
Lily Chen

Alex Cohen

Bala Chidambaram

Prashanth Chakravartula

Marc Hourican
A technical leader, Marc has led the design and construction of large-scale data center projects across the United States as well as in the Middle East and Asia. His projects have included greenfield, brownfield, build to suite, and adaptive reuse projects for colocation, corporate, and hyperscale data center customers.
Before joining CleanArc, Marc held leadership positions at leading data center consultancy firms Orchard Green Associates, Smith Engineering, PLLC and Syska Hennessy Group. Marc takes pride in understanding the technical and cultural nuances required for project execution across geographies. At CleanArc, he takes a collaborative and comprehensive approach to project management and execution, bridging the gaps between infrastructure and design/construction teams as CleanArc works to deliver best-in-class reliability, sustainability, supply chain management and capital efficiency during the entire data center life cycle. Marc holds a BS in Mechanical Engineering from Stevens Institute of Technology and an MS in Real Estate from the NYU Shack Institute of Real Estate.

Prashanth Chakravartula

Ahmed Menshawy
Ahmed Menshawy is the Vice President of AI Engineering at Mastercard. In this role, he leads the AI Engineering team, driving the development and commercialization of AI products that deliver business value across the organization. His work focuses on enabling Mastercard to harness the power of AI to solve complex problems, optimize operations, and enhance customer experiences. Ahmed collaborates with cross-functional teams to bring innovative AI solutions from concept to market, ensuring they align with Mastercard’s strategic objectives
An accomplished author and recognized contributor to the AI community, Ahmed has co-authored Deep Learning with TensorFlow and written Deep Learning by Example. His most recent book, Graph Learning for the Enterprise, published by O’Reilly, provides practical insights into efficiently training and deploying graph learning pipelines at scale