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DTSTART;TZID=America/New_York:20260423T133000
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SUMMARY:Boundedness for K-trivial varieties with fibrations
DESCRIPTION:According to the Beauville-Bogomolov decomposition theorem\, any smooth K-trivial variety admits a finite cover by a product of (1) abelian varieties\, (2) strict Calabi-Yau varieties\, and (3) irreducible holomorphic symplectic varieties (IHSV). In a fixed dimension\, all abelian varieties are diffeomorphic\, and indeed deformation equivalent through non-algebraic complex tori. The corresponding question remains largely open for cases (2) and (3). If we assume that a variety of class (2) or (3) admits a non-trivial fibration structure\, then much more can be shown. In particular\, fibered Calabi-Yau threefolds have bounded moduli problem\, and IHSV of a fixed dimension with a Lagrangian fibration have bounded moduli. This is based on joint work with Engel\, Filipazzi\, Mauri\, and Svaldi.\n\nZoom link: https://harvard.zoom.us/j/91784227416?pwd=4tETrJrpUeRxh9WKG5Ujxt4cNBF6N6.1
URL:https://www.math.harvard.edu/event/boundedness-for-k-trivial-varieties-with-fibrations/
LOCATION:CMSA\, 20 Garden St\, G10\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:CMSA Differential Geometry and Physics Seminar
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DTSTART;TZID=America/New_York:20260423T160000
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SUMMARY:Sixth Annual Yip Lecture | Regina Barzilay: Can ML methods design drugs?
DESCRIPTION:Sixth Annual Yip Lecture | Regina Barzilay: Can ML methods design drugs?\n\n\nDate: April 23\, 2026 \nTime: 4:00-5:00 pm ET \nLocation: Harvard Science Center Hall A \nSpeaker: Regina Barzilay\, MIT \nTitle: Can ML methods design drugs? \nAbstract: Today\, life sciences are driven by prohibitively expensive wet lab experimentations\, which limit the pace and scope of discovery. This talk focuses on AI algorithms that enable in-silico modeling of biological processes. Specifically\, I will focus on algorithms for molecular and cellular modeling. I will highlight several successful examples where these algorithms have already transformed drug discovery. In the second part of the talk\, I want to focus on problems where current methods fail to deliver as expected\, motivating the need for algorithmic innovations. \nIn-person registration \nWebinar registration \nRegina Barzilay is a Delta Electronics professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Her research interests are in natural language processing\, applications of deep learning to chemistry and oncology. She is a recipient of various awards including the NSF Career Award\, the MIT Technology Review TR-35 Award\, Microsoft Faculty Fellowship and several Best Paper Awards at NAACL and ACL. In 2017\, she received a MacArthur fellowship\, an ACL fellowship and an AAAI fellowship. She received her Ph.D. in Computer Science from Columbia University\, and spent a year as a postdoc at Cornell University. \nThe Yip Lecture takes place thanks to the support of Dr. Shing-Yiu Yip. \nSee CMSA webpage for more details
URL:https://www.math.harvard.edu/event/sixth-annual-yip-lecture-regina-barzilay/
LOCATION:Science Center Hall A\, 1 Oxford Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:CMSA EVENTS
ATTACH;FMTTYPE=image/jpeg:https://www.math.harvard.edu/wp-content/uploads/yip_2026_final.jpg
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