Greg Lavender is Senior Vice President and Chief Technology Officer at VMware. He is responsible for engaging with strategic VMware and Dell/EMC customers to enable senior IT executives and technology architects to understand the importance of having a comprehensive cloud strategy and end-to-end systems architecture for secure private, hybrid and public cloud services. He works closely with all VMware R&D business units to ensure that the product portfolio is aligned to meet customer expectations from a strategic vendor, and to ensure that VMware’s Professional Services organization is trained on the latest cloud principles and architectures so that customers are successful in adopting VMware technologies to enable their businesses. Greg has 36 years of experience in software and hardware product engineering and advanced R&D in industry research labs and academia. He holds BS, MS and PhD degrees in Computer Science. Before joining VMware in January 2018, Greg was Managing Director and CTO for Cloud Architecture and Technology Engineering at Citigroup for six years, where he led the global transformation of Citi IT to adopt modern mobile technology, cloud IaaS & PaaS, big data & advanced analytics, high performance computing, and agile software development models. Prior to Citi, Greg was Corporate Vice President of Network Software Engineering at Cisco, where he led network operating system engineering and platform independent protocol engineering for both enterprise and data center switching and routing products, including the next generation virtualized multi-core network operating system for software-defined networking. Prior to Cisco, Greg spent 10 years at Sun Microsystems in various engineering leadership roles, including VP of Engineering for the Solaris Operating System.
Enjoyed being part of VMware's annual internal Machine Learning conference last week. ML is key to intelligent IT infrastructure, an important emerging workload, and promising for what we call "Intrinsic Sustainability." Find out more on our ML approach: https://bddy.me/3kDR0Pc