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DTSTART;TZID=America/New_York:20240918T090000
DTEND;TZID=America/New_York:20240918T103000
DTSTAMP:20260504T063741
CREATED:20240904T181255Z
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UID:10003442-1726650000-1726655400@cmsa.fas.harvard.edu
SUMMARY:CMSA/Tsinghua Math-Science Literature Lecture: Marc Lackenby
DESCRIPTION:CMSA/Tsinghua Math-Science Literature Lecture \nDate: Wednesday\, September 18\, 2024 \nTime: 9:00 – 10:30 am ET \nLocation: Via Zoom Webinar \nSpeaker: Marc Lackenby\, University of Oxford \nTitle: The complexity of knots \nAbstract: In his final paper in 1954\, Alan Turing wrote `No systematic method is yet known by which one can tell whether two knots are the same.’ Within the next 20 years\, Wolfgang Haken and Geoffrey Hemion had discovered such a method. However\, the computational complexity of this problem remains unknown. In my talk\, I will give a survey on this area\, that draws on the work of many low-dimensional topologists and geometers. Unfortunately\, the current upper bounds on the computational complexity of the knot equivalence problem remain quite poor. However\, there are some recent results indicating that\, perhaps\, knots are more tractable than they first seem. Specifically\, I will explain a theorem that provides\, for each knot type K\, a polynomial p_K with the property that any two diagrams of K with n_1 and n_2 crossings differ by at most p_K(n_1) + p_K(n_2) Reidemeister moves. \n\nBeginning in Spring 2020\, the CMSA began hosting a lecture series on literature in the mathematical sciences\, with a focus on significant developments in mathematics that have influenced the discipline\, and the lifetime accomplishments of significant scholars.
URL:https://cmsa.fas.harvard.edu/event/mathscilit2024_ml/
LOCATION:Virtual
CATEGORIES:Math Science Literature Lecture Series,Public Lecture,Special Lectures
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/Mathlit_Lackenby_8.5x11.jpg
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DTSTART;TZID=America/New_York:20240930T153000
DTEND;TZID=America/New_York:20240930T173000
DTSTAMP:20260504T063741
CREATED:20240912T152420Z
LAST-MODIFIED:20250328T150047Z
UID:10003504-1727710200-1727717400@cmsa.fas.harvard.edu
SUMMARY:Machine Learning in Science Education Panel Discussion
DESCRIPTION:Machine Learning in Science Education Panel Discussion\nMonday\, Sep. 30\, 2024\n3:30-5:30 pm ET \nMachine Learning is rapidly influencing many spheres of human activity. As part of the CMSA Mathematics and Machine Learning Program\, this panel discussion will explore current and future uses of Machine Learning in science education. Panelists will make brief presentations\, which will be followed by discussion and audience questions. \nGregory Kestin (Harvard University)\n AI-Supported Activities: Design Principles and Impact on Student Learning \nLogan McCarty (Harvard University)\nSurveying the Landscape: Teaching and Learning with AI \nAlexis Ross (Massachusetts Institute of Technology)\nAdaptive Teaching towards Misconceptions with LLMs \nIlia Sucholutsky (New York University)\n Why should machines have human-like  representations? Towards  student-centric AI tutors \n  \nOrganizers: \n\nDan Freed (Harvard University and CMSA)\nMichael Douglas (CMSA)
URL:https://cmsa.fas.harvard.edu/event/teachingmachinelearning_93024/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Event,MML Meeting,Special Lectures
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/ML_9.30.24_Machine-Learning-in-Science-Education.png
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