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NanoManufacturing

Michael De Volder, Engineering Department - IfM
 
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This is a superlist of research seminars in Cambridge open to all interested researchers. Weekly extracts of this list (plus additional talks not yet on talks.cam) are emailed to a distribution list of over 200 Cambridge researchers by Research Services Division. To join the list click here https://lists.cam.ac.uk/mailman/listinfo/biophy-cure For more information see http://www.cure.group.cam.ac.uk or email drs45[at]rsd.cam.ac.uk
Updated: 39 min 9 sec ago

Thu 05 Jun 14:00: Talk title tbc

Thu, 24/04/2025 - 14:39
Talk title tbc

Abstract not available

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Fri 02 May 16:00: Connecting scales in the SMEFT at the LHC and future colliders

Thu, 24/04/2025 - 11:07
Connecting scales in the SMEFT at the LHC and future colliders

Given the absence of direct evidence for new resonances beyond the Standard Model at the LHC so far, a complementary strategy to search for new physics in an indirect way is provided by the Standard Model Effective Field Theory (SMEFT). Global interpretations within the SMEFT framework, including their matching to UV-complete models, involve energy scales spanning several orders of magnitude. In this talk, I will demonstrate how to relate these measurements among them in terms of a common energy scale as enabled by the Renormalisation Group Equations. I will then quantify their impact in a global SMEFT fit to LEP and LHC data, presenting results in terms of SMEFT parameters as well as UV couplings. Finally, I will show a brief application to the Higgs self-coupling using projected data from the HL-LHC and the FCC -ee.

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Fri 09 May 14:00: Extrapolation-aware statistical machine learning

Thu, 24/04/2025 - 10:08
Extrapolation-aware statistical machine learning

Nonparametric function estimation and prediction with moderate or large dimension of the covariates are particularly susceptible to extrapolation, because data points are typically far apart from each other in such moderate or higher dimension. Thus, there is a need to have machine learning methods that are extrapolation-aware, i.e. that automatically perform well (in a sense) when extrapolation occurs. Without such extrapolation-aware techniques, inference from standard machine learning and nonparametric procedures may be poor or invalid. We introduce a novel conceptual framework and introduce Xtrapolation which allows for extrapolation-aware inference with any ML algorithm.

This is joint work with Niklas Pfister (Lakera AI)

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Tue 13 May 16:00: No One Left Behind: Building Low-Cost Wearables for Health Equity Zoom: https://cam-ac-uk.zoom.us/j/84016051221?pwd=TmAESuU8bWf3VDhZV1AuPb5CejZgJq.1

Thu, 24/04/2025 - 09:58
No One Left Behind: Building Low-Cost Wearables for Health Equity

Abstract: Wearable devices such as Apple Watch and Fitbit wristband allow users to track their health statistics around the clock. They have become increasingly popular over the past few years. However, in the context of underdeveloped regions where people may earn less than 5 US dollars a day, these wearable devices are still pricey and thus constitute a critical bottleneck in their adoption. In this talk, I will present our past and ongoing works on repurposing electronic wastes, particularly everyday earphones into health trackers – from heart rate monitoring, heart sound recovery, all the way down to pulse wave velocity estimation. Moreover, I will summarize our observations and insights gained from the pilot study at Senegal. I believe this research creates a holistic approach toward recycling and repurposing electronic waste while fostering a sustainable and equitable future.

Bio: Longfei Shangguan is an Assistant Professor at the University of Pittsburgh. His research interest lies in mobile health, wireless networks, and IoT. His work has been awarded the Best Paper Award at MobiCom 2024, Best Paper Runner-up Award at MobiCom 2021, Distinguished Paper Award at Ubicomp 2017, and Best Paper Award at TrustCom 2014. He is the recipient of an NSF CAREER Award in 2024, a Google Research Scholar Award in 2023, and the AIoTSys Young Scientist Award in 2023. Longfei earned his Ph.D. from HKUST in 2015 and his bachelor’s degree from Xidian University in 2011.

Zoom: https://cam-ac-uk.zoom.us/j/84016051221?pwd=TmAESuU8bWf3VDhZV1AuPb5CejZgJq.1

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Thu 15 May 11:30: TBC

Thu, 24/04/2025 - 09:21
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Wed 21 May 14:00: Title to be confirmed

Wed, 23/04/2025 - 20:07
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Tue 13 May 13:00: Title to be confirmed

Wed, 23/04/2025 - 16:58
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Wed 11 Jun 13:00: Title to be confirmed

Wed, 23/04/2025 - 16:25
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Wed 04 Jun 13:00: Title to be confirmed

Wed, 23/04/2025 - 16:24
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Wed 23 Apr 17:00: bla bla

Wed, 23/04/2025 - 16:01
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Wed 23 Apr 17:00: bla bla

Wed, 23/04/2025 - 13:04
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Fri 09 May 14:00: Title to be confirmed

Wed, 23/04/2025 - 11:58
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