Engineering Data You Can Trust: Synthetic Data and the Hidden Privacy Failures in Enterprise AI.

DATE:            Thursday, September 24, 2026

PLACE :        March First Brewing & Distilling (Voltage Room) (see below for directions)

TIME :           5:30 p.m.  Social Time & Registration,  6:00 p.m.  Dinner,    7:00 p.m.  Presentation  (45-60 min)

COST:            $15- $20, See information in Reservations

ABOUT THE MEETING:   Enterprise AI systems depend on large volumes of rich data, and much of that data is personal and regulated. This session looks at how organizations are resolving that tension with synthetic data, which is artificially generated data that preserves the statistical patterns of real data without copying any real record. Participants will see what synthetic data actually is, how it is generated, and where enterprises are using it today, including software testing, AI model training, analytics, and safe data sharing. The session also explains why traditional masking and anonymization fall short, and then follows a single piece of data through a modern AI pipeline to show where privacy quietly breaks, including training data memorization and the collapse of consent boundaries in foundation models. It closes with the practical controls and governance steps that keep these systems trustworthy. Attendees will leave with a clear understanding of how synthetic data works, where it fits in an enterprise AI strategy, and what questions to ask of any AI system that touches personal data.

ABOUT THE PRESENTER:   Harshavardhan Peddireddy is a Platform Architect at Meijer Inc. and a PhD Candidate in Artificial Intelligence at the University of the Cumberlands. He has more than 18 years of experience in data privacy engineering across the healthcare insurance, enterprise financial services, and retail industries, with hands-on work in data masking, synthetic data generation, tokenization, and de-identification for environments regulated under HIPAA and PCI DSS. He is an IEEE Senior Member and a Fellow of Information Privacy with the International Association of Privacy Professionals, and holds the CIPP/US, CDPSE, AIGP, and PMP certifications. He serves as a peer reviewer for IEEE Access, Springer Nature, and Wiley, and is a regular invited speaker on synthetic data, privacy engineering, and AI governance at international conferences and professional forums.

MENU SELECTIONS:  Menu: Pepperoni Pizza, Cheese Pizza, Bourbon Chicken Pizza, Buffalo Chicken Pizza, Chicken Bacon Ranch Pizza, Margherita Pizza, Italian Sausage Pizza, Veggie Lovers Pizza

LOCATION:  March First Brewing & Distilling (Voltage Room) 7885 E Kemper Rd, Cincinnati, OH 45249 (39.27955510134435, -84.34861587323701)

RESERVATIONS:  MEETING RESERVATION LINK.  Please click on the appropriate link and complete the reservation.  Cost is $15 for members advanced registration.  Non-members cost is $20 cash at the door. (registration IS required)

Reservations close at 11:59 PM on September 23, 2026.

DINNER RESERVATION CANCELLATION POLICY
An email to reserve.cinti@ieee.org prior to the close of reservations is required to properly cancel your reservation.

All Reservations must be made by September 23rd, 2026

WALK-INS (those without reservations): Due to catering and seating arrangements, reservations are required for this meeting

PE CREDITS:  Depending on the subject matter, attendance at IEEE Cincinnati Section Meetings now qualifies the attendee for Professional Development Hours towards renewal of Professional Engineers Licenses.  Required documentation will be available following the meeting if qualified!  The Section Meetings also provide a great opportunity to network with fellow engineers in the area.