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Ali Ghodsi
San Francisco, California,United States
Find Ali Ghodsi's Email
Find Ali Ghodsi's PhoneWho Is Ali Ghodsi?
Ali Ghodsi is the CEO and Co-Founder of Databricks, a leading data and AI company known for its innovative work in the field of big data processing and machine learning. He is also an Adjunct Professor at UC Berkeley. His expertise spans distributed systems, algorithms, and large-scale data processing. As CEO of Databricks, he leads the company in its mission to democratize data and AI, empowering organizations to solve their toughest challenges with data-driven insights. Prior to Databricks, Ali held research and academic positions at UC Berkeley, KTH Royal Institute of Technology, and the Swedish Institute of Computer Science.
How Did Ali Ghodsi's Career Path Shape Their Journey?
Ali Ghodsi's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
What Are Ali Ghodsi's Key Achievements?
CEO & Co-Founder at Databricks
Led Databricks from its inception to a leading data and AI company, driving innovation in big data processing and machine learning.
Adjunct Professor at UC Berkeley
Shares expertise and contributes to the academic community through teaching and research in computer science.
Co-founded Databricks
Helped create a groundbreaking company using the technology he helped create at the AMPLab at UC Berkeley; he was instrumental in the development of Apache Spark.
What's Ali Ghodsi's Educational Background?
PhD, Computer Science
KTH Royal Institute of Technology - Year 2002
M.B.A, Logistics and Strategic Marketing
Mid Sweden University - Year 1997
MSc, Computer Engineering
Mid Sweden University - Year 1997
Post-doc, Computer Science
University of California, Berkeley
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Company Overview
DatabricksDatabricks is a data and AI company. Databricks unifies data teams around a single platform for data warehousing and AI, enabling them to innovate faster and tackle challenges like massive data migration and transformation, the development of high-quality machine learning models, and the accelerated deployment of AI solutions.
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