BEGIN:VCALENDAR VERSION:2.0 PRODID:-//ChamberMaster//Event Calendar 2.0//EN METHOD:PUBLISH X-PUBLISHED-TTL:P1H REFRESH-INTERVAL:P1H CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU DTSTART:20070101T000000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:Eastern Daylight Time END:DAYLIGHT BEGIN:STANDARD RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU DTSTART:20070101T000000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:Eastern Standard Time END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20260505T120000 DTEND;TZID=America/New_York:20260505T130000 X-MICROSOFT-CDO-ALLDAYEVENT:FALSE SUMMARY:CYTO U Webinar: Detector Technologies in Flow Cytometry | Presented by Keegan Owsley DESCRIPTION:Modern flow cytometry relies on a diverse set of optical detectors\, each with distinct physical operating principles\, gain mechanisms\, and noise characteristics that directly impact system performance. Selecting and optimizing a detector is therefore not a one‑size‑fits‑all decision\, but a trade‑space shaped by sensitivity requirements\, dynamic range\, speed\, stability\, and application context. This talk presents a practical\, physics‑grounded overview of the major detector technologies used in flow cytometry\, including photodiodes\, avalanche photodiodes\, photomultiplier tubes\, silicon photomultipliers\, and camera‑based sensors. For each class of detector\, we will examine how signal is generated and amplified\, how gain is implemented and controlled\, and the dominant noise sources that limit performance. We will then put this knowledge into practical context for an advanced flow user trying to optimize their system for a particular application.\n\nLearning Objectives: Participants will receive an overview of different detector technologies\, learn how they function\, why they are used in different circumstances\, and how they can be optimized for use in flow. Who Should Attend: Imaging Cytometrists\, Industry Scientists (vendor-agnostic\; tool developers\; method innovators)\, Shared Resource Laboratory (SRL) Managers and Staff\, Unconventional Cytometrists (plant\, water\, microbes\, etc.)\n\nTHE SPEAKER\nKeegan Owsley is an Associate Principal Engineer in the Advanced Technology Group at Waters Biosciences (formerly BD Biosciences)\, where he focuses on next‑generation technologies for flow cytometry\, imaging flow\, and cell sorting. He brings over twelve years of experience designing and engineering flow cytometry systems\, with hands‑on work spanning fluidics\, electronics\, firmware\, and software. In his current role\, he has contributed to the development of the FACSDiscover platform\, and continues to work on technologies powering the next generation of flow sorters.Prior to joining BD\, Keegan worked at a flow imaging startup developing novel imaging‑based cytometry technology that later became the CellView platform following its acquisition. Earlier in his career\, he pursued research in inertial microfluidics\, building microscale systems for particle and cell manipulation\, and before that conducted undergraduate research in synthetic biology. Outside of work\, he is the proud father of two young daughters\, ages six and three.REGISTER: ISAC Learning: Detector Technologies in Flow Cytometry X-ALT-DESC;FMTTYPE=text/html:

Modern flow cytometry relies on a diverse set of optical detectors\, each with distinct physical operating principles\, gain mechanisms\, and noise characteristics that directly impact system performance. Selecting and optimizing a detector is therefore not a one‑size‑fits‑all decision\, but a trade‑space shaped by sensitivity requirements\, dynamic range\, speed\, stability\, and application context. This talk presents a practical\, physics‑grounded overview of the major detector technologies used in flow cytometry\, including photodiodes\, avalanche photodiodes\, photomultiplier tubes\, silicon photomultipliers\, and camera‑based sensors. For each class of detector\, we will examine how signal is generated and amplified\, how gain is implemented and controlled\, and the dominant noise sources that limit performance. We will then put this knowledge into practical context for an advanced flow user trying to optimize their system for a particular application.

Learning Objectives: Participants will receive an overview of different detector technologies\, learn how they function\, why they are used in different circumstances\, and how they can be optimized for use in flow. Who Should Attend: Imaging Cytometrists\, Industry Scientists (vendor-agnostic\; tool developers\; method innovators)\, Shared Resource Laboratory (SRL) Managers and Staff\, Unconventional Cytometrists (plant\, water\, microbes\, etc.)

THE SPEAKER
Keegan Owsley is an Associate Principal Engineer in the Advanced Technology Group at Waters Biosciences (formerly BD Biosciences)\, where he focuses on next‑generation technologies for flow cytometry\, imaging flow\, and cell sorting. He brings over twelve years of experience designing and engineering flow cytometry systems\, with hands‑on work spanning fluidics\, electronics\, firmware\, and software. In his current role\, he has contributed to the development of the FACSDiscover platform\, and continues to work on technologies powering the next generation of flow sorters.

Prior to joining BD\, Keegan worked at a flow imaging startup developing novel imaging‑based cytometry technology that later became the CellView platform following its acquisition. Earlier in his career\, he pursued research in inertial microfluidics\, building microscale systems for particle and cell manipulation\, and before that conducted undergraduate research in synthetic biology. Outside of work\, he is the proud father of two young daughters\, ages six and three.

LOCATION: UID:e.4653.1415014 SEQUENCE:3 DTSTAMP:20260407T022311Z URL:https://internationalsocietyforadvancementofcytometryisac.growthzoneapp.com/eventcalendar/Details/cyto-u-webinar-detector-technologies-in-flow-cytometry-presented-by-keegan-owsley-1672427?sourceTypeId=Hub END:VEVENT END:VCALENDAR