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DTSTAMP:20260225T091422
DTSTART;TZID=America/Detroit:20260309T150000
DTEND;TZID=America/Detroit:20260309T160000
SUMMARY:Workshop / Seminar:HEP-Astro Seminar | A frequentist view on cosmological neutrinos and dark-energy constraints
DESCRIPTION:The DESI galaxy survey has recently placed the tightest constraint on the sum of neutrino masses to date. For such effects “below the detection limit”\, where data can only infer upper bounds\, Bayesian and frequentist methods can give important complimentary information. I will begin with an overview of the frequentist profile-likelihood method\, its advantages and limitations. Using a frequentist and Bayesian toolbox\, I will discuss neutrino mass constraints from Planck and DESI data. In particular\, I will focus on the impact of different assumptions about the neutrino mass hierarchy on the inferred mass bounds. Further\, I will compare Bayesian and frequentist constraints on evolving dark energy from recent cosmological data.
UID:145458-21897372@events.umich.edu
URL:https://events.umich.edu/event/145458
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Physics,Science
LOCATION:West Hall - 340
CONTACT:
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DTSTAMP:20260204T094256
DTSTART;TZID=America/Detroit:20260309T150000
DTEND;TZID=America/Detroit:20260309T160000
SUMMARY:Lecture / Discussion:Intersections of AI\, Photonics\, and Scientific Discovery
DESCRIPTION:Abstract: Artificial intelligence is beginning to transform the way we do science and engineering—not only by analyzing data\, but increasingly by generating hypotheses\, designing experiments\, and even running them. Photonics plays a dual role in this story: it provides some of the most promising physical platforms for AI hardware\, while also serving as a rich testbed for applying AI itself. I will discuss how conventional “black box” AI and more interpretable approaches can both uncover structure in complex systems\, and how large language models point toward a future where significant parts of scientific discovery may be automated. I will also highlight how robotics\, combined with AI\, is moving us closer to self-driving laboratories. While my examples will often come from photonics\, the broader message is that these developments foreshadow a profound shift in how science is practiced across disciplines.\n\nBio: Marin Soljačić is a Professor of Physics at MIT. He is a founder of a few companies\, including WiTricity Corporation (2007)\, Lightelligence (2017) and Axiomatic (2024). His main research interests are in artificial intelligence as well as electromagnetic phenomena\, focusing on nanophotonics\, non-linear optics\, and wireless power transfer. He is a co-author of more than 300 scientific articles\, more than 100 issued US patents\, and he has been invited to give more than 100 invited talks at conferences and universities around the world. He is a recipient of the Adolph Lomb medal from the Optical Society of America (2005)\, and the TR35 award of the Technology Review magazine (2006). In 2008\, he was awarded a MacArthur fellowship “genius” grant. He is an international member of the Croatian Academy of Engineering since 2009. In 2011 he became a Young Global Leader (YGL) of the World Economic Forum. In 2014\, he was awarded Blavatnik National Award\, as well as Invented Here! (Boston Patent Law Association). In 2017\, he was awarded “The Order of the Croatian Daystar\, with the image of Ruđer Bošković”\, the Croatian President’s top medal for Science. In 2017\, the Croatian President also awarded him with “The Order of the Croatian Interlace” medal. He was a Highly Cited Researcher according to WoS for 2019\, 2020\, 2021\, 2022\, 2023\, 2024 & 2025. In 2023\, he was awarded Max Born award of Optica.
UID:145036-21896571@events.umich.edu
URL:https://events.umich.edu/event/145036
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:College Of Engineering,Computer Engineering,Computer Science And Engineering,Electrical And Computer Engineering,Electrical Engineering and Computer Science,engineering,Lecture
LOCATION:Lurie Robert H. Engin. Ctr - Johnson Rooms (3rd Floor)
CONTACT:
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