Asaf Somekh

Co-Founder & CEO at Iguazio

Asaf Somekh is the Co-Founder and CEO of Iguazio, who’s data science platform supports enterprises in getting their AI projects from research to production and building real-time AI applications. Iguazio has raised $72M from prominent investors such as Bosch, Verizon Ventures, Samsung, CME Group, Dell. Asaf holds a BSc in computer engineering from the Technion Israel Institute of Technology and an MBA from IMD in Switzerland. He has been at the helm of the tech and data scene for more than twenty years, and prior to founding Iguazio has held various leadership roles in early stage startups as well as public corporations in R&D, Marketing and Business Development.

Daniel Meehan

CEO & Founder of Padsquad

As the Founder of three companies, Meehan has operated at the intersection of digital content and advertising technology for the better part of two decades. Launched in late 2012, PadSquad is a creative technology and media company that designs, develops and activates mobile-first ad experiences for some of the largest brand marketers in the United States. It’s innovative ad campaigns have won numerous industry awards, working with amazing clients such as 7-Eleven, Hewlett-Packard, Novartis, Ben & Jerry’s, Purina and Mastercard, leading to consistent growth of the company that found it named to industry lists such as the INC 500 Fastest Growing Companies, Crain’s Fast 50 list of fastest growing private companies in New York and the Financial Times America’s Fastest Growing Companies list. Prior to launching PadSquad, Meehan created Haven Home Media, a digital media company that was acquired by Trusted Media Brands, owner of media properties such as The Family Handyman, Taste of Home and Reader’s Digest. He also held stints at HGTV and The DIY Network, responsible for online content strategy and business development. Meehan resides near Princeton, NJ with his wife and three boys.

WATCH LIVE: September 22 @ 3:35PM – 3:55PM ET

Predicting Ad Performance in Real Time Based on Multi-Variant Data

In this talk, Asaf will demonstrate how to build a predictive AI application which can analyze events and impressions from online ads in real-time. He will show how to run and analyze thousands of real-time and batch events per second for ad performance optimization. By creating an automated ML pipeline that supports the entire data science lifecycle, abstracts away DevOps, and includes advanced feature engineering capabilities, engagement can be monitored per individual ad location, enabling enhanced performance while drastically reducing media costs.