Presented By O’Reilly and Intel AI
Put AI to work
Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA
Ramzi Roy Labban

Ramzi Roy Labban
Director, Computer Modeling and Simulation, Consolidated Contractors Company (CCC)


Roy Labban is the director of computer modeling and simulation in the Information Systems Department at Consolidated Contractors Company (CCC), which is ranked among the top 20 international contractors in 2017 by ENR. Roy has 20+ years of experience in software engineering and database application development, business intelligence and analytics, and computer modeling and simulation. Roy is the cofounder and managing partner of a boutique consulting firm focused on delivering business intelligence and analytics for higher education enrollment management. Roy is also the founder and director of a postgraduate coding bootcamp diploma program focusing on new technologies such as the blockchain, artificial intelligence, machine learning, and mobile apps. Roy serves as a member of the Industry Advisory Board of the Computer Science Program (ABET Accredited) at the American University of Science and Technology. He is also a part-time university instructor teaching graduate level courses on computer simulation and machine learning. Roy holds a PhD in construction engineering and management from the University of Alberta and a BE in computer and communications engineering from the American University of Beirut.


4:50pm-5:30pm Friday, September 7, 2018
AI in the Enterprise
Location: Continental 1-3
Secondary topics:  Temporal data and time-series, Transportation and Logistics
Ramzi Roy Labban (Consolidated Contractors Company (CCC))
Average rating: *....
(1.00, 1 rating)
Estimating the performance of heavy earth-moving equipment on large construction projects is a complex task that can be riddled with uncertainty. Ramzi Roy Labban details how CCC uses machine learning, leveraging large datasets of actual performance of trucks on construction sites, to more accurately predict future performance and allow the company to make realistic performance assumptions. Read more.