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Harnessing AI and ML for Enhanced Project Controls – A Case Study

Anand Rathinem

Head of North American & Europe Operations at Wrench Solutions

Session description
Anand Rathinem is the Head of North American & Europe Operations at WRENCH Solutions, bringing extensive experience across multiple industries. Previously, he held key positions at John Deere, including IT Division Leader and SAP Program Manager in China. His leadership journey also includes roles as Director of Operations and Marketing Manager at Unimobile, Inc., as well as Management Consultant at PwC. Anand has contributed to academia as an Administrative Faculty member at the University of Nevada, Reno. He holds a Bachelor of Engineering in Civil Engineering from the University Visvesvaraya College of Engineering and a Master of Science in Civil Engineering from the University of Nevada, Reno. Anand is set to share his insights on “Harnessing AI and ML for Enhanced Project Controls – A Case Study.”

Anand Rathinem will share his insights on practical strategies and real-world examples that illustrate the transformative power of AI in effectively managing complex projects. He will discuss how predictive analytics, machine learning, and real-time data processing can revolutionize traditional project controls, providing more accurate forecasts and enhancing decision-making capabilities. Anand will explore applications such as predictive analytics for project risk management, AI-driven planning, scheduling, and resource allocation, as well as real-time data analysis for proactive monitoring. His session aims to highlight how these advanced technologies can significantly improve project outcomes and efficiency.

Key Topics
  • Practical strategies and real-world examples that demonstrate the transformative power of AI in managing complex projects effectively.
  • Learn how predictive analytics, machine learning, and real-time data processing can transform traditional project controls, offering more accurate forecasts and smarter decision-making capabilities.
  • Predictive analytics for project risk management, AI-driven planning, scheduling and resource allocation, and real-time data analysis for proactive monitoring.


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