Chirag Dekate is a VP, Analyst at Gartner, where his research focus is on providing strategic advice to CIOs and IT leaders on AI Operationalization infrastructures, Scaling from AI Pilots into Production across a Hybrid and Multicloud Context, with an emphasis on AI (machine learning and deep learning) infrastructures, high-performance computing, and emerging compute architectures (quantum computing).
Dr. Dekate's coverage areas include MLOps, AI Orchestration and Automation Platforms, Emerging Compute Platforms, Design Patterns and Hybrid Multicloud Infrastructures to Productize Enterprise AI, Advanced Systems and Accelerator Architectures (GPUs, Neuromorphic, DNN ASIC and beyond). Dr. Dekate has in-depth expertise in Advanced Analytics and high-performance computing, technical computing simulations, extreme scale graph processing and future of compute infrastructures. He has rich experience in strategy development and execution from vendor ecosystems, having led multiple successful campaigns and product launches.
Before joining Gartner, Dr. Dekate led strategy development and execution for WW commercial HPC vertical markets including financial services, oil and gas, manufacturing, earth sciences and more. Prior to that, Dr. Dekate was a Research Manager at IDC, covering HPC, big data and cloud computing, where he managed HPC quarterly tracking and strategic consulting engagements with vendors, end users and governments.
Sr. Manager, WW Commercial HPC Verticals
Research Manager, HPC and Big Data
Center for Computation and Technology, LSU
Data and Analytics Leaders
Data Center Infrastructure
Analytics, BI and Data Science Solutions
Executive Leadership: Artificial Intelligence
Doctor of Philosophy, Computer Science (HPC, Exascale Computing, Execution Models, Extreme Scale Graph Processing), Louisiana State University
Master of Science, System Science (Grid and Cloud Computing), Louisiana State University
Bachelor of Science, Computer Science, Louisiana State University
1MLOps, AI pilots to production, AI Orchestration Platforms, Hybrid Multicloud AI Operationalization, Infrastructures for Productionalizing AI
2Platform Ops for AI, Machine learning, deep learning, artificial intelligence infrastructures and best practices. Design Patterns to Productize AI
3High-performance computing applications, infrastructure and operations (HPC), supercomputing, HPC clouds
4Emerging Compute Architectures (processors, interconnects, machine learning technologies and memory technologies), GPU, Neuromorphic, DNN ASICs etc.