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:20251102T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20251231T150758Z UID:0704E868-429B-4E66-A3AC-F4BA2545616C DTSTART;TZID=America/New_York:20251211T120000 DTEND;TZID=America/New_York:20251211T130000 DESCRIPTION:Series of Virtual Technical & Professionals Talks\n\nTalk II by Dr. Dimah Dera\n\nTitle of the Talk: Trustworthy and Adaptive AI for Imag ing Systems\n\nAbstract: This work advances the development of trustworthy and adaptive artificial intelligence for imaging applications. Building o n Bayesian uncertainty estimation and probabilistic learning\, the propose d framework enables imaging systems to assess their confidence\, adapt to changing environments\, and maintain reliability under data drift. Applica tions span medical image segmentation\, remote-sensing anomaly detection\, and autonomous vision\, where uncertainty-guided adaptation enhances safe ty\, interpretability\, and robustness. The approach integrates statistica l signal processing with deep learning to create imaging-based AI systems that are self-aware\, resilient\, and transparent in real-world conditions .\n\nSpeaker Bio: Dimah Dera is the Frederick and Anna B. Wiedman II Profe ssor at the Chester F. Carlson Center for Imaging Science at the Rochester Institute of Technology. She holds a Ph.D. and M.S. in Electrical and Com puter Engineering and an M.A. in Mathematics from Rowan University. Dr. De ra received the NSF CISE Research Initiation Initiative (CRII) Award in 20 23 and an NSF REU supplement in 2024 for her work on robust and trustworth y machine learning. Her research focuses on developing adaptive and uncert ainty-aware AI systems grounded in Bayesian theory and statistical signal processing for applications in healthcare\, remote sensing\, and autonomou s imaging. She is a recipient of several honors\, including the IEEE Best Paper Award (2019)\, the NJ Tech Council STEM Innovator to Watch Award (20 19)\, and the IEEE Benjamin Franklin Key Award (2021).\n\n[]\n\nVirtual: h ttps://events.vtools.ieee.org/m/514664 LOCATION:Virtual: https://events.vtools.ieee.org/m/514664 ORGANIZER:deyasini.majumdar@ieee.org SEQUENCE:28 SUMMARY:Virtual Speaker Series - 2025: Talk II URL;VALUE=URI:https://events.vtools.ieee.org/m/514664 X-ALT-DESC:Description: <br /><p><strong>Series of Virtual Technical &amp\; Professionals Talks</strong></p>\n<p><strong>Talk II by Dr. Dimah Dera</s trong></p>\n<p class="MsoNormal" style="text-align: justify\;"><strong>Tit le of the Talk:&nbsp\;</strong><em>Trustworthy and Adaptive AI for Imaging Systems</em></p>\n<p class="MsoNormal" style="text-align: justify\;"><str ong>Abstract: </strong>This work advances the development of trustworthy a nd adaptive artificial intelligence for imaging applications. Building on Bayesian uncertainty estimation and probabilistic learning\, the proposed framework enables imaging systems to assess their confidence\, adapt to ch anging environments\, and maintain reliability under data drift. Applicati ons span medical image segmentation\, remote-sensing anomaly detection\, a nd autonomous vision\, where uncertainty-guided adaptation enhances safety \, interpretability\, and robustness. The approach integrates statistical signal processing with deep learning to create imaging-based AI systems th at are self-aware\, resilient\, and transparent in real-world conditions.< /p>\n<p class="MsoNormal" style="text-align: justify\;"><strong>Speaker Bi o: </strong><span class="il">Dimah</span> Dera is the Frederick and Anna B . Wiedman II Professor at the Chester F. Carlson Center for Imaging Scienc e at the Rochester Institute of Technology. She holds a Ph.D. and M.S. in Electrical and Computer Engineering and an M.A. in Mathematics from Rowan University. Dr. Dera received the NSF CISE Research Initiation Initiative (CRII) Award in 2023 and an NSF REU supplement in 2024 for her work on rob ust and trustworthy machine learning. Her research focuses on developing a daptive and uncertainty-aware AI systems grounded in Bayesian theory and s tatistical signal processing for applications in healthcare\, remote sensi ng\, and autonomous imaging. She is a recipient of several honors\, includ ing the IEEE Best Paper Award (2019)\, the NJ Tech Council STEM Innovator to Watch Award (2019)\, and the IEEE Benjamin Franklin Key Award (2021).</ p>\n<p class="MsoNormal" style="text-align: justify\;">&nbsp\;</p>\n<p cla ss="MsoNormal"><img style="display: block\; margin-left: auto\; margin-rig ht: auto\;" src="https://events.vtools.ieee.org/vtools_ui/media/display/ad c2aadf-18c8-4121-adf1-03928d6aac9e" alt="" width="467" height="605"></p> END:VEVENT END:VCALENDAR