BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0600 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:CDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:CST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260620T145550Z UID:2EDDC7A7-60DD-4EDD-B062-59D5277C0466 DTSTART;TZID=America/Chicago:20260618T183000 DTEND;TZID=America/Chicago:20260618T200000 DESCRIPTION:Artificial Intelligence is rapidly transforming software engine ering\, extending beyond code generation into code quality\, security\, go vernance\, and engineering productivity. As organizations increasingly ado pt AI-assisted development\, traditional code review processes are struggl ing to keep pace with growing code volumes\, accelerated release cycles\, and the emergence of AI- generated code. This presentation explores how AI -powered code review solutions can augment human expertise by identifying defects\, security vulnerabilities\, architectural concerns\, performance issues\, and compliance risks earlier in the development lifecycle. The se ssion presents a practical framework for integrating AI into enterprise co de review workflows while maintaining human accountability and engineering governance. Attendees will learn how leading organizations are leveraging AI-assisted reviews to improve code quality\, reduce review cycle times\, enhance developer productivity\, and strengthen security posture. The pre sentation also examines key challenges\, including false positives\, expla inability\, governance\, intellectual property considerations\, and respon sible AI adoption.\n\nSpeaker(s): Himanshu Pathek\n\nAgenda: \n6:25 to 6:3 5 PM - Open for participants to enter and network.\n6:35 to 6:40 PM - IEEE LM and CTCN Business meeting and to introduce speaker.\n6:40 to 7:55PM - Formal Program and Q&A.\n\nVirtual: https://events.vtools.ieee.org/m/56228 4 LOCATION:Virtual: https://events.vtools.ieee.org/m/562284 ORGANIZER:bill.martino@ieee.org, uday.kanike@ieee.org,jayasudha.yedalla@gma il.com SEQUENCE:39 SUMMARY:IEEE CTS CTCN/LMAG Zoom Meeting\, 6-18-2026\, "AUTOMATED TESTING US ING ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML)" URL;VALUE=URI:https://events.vtools.ieee.org/m/562284 X-ALT-DESC:Description: <br /><p>Artificial Intelligence is rapidly transfo rming software engineering\, extending beyond code generation into code qu ality\, security\, governance\, and engineering productivity. As organizat ions increasingly adopt AI-assisted development\, traditional code review processes are struggling to keep pace with growing code volumes\, accelera ted release cycles\, and the emergence of AI- generated code. This present ation explores how AI-powered code review solutions can augment human expe rtise by identifying defects\, security vulnerabilities\, architectural co ncerns\, performance issues\, and compliance risks earlier in the developm ent lifecycle. The session presents a practical framework for integrating AI into enterprise code review workflows while maintaining human accountab ility and engineering governance. Attendees will learn how leading organiz ations are leveraging AI-assisted reviews to improve code quality\, reduce review cycle times\, enhance developer productivity\, and strengthen secu rity posture. The presentation also examines key challenges\, including fa lse positives\, explainability\, governance\, intellectual property consid erations\, and responsible AI adoption.</p><br /><br />Agenda: <br /><div dir="ltr" data-setdir="false">6:25 to 6:35 PM - Open for participants to e nter and network.&nbsp\;</div>\n<div dir="ltr" data-setdir="false">6:35 to 6:40 PM - IEEE LM and CTCN Business meeting and to introduce speaker.</di v>\n<div dir="ltr" data-setdir="false">6:40 to 7:55PM - Formal Program and Q&amp\;A.&nbsp\;</div> END:VEVENT END:VCALENDAR