BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20250309T030000 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:20250602T183019Z UID:F97D5646-4297-46A5-B727-975ECE8FF216 DTSTART;TZID=America/New_York:20250602T100000 DTEND;TZID=America/New_York:20250602T110000 DESCRIPTION:Speaker 1:\n\nThe rapid pace of technological advancement and t he complexity of real-world challenges demand that computational intellige nce (CI) research quickly move from innovation to application. Traditional project management methods often fall short in supporting the iterative n ature of CI development. This presentation explores how Agile methodologie s can bridge this gap by enabling faster\, more adaptive application of ac ademic research to real-world projects. Agile's emphasis on iterative deve lopment\, prototyping\, and testing allows teams to run experiments and re fine solutions based on real-time feedback. It fosters cross-disciplinary collaboration between data scientists\, domain experts\, and stakeholders\ , ensuring that CI systems are co-created efficiently. Real-world examples demonstrate how Agile accelerates the implementation of neural networks\, fuzzy logic\, and evolutionary algorithms across domains like adaptive le arning\, decision-making\, and optimization. Core Agile practices—such a s sprint planning\, daily stand-ups\, and incremental delivery—support c ontinuous validation and refinement while promoting ethical\, explainable applications in critical sectors like healthcare\, finance\, and smart inf rastructure. Ultimately\, Agile transforms CI development from a static pr ocess to a dynamic\, evolving approach that enhances both impact and resil ience.\n\nSpeaker 2:\n\nHow computational intelligence techniques—such a s machine learning\, neural networks\, and optimization algorithms—are b eing practically applied to enhance go-to-market strategies and optimize r evenue operations at scale.\n\nSpeaker(s): Samant\, Roshin\n\nAgenda: \nTo pic1 : From Research to Real-World: Agile Implementation in Computational Intelligence Projects\n\nTopic 2: Bridging Strategy and AI: Real-World App lications of Computational Intelligence in GTM and Revenue Operations\n\nV irtual: https://events.vtools.ieee.org/m/486345 LOCATION:Virtual: https://events.vtools.ieee.org/m/486345 ORGANIZER:swethachinta@ieee.org;ysuthari@ieee.org SEQUENCE:217 SUMMARY:Agile Implementation in Computational Intelligence Projects and Rea l-World Applications of Computational Intelligence in GTM and Revenue Oper ations URL;VALUE=URI:https://events.vtools.ieee.org/m/486345 X-ALT-DESC:Description: <br /><div class="page" title="Page 1">\n<div class ="layoutArea">\n<div class="column">\n<p>Speaker 1:</p>\n<p>The rapid pace of technological advancement and the complexity of real-world challenges demand that computational intelligence (CI) research quickly move from inn ovation to application. Traditional project management methods often fall short in supporting the iterative nature of CI development. This presentat ion explores how Agile methodologies can bridge this gap by enabling faste r\, more adaptive application of academic research to real-world projects. Agile's emphasis on iterative development\, prototyping\, and testing all ows teams to run experiments and refine solutions based on real-time feedb ack. It fosters cross-disciplinary collaboration between data scientists\, domain experts\, and stakeholders\, ensuring that CI systems are co-creat ed efficiently. Real-world examples demonstrate how Agile accelerates the implementation of neural networks\, fuzzy logic\, and evolutionary algorit hms across domains like adaptive learning\, decision-making\, and optimiza tion. Core Agile practices&mdash\;such as sprint planning\, daily stand-up s\, and incremental delivery&mdash\;support continuous validation and refi nement while promoting ethical\, explainable applications in critical sect ors like healthcare\, finance\, and smart infrastructure. Ultimately\, Agi le transforms CI development from a static process to a dynamic\, evolving approach that enhances both impact and resilience.</p>\n<p>Speaker 2:</p> \n<p>How computational intelligence techniques&mdash\;such as machine lear ning\, neural networks\, and optimization algorithms&mdash\;are being prac tically applied to enhance go-to-market strategies and optimize revenue op erations at scale.</p>\n<p>&nbsp\;</p>\n<p>&nbsp\;</p>\n<p>&nbsp\;</p>\n</ div>\n</div>\n</div><br /><br />Agenda: <br /><p>Topic1 : From Research to Real-World: Agile Implementation in Computational Intelligence Projects</ p>\n<p>Topic 2: Bridging Strategy and AI: Real-World Applications of Compu tational Intelligence in GTM and Revenue Operations</p> END:VEVENT END:VCALENDAR