BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Denver BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0700 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:MDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0600 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:MST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260331T044353Z UID:CBC204CA-3671-48DD-A4AD-01FD09A3A4E1 DTSTART;TZID=America/Denver:20260914T233800 DTEND;TZID=America/Denver:20260918T234000 DESCRIPTION:THE DETAILS TO BE ANNOUNCED SOON\n\nScientific and technologica l advances now allow us to measure\, model\, and intervene across environm ental\, biological\, and societal dimensions of health. This seasonal scho ol equips participants to integrate exposomics and biosensing into informe d decision-ready frameworks\, including digital twins\, to address global health challenges.\n\nThe central focus of this seasonal school is exposom ics enabled by multimodal sensing\, with particular emphasis on how divers e sensing technologies can be integrated to capture the multi-dimensional\ , dynamic nature of human exposures. The program is not intended as a broa d survey of sensors\; rather\, it targets a specific scientific challenge: how to design and deploy coordinated sensing systems that generate cohere nt\, high-resolution exposome data across environmental\, biological\, and behavioral domains.\n\nExposomics requires moving beyond isolated measure ments toward simultaneous\, longitudinal characterization of multiple expo sure layers. To address this\, the workshop focuses on the integration of multimodal sensors\, including wearable and ambient devices\, geospatial t echnologies\, and molecular-level sensors such as proteomics and genomics biosensors. Together\, these approaches enable the collection of complemen tary data streams—external exposures\, internal biological responses\, a nd contextual factors—forming a more complete and actionable representat ion of the exposome.\n\nA key theme is the transition from fragmented data collection to structured\, multi-dimensional exposure datasets. Participa nts will explore how different sensing modalities can be aligned across te mporal\, spatial\, and biological scales\, and how these data can be harmo nized to support downstream analysis and modeling. Particular attention is given to challenges inherent to multimodal sensing\, including high quali ty data collection and integration\, calibration across platforms\, variab ility in resolution\, and uncertainty quantification.\n\nThe workshop furt her emphasizes how multimodal exposome data can inform integrated analytic al frameworks\, including AI-driven models and digital twins\, that captur e interactions among exposures and their cumulative effects on health. In this context\, sensing is framed as a foundational layer that determines t he quality\, interpretability\, and utility of all subsequent analyses.\n\ nBy focusing on multimodal sensing as the primary mechanism for operationa lizing exposomics\, the seasonal school provides a clear and cohesive them atic direction. It equips participants to design exposure measurement stra tegies that are not only technologically advanced\, but also systematicall y integrated\, scalable\, and aligned with real-world health applications. This approach advances exposomics from a conceptual framework to a data-r ich\, actionable science capable of supporting the future of health.\n\nCo -sponsored by: International Institute for Biosensing\n\nMinneapolis\, Min nesota\, United States\, Virtual: https://events.vtools.ieee.org/m/551995 LOCATION:Minneapolis\, Minnesota\, United States\, Virtual: https://events. vtools.ieee.org/m/551995 ORGANIZER:patricia.kh@gmail.com SEQUENCE:0 SUMMARY:Mapping the Invisible: Exposomics\, Biosensing\, and the Future of Health (SAVE the DATE) URL;VALUE=URI:https://events.vtools.ieee.org/m/551995 X-ALT-DESC:Description: <br /><p dir="ltr">THE DETAILS TO BE ANNOUNCED SOON </p>\n<p dir="ltr">&nbsp\;</p>\n<p dir="ltr">Scientific and technological advances now allow us to measure\, model\, and intervene across environmen tal\, biological\, and societal dimensions of health. This seasonal school equips participants to integrate exposomics and biosensing into informed decision-ready frameworks\, including digital twins\, to address global he alth challenges.</p>\n<p dir="ltr">The central focus of this seasonal scho ol is exposomics enabled by multimodal sensing\, with particular emphasis on how diverse sensing technologies can be integrated to capture the multi -dimensional\, dynamic nature of human exposures. The program is not inten ded as a broad survey of sensors\; rather\, it targets a specific scientif ic challenge: how to design and deploy coordinated sensing systems that ge nerate coherent\, high-resolution exposome data across environmental\, bio logical\, and behavioral domains.</p>\n<p dir="ltr">Exposomics requires mo ving beyond isolated measurements toward simultaneous\, longitudinal chara cterization of multiple exposure layers. To address this\, the workshop fo cuses on the integration of multimodal sensors\, including wearable and am bient devices\, geospatial technologies\, and molecular-level sensors such as proteomics and genomics biosensors. Together\, these approaches enable the collection of complementary data streams&mdash\;external exposures\, internal biological responses\, and contextual factors&mdash\;forming a mo re complete and actionable representation of the exposome.</p>\n<p dir="lt r">A key theme is the transition from fragmented data collection to struct ured\, multi-dimensional exposure datasets. Participants will explore how different sensing modalities can be aligned across temporal\, spatial\, an d biological scales\, and how these data can be harmonized to support down stream analysis and modeling. Particular attention is given to challenges inherent to multimodal sensing\, including high quality data collection an d integration\, calibration across platforms\, variability in resolution\, and uncertainty quantification.</p>\n<p dir="ltr">The workshop further em phasizes how multimodal exposome data can inform integrated analytical fra meworks\, including AI-driven models and digital twins\, that capture inte ractions among exposures and their cumulative effects on health. In this c ontext\, sensing is framed as a foundational layer that determines the qua lity\, interpretability\, and utility of all subsequent analyses.</p>\n<p dir="ltr">By focusing on multimodal sensing as the primary mechanism for o perationalizing exposomics\, the seasonal school provides a clear and cohe sive thematic direction. It equips participants to design exposure measure ment strategies that are not only technologically advanced\, but also syst ematically integrated\, scalable\, and aligned with real-world health appl ications. This approach advances exposomics from a conceptual framework to a data-rich\, actionable science capable of supporting the future of heal th.</p> END:VEVENT END:VCALENDAR