BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20261001T105909Z UID:FF7CEABA-368A-4748-B20D-E261EB6A3FAE DTSTART;TZID=America/New_York:20261002T130000 DTEND;TZID=America/New_York:20261002T140000 DESCRIPTION:This talk will present research from Dr. Jiang’s Aerosol Rese arch Lab at Lawrence Technological University. Jiang’s lab specializes i n developing novel aerosol sensing techniques for health-related applicati ons\, with two major research focuses: ultrafine particle detection and va ping aerosol characterization. Ultrafine particles are airborne particles with diameters smaller than 100 nm. These particles can pose severe health risks\, as they can enter the body through the lungs and potentially reac h organs throughout the body. Optical detection of ultrafine particles is particularly challenging due to their small sizes. Jiang’s lab investiga tes novel optical aerosol sensing schemes based on nanoplasmonic structure s\, achieving significantly better detection limits than existing optical approaches. To study and monitor the adverse health consequences associate d with electronic cigarette use\, Jiang’s lab develops compact optical a erosol sensors that can be integrated into electronic cigarettes to conven iently monitor users’ daily puff topography in real time. Such sensors h old promise for supporting efforts to mitigate the health risks of vaping and enabling quantitative measurements for vaping-related research. Jiang ’s lab has also introduced machine-learning-based multispectral sensing of vaping aerosols to quantify size-resolved aerosol mass in concentrated vaping aerosols. This new approach enables predictions of aerosol particle deposition in human airways.\n\nCo-sponsored by: College of Engineering\, Lawrence Technological University\n\nSpeaker(s): Dr. Hao \, \n\nAgenda: \ nTime: 1:00 – 2:00PM\n\nRoom: E159\, Bldg: Engineering\, 21000 West Ten Mile Road\, Southfield\, Michigan\, United States\, 48075 LOCATION:Room: E159\, Bldg: Engineering\, 21000 West Ten Mile Road\, Southf ield\, Michigan\, United States\, 48075 ORGANIZER:mguduri@ltu.edu SEQUENCE:3 SUMMARY:Aerosol Sensing for Health: Optical Detection of Particulate Matter in Vaping and Environmental Aerosols URL;VALUE=URI:https://events.vtools.ieee.org/m/580535 X-ALT-DESC:Description: <br /><p>This talk will present research from Dr. J iang&rsquo\;s Aerosol Research Lab at Lawrence Technological University. J iang&rsquo\;s lab specializes in developing novel aerosol sensing techniqu es for health-related applications\, with two major research focuses: ultr afine particle detection and vaping aerosol characterization. Ultrafine pa rticles are airborne particles with diameters smaller than 100 nm. These p articles can pose severe health risks\, as they can enter the body through the lungs and potentially reach organs throughout the body. Optical detec tion of ultrafine particles is particularly challenging due to their small sizes. Jiang&rsquo\;s lab investigates novel optical aerosol sensing sche mes based on nanoplasmonic structures\, achieving significantly better det ection limits than existing optical approaches. To study and monitor the a dverse health consequences associated with electronic cigarette use\, Jian g&rsquo\;s lab develops compact optical aerosol sensors that can be integr ated into electronic cigarettes to conveniently monitor users&rsquo\; dail y puff topography in real time. Such sensors hold promise for supporting e fforts to mitigate the health risks of vaping and enabling quantitative me asurements for vaping-related research. Jiang&rsquo\;s lab has also introd uced machine-learning-based multispectral sensing of vaping aerosols to qu antify size-resolved aerosol mass in concentrated vaping aerosols. This ne w approach enables predictions of aerosol particle deposition in human air ways.<br><br><br></p><br /><br />Agenda: <br /><p>Time: 1:00 &ndash\; 2:00 PM</p> END:VEVENT END:VCALENDAR