Ash Munshi
Chief Executive Officer
Technology, BigData
San Fransciso, CA, USA
Ash Munshi is the Chief Executive Officer for Pepperdata. Before joining Pepperdata, Ash was executive chairman for Marianas Labs, a deep learning startup sold in December 2015. Prior to that, he was CEO for Graphite Systems, a big data storage startup that was sold to EMC DSSD in August 2015. Ash also served as CTO of Yahoo, as a CEO of both public and private companies, and is on the board of several technology startups. Ash attended Harvard University, Brown University, and Stanford University.
Ash Munshi’s LinkedIn profile states:
Senior Technology Executive with broad and deep technical and business knowledge along with proven ability to motivate teams and deliver results at scale. Strategic thinker able to quickly synthesize data and transform it into market opportunity and competitive advantage. World-class recruiter that can build technical and GTM teams across a large spectrum of technologies and verticals.
Business Skills / Knowledge:
• Public: Comp, Audit, Governance committees; experience with BOD activists
• CEO: Public Company (MSC) and many startups
• GM / Exec: P&L responsibility at scale
• CTO
• Turnarounds
• M&A
• Take Private
• Spinouts
• Startup founder / investor
• Strategic Sales
• Industries: Aerospace, Automotive, Pharma, Medical Device, Technology, Agriculture
Management Skills / Knowledge:
• Hiring: world class people at all levels
• Leadership: hands on and from the front. Deep, broad and strategic.
• Style: Personal, friendly but always challenging. High energy.
• Organizational: restructuring, outsourcing, managed very large teams
Technical Skills / Knowledge:
• Semiconductor Fabrication: Recipe Processing, control system software
• Silicon: Microprocessor Architecture; ISA design, register, cache design
• Systems Software: Compilers (patents), Tools, Unix Kernel
• Systems Architecture: SMP, DSM
• Database and Tools: RDBMS, NOSQL, …
• Machine Learning: Recommendation system (patents), NLP, UGC , image based ML
• Large Scale Processing: Hadoop, Spark, Hive, Kubernetes
• Advertising: Display Ad Optimization, Serving, Targeting
• Content: Topic Modeling, Personalization
