Electronic Health Records and medical/Pharmaceutical claims for population-based scientific research have become increasingly common. With vast sample sizes leading to very small standard errors\, researchers need to pay more attention to potential biases in the estimates of association parameters of interest\, specifically to biases that do not diminish with increasing sample size. Of these multiple sources of biases\, in this talk\, we primarily focus on understanding selection bias. We present an analytical framework for understanding selection bias and arriving at bias-reduced inference using external data from a target population. We illustrate our methods via case-studies in cancer and COVID-19. We try to highlight that sampling and study design are at the heart of analysis of big data. This is joint work with many students and colleagues at the University of Michigan School of Public Health.
URL:https://pages.vassar.edu/mathstats/event/henry-seely-white-lecture2/
LOCATION:Rockefeller Hall 300
CATEGORIES:Annual,HSW
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240426T150000
DTEND;TZID=America/New_York:20240426T160000
DTSTAMP:20240908T234154Z
CREATED:20240316T135933Z
LAST-MODIFIED:20240908T234154Z
UID:524-1714143600-1714147200@pages.vassar.edu
SUMMARY:(Colloquium) Leo Goldmakher 4/26
DESCRIPTION:Some Fascinating Characters in Number Theory \nAre there infinitely many primes of the form n^2+1\, where n is an integer? No one knows. In fact\, there’s no example of any (single variable) polynomial of degree 2 or greater that’s been proved to output infinitely many primes. By contrast\, the linear polynomial n+1 outputs infinitely many primes\, a fact that’s been known for over 2000 years. Rather less trivially\, Dirichlet proved in 1837 that any linear polynomial of the form an+b with a\, b coprime must output infinitely many primes. To make his proof work\, Dirichlet introduced certain nice functions called characters\, which evolved (over the course of the next hundred years) into fundamental objects of study in algebra and number theory. I will discuss some of the history and mathematics of Dirichlet’s characters\, including a very recent and simple characterization of them that seems to have been previously overlooked.
URL:https://pages.vassar.edu/mathstats/event/colloquium-leo-goldmakher-4-26/
CATEGORIES:Colloquium
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