BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Asia/Kolkata BEGIN:STANDARD DTSTART:19451014T230000 TZOFFSETFROM:+0630 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260619T052014Z UID:CAC0BFE9-0458-4757-BE7D-5640515270D9 DTSTART;TZID=Asia/Kolkata:20260622T180000 DTEND;TZID=Asia/Kolkata:20260622T180200 DESCRIPTION:IEEE Sensors Council Delhi - Rajasthan Chapter\, IEEE Sensors C ouncil Vardhaman SBC and IEEE Sensors Council Hyderabad Chapter in associa tion with IEEE India Council Presents a webinar series on Advances in Sens ors and Sensor Systems.\n\nWebinar-1: Hardware–Analytics Co-Design for T rust-Enhanced Gas Sensing\n\nDate: 22nd June\, 2026\n\nTime: 6-7 PM (IST)\ n\nGas sensing is becoming critical for applications ranging from gas spec iation of indoor and outdoor air-quality to monitoring of energy-assets\, precision agriculture\, noninvasive medical diagnostics\, and security. Ho wever\, conventional legacy gas sensors rely on single-output designs that struggle with drift and detection of low-concentration analytes in chemic ally complex environments. In this lecture we will present a roadmap towar d next-generation multi-output gas sensors: inspired by proven traditional analytical instruments such as gas chromatography and spectroscopy\, we w ill show how their underlying mathematical principles can be translated in to new sensing designs to improve selectivity\, stability\, and reliabilit y. The central focus of this lecture is understanding of importance of har dware–analytics co-design. Machine learning (ML) cannot fully succeed wh en sensor outputs contain insufficient independent information. Thus\, eme rging multi-output sensor architectures - enabled by independent excitatio n variables\, advances in electronics\, and edge analytics - create the in formation richness needed for multi-analyte discrimination\, drift correct ion\, and robust calibration. Using multiple examples from research teams worldwide\, we will connect foundational principles to practical design st rategies and illustrate commercialization pathways. We will provide a syst ems-level understanding of how to design multi-output gas sensors to achie ve trusted performance in chemically complex environments.\n\n[]\n\nVirtua l: https://events.vtools.ieee.org/m/562842 LOCATION:Virtual: https://events.vtools.ieee.org/m/562842 ORGANIZER:sangeeta.singh@ieee.org SEQUENCE:23 SUMMARY:IEEE Sensors Council Delhi-Rajasthan\, Vardhaman SBC\, Hyderabad Ch apter DL on "Hardware–Analytics Co-Design for Trust-Enhanced Gas Sensing " URL;VALUE=URI:https://events.vtools.ieee.org/m/562842 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-bottom: 0c m\; text-align: justify\; line-height: normal\;"><span lang="EN-US" style= "font-size: 12.0pt\; font-family: 'Times New Roman'\,serif\;">IEEE Sensors Council Delhi - Rajasthan Chapter\, IEEE Sensors Council Vardhaman SBC an d IEEE Sensors Council Hyderabad Chapter in association with IEEE India Co uncil Presents a webinar series on Advances in Sensors and Sensor Systems. </span></p>\n<p class="MsoNormal" style="margin-bottom: 0cm\; text-align: justify\; line-height: normal\;"><strong><span lang="EN-US" style="font-si ze: 12.0pt\; font-family: 'Times New Roman'\,serif\;">Webinar-1: </span><s pan lang="EN-US" style="font-size: 12.0pt\; font-family: 'Times New Roman' \,serif\;">Hardware&ndash\;Analytics Co-Design for Trust-Enhanced Gas Sens ing</span></strong></p>\n<p class="MsoNormal" style="margin-bottom: 0cm\; text-align: justify\; line-height: normal\;"><span lang="EN-US" style="fon t-size: 12.0pt\; font-family: 'Times New Roman'\,serif\;"><strong>Date:&nb sp\;</strong>22nd&nbsp\;June\, 2026</span></p>\n<p class="MsoNormal" style ="margin-bottom: 0cm\; text-align: justify\; line-height: normal\;"><span lang="EN-US" style="font-size: 12.0pt\; font-family: 'Times New Roman'\,se rif\;"><strong>Time:</strong> 6-7 PM (IST)</span></p>\n<p class="MsoNormal " style="margin-bottom: 0cm\; text-align: justify\; line-height: normal\;" ><span lang="EN-US" style="font-size: 12.0pt\; font-family: 'Times New Rom an'\,serif\;">Gas sensing is becoming critical for applications ranging fr om gas speciation of indoor and outdoor air-quality<span style="mso-spacer un: yes\;">&nbsp\; </span>to monitoring of energy-assets\, precision agric ulture\, noninvasive medical diagnostics\, and security. However\, convent ional legacy gas sensors rely on single-output designs that struggle with drift and detection of low-concentration analytes in chemically complex en vironments. In this lecture we will present a roadmap toward next-generati on multi-output gas sensors: inspired by proven traditional analytical ins truments such as gas chromatography and spectroscopy\, we will show how th eir underlying mathematical principles can be translated into new sensing designs to improve selectivity\, stability\, and reliability. The central focus of this lecture is understanding of importance of hardware&ndash\;an alytics co-design. Machine learning (ML) cannot fully succeed when sensor outputs contain insufficient independent information. Thus\, emerging mult i-output sensor architectures - enabled by independent excitation variable s\, advances in electronics\, and edge analytics - create the information richness needed for multi-analyte discrimination\, drift correction\, and robust calibration. Using multiple examples from research teams worldwide\ , we will connect foundational principles to practical design strategies a nd illustrate commercialization pathways. We will provide a systems-level understanding of how to design multi-output gas sensors to achieve trusted performance in chemically complex environments.<span style="mso-spacerun: yes\;">&nbsp\;&nbsp\;</span></span></p>\n<p class="MsoNormal" style="marg in-bottom: 0cm\; text-align: justify\; line-height: normal\;"><img src="ht tps://events.vtools.ieee.org/vtools_ui/media/display/a5886274-0dcd-45e8-b2 05-610a76cb7d64" alt="" width="1020" height="574"></p> END:VEVENT END:VCALENDAR