Jeff Dean. Jeffrey Adgate Dean (born July 23, 1968) is an American computer scientist and software engineer. Since 2018, he has been the lead of Google AI. He was appointed Google's chief scientist in 2023 after the merger of DeepMind and Google Brain into Google DeepMind.

Education 
Dean received a B.S., summa cum laude, from the University of Minnesota in computer science and economics in 1990. His undergraduate thesis was on neural networks in C programming, advised by Vipin Kumar.

He received a Ph.D. in computer science from the University of Washington in 1996, working under Craig Chambers on compilers and whole-program optimization techniques for object-oriented programming languages. He was elected to the National Academy of Engineering in 2009, which recognized his work on "the science and engineering of large-scale distributed computer systems".

Career 
Before joining Google, Dean worked at DEC/Compaq's Western Research Laboratory, where he worked on profiling tools, microprocessor architecture and information retrieval. Much of his work was completed in close collaboration with Sanjay Ghemawat.

Before graduate school, he worked at the World Health Organization's Global Programme on AIDS, developing software for statistical modeling and forecasting of the HIV/AIDS pandemic.

Dean joined Google in mid-1999. He joined Google X in 2011 to investigate deep neural networks, which had just resurged in popularity. This ended with "the cat neuron paper", a deep belief network trained by unsupervised learning on YouTube videos. This project morphed into Google Brain, also formed in 2011. Jeff Dean became its leader in 2012. In April 2018, he was appointed the head of Google's artificial intelligence division, after John Giannandrea left to lead Apple's AI projects.

While at Google, he designed and implemented large portions of the company's advertising, crawling, indexing and query serving systems, along with various pieces of the distributed computing infrastructure that underlies most of Google's products. At various times, he has also worked on improving search quality, statistical machine translation and internal software development tools and has had significant involvement in the engineering hiring process.

The projects Dean has worked on include:
 Original design of Protocol Buffers, an open-source data interchange format.
 Spanner, a scalable, multi-version, globally distributed, and synchronously replicated database
 Some of the production system design and statistical machine translation system for Google Translate
 Bigtable, a large-scale semi-structured storage system
 MapReduce, a system for large-scale data processing applications
 LevelDB, an open-source on-disk key-value store
 DistBelief, a proprietary machine-learning system for distributed training of deep neural networks. The "Belief" part is because it could be used to train deep belief networks. It was eventually refactored into TensorFlow. It was used to train the network in "the cat neuron paper".
 TensorFlow, an open-source machine-learning software library. He was the primary designers and implementors of the initial system.
 Pathways, an asynchronous distributed dataflow system for neural networks. It was used in PaLM.

He was an early member of Google Brain, a team that studies large-scale artificial neural networks, and he has headed artificial intelligence efforts since they were split from Google Search.

In 2020, after Timnit Gebru tried to publish a paper, Dean wrote that an internal review concluded that the paper "ignored too much relevant research" and did not meet Google's bar for publication, also noting that it was submitted one day instead of at least two weeks before the deadline. Gebru challenged Google's research review process and wrote that if her concerns were not addressed, they could "work on an end date". Google responded that they could not meet her conditions and accepted her resignation immediately. Gebru stated that she was fired, leading to a controversy. Dean later published a memo on Google's approach to the review process.

In 2023, DeepMind was merged with Google Brain to form a unified AI research unit, Google DeepMind. As part of this reorganization, Dean became Google's chief scientist.

Philanthropy 
Dean and his wife, Heidi Hopper, started the Hopper-Dean Foundation and began making philanthropic grants in 2011. In 2016, the foundation gave $2 million each to UC Berkeley, Massachusetts Institute of Technology, University of Washington, Stanford University and Carnegie Mellon University to support programs that promote diversity in science, technology, engineering and mathematics (STEM).

Personal life 
Dean is married and has two daughters.

He is the subject of an Internet meme for "Jeff Dean facts". Similar to Chuck Norris facts, the Jeff Dean facts exaggerate his programming powers. For example:Once, in early 2002, when the index servers went down, Jeff Dean answered user queries manually for two hours. Evals showed a quality improvement of 5 points.

Awards and honors 
 Elected to the National Academy of Engineering (2009)
 Fellow of the Association for Computing Machinery (2009)
 ACM-Infosys Foundation Award (2012)
 ACM SIGOPS Mark Weiser Award (2007)
 Fellow of the American Academy of Arts and Sciences (2016)
 Recipient of the IEEE John von Neumann Medal in 2021

Books 
Dean was interviewed for the 2018 book Architects of Intelligence: The Truth About AI from the People Building it by the American futurist Martin Ford.

Major publications 
 Jeffrey Dean and Sanjay Ghemawat. 2004. MapReduce: Simplified Data Processing on Large Clusters. OSDI'04: Sixth Symposium on Operating System Design and Implementation (December 2004)
 Fay Chang, Jeff Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber. 2006. Bigtable: A Distributed Storage System for Structured Data. OSDI'06: 7th Symposium on Operating System Design and Implementation (October 2006)

See also 
 Sanjay Ghemawat
 MapReduce
 TensorFlow

References

External links 
 Jeff Dean's Google home and publication page

Living people
American computer scientists
American artificial intelligence researchers
University of Washington College of Engineering alumni
University of Minnesota College of Science and Engineering alumni
2009 fellows of the Association for Computing Machinery
Fellows of the American Academy of Arts and Sciences
Members of the United States National Academy of Engineering
Digital Equipment Corporation people
Google employees
Google Fellows
1968 births
Place of birth missing (living people)
Recipients of the ACM Prize in Computing
Open source advocates