Lead the product development team for AI Factory and AI @ Edge. The AI Factory is a solution consisting of infrastructure (Computation, Storage and Network), AI Optimized Network Design, Control Software Stacks Cluster Operation and Multitenancy, Application for training/inference operations for AI pre-training, customization/tuning, optimization and inference. Edge AI solutions focus primarily on distributed training and inference. Direct the product strategy, engineering requirements/design and large customer engagements support. Establish roadmap for Generative AI and Edge AI. Engage with key partners for infrastructure, ISV applications, operating software and technology level. Serve as product owner for Dell AI Factory product solution. Redesigned AI Factory to match requirements of modern GenAI including inference sizing and performance. Led with Nvidia the development of Enterprise Reference Architecture for AI implementation for enterprise use cases. First to complete this important Nvidia certification. 24 Patents granted and 43 pending as of June 2025.
Member of the Digital Twin Consortium Steering Committee Board representing Dell Technologies.
Chief Technology Officer for Edge at Dell Technologies ISG CTO organization. Focus on Edge platform design and application of Edge technology to current enterprise use cases and emerging use cases of generative AI, simulation(XR/VR) and autonomous system control. Structured Edge partner design program, Edge patent committee co-chair, member of AI/ML Architecture Review Board. Technical focus areas in Distributed Systems Design using Model Driven Agent-Based control, Edge Orchestration, Edge Infrastructure Control, Scheduling Algorithm design, AI Discriminative/Generative ensemble and multimodal approaches for AI/ML control, AI/ML workload support, MultiCloud Execution Environment, Edge Information-Data Management, Edge Native Hardware evolution. Patents in distributed data management, Generative and Discriminative AI/ML, MultiTier/MultiObjective scheduling orchestration algorithms, cybersecurity and software defined edge. 14 Patents granted and 37 pending as of July 2024, see below.
Lead for edge technology development, composable systems technology strategy and autonomous technical ecosystem development for the Global Office of CTO for Dell Technologies. Areas of technology research include edge distributed systems management, edge communications, platform as a service, autonomous systems, applied artificial intelligence, distributed data management, hybrid multi-cloud architecture, policy/control/orchestration. Lead an architecture and development team focused on customer collaborative research. Chair the Dell Automotive Design Authority Council providing technical leadership of Dell's automotive vertical. Vice-Chairman award winner for 2020. Patents in the area of edge platform control, distributed data management, cloud native application management, scheduling and autonomic control.
Early stage venture focused on experimental stratospheric communications platform for Broadband and 5G access. Directed technology strategy, spectrum acquisition, system planning and system design in conjunction with tier 1 US defense contractor. Led technology discussions with prospective investors, government regulators and partners.
Lead HPE efforts in Communications segment in developing innovative solutions addressing transformation to Cloud, SDN and IP based platforms and business models. Set strategy, Design Solutions and Develop Business engagement. Significant engagements with clients in net new business areas.
Member of the Digital Twin Consortium Steering Committee Board representing Dell Technologies
Chairman of Board of Directors (2012 - 2014) and Member of Board of Directors (2007 - 2014) of Technology Association of Dallas Fort Worth focusing on Entrepreneurial Support, STEM, Legislative Advocacy, and Technology Industry Development
Senior member (2024), recognized by Dallas section (2008), recognized for leadership in industry relations (2011), best presentation at Envision 2020 conference, keynote speaker at IEEE/ACM Symposium on Edge Computation
Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by an endpoint controller associated with a device, an initial resource buffer from a local controller; in response to obtaining the initial resource buffer: maintaining the initial resource buffer during task provision for the device; obtaining device metrics based on performance of tasks on the device; making a determination that a resource buffer change event is identified; and in response to the determination: updating the initial resource buffer based on the resource buffer change event.
Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes identifying, by a local controller associated with an DMC domain, a domain scheduling event associated with a scheduling job; and in response to identifying the domain scheduling event: identifying a candidate list of devices of the DMC domain to schedule tasks associated with the scheduling job based on a location and service level objectives; refining the candidate list of devices based on device configuration requirements, device management requirements, and security requirements to generate a final candidate list; scheduling tasks to devices using the final candidate list; generating scheduling assignments and provisioning command packages based on the scheduled tasks; providing the scheduling assignments and the provision command packages to the devices; and updating a graph based on the scheduling assignments.