Jeff Dean

Jeff Dean

• Google Senior Fellow and Head of Google’s AI division
• Played an instrumental role in various Google applications and deep learning projects
• Received numerous awards for his contributions in the field of AI
• Philanthropist

Jeff Dean is an acclaimed computer scientist and software engineer who leads Google’s artificial intelligence (AI) division. He has a Ph.D. in Computer Science from the University of Washington, a B.S. summa cum laude from the University of Minnesota in Computer Science and Economics, and was elected to the National Academy of Engineering in recognition of his work on the science and engineering of large-scale distributed computer systems.

Life before Google saw Dean work at the World Health Organisation’s Global Programme on AIDS, where he developed software for the statistical modeling and forecasting of the HIV/AIDS epidemic at the time. He also worked at DEC/Compaq’s Western Research laboratory, profiling tools, microprocessor architecture, and information retrieval.

Dean currently works at Google where he is a Google Senior Fellow in the Research Group and head of their AI division, leading the Google Brain project.  His involvement thus far includes large-scale distributed systems, performance monitoring, compression techniques, information retrieval, application of machine learning, microprocessor architecture, compiler optimizations, and the development of new products that organise existing information in new, interesting ways.

Since joining Google in 1999, Jeff Dean has worked on numerous Google projects. Amongst these he includes:

• The design and implementation of Google’s initial advertising serving system.
• The design and implementation of five generations of the company’s crawling, indexing, and query serving systems.
• The initial development of Google’s AdSense for Content
• The development of Protocol Buffers that encode structured data and generates wrappers for the manipulation of objects in different languages. Google makes extensive use of Protocol Buffers for most RPC protocols and the storage of structured information in various persistent storage systems.
• The initial production serving system work for the Google News product and some aspects of Google’s search ranking algorithms.
• The design and implementation of Google’s first generation automated job scheduling system for managing a cluster of machines.
• The design and implementation of prototyping infrastructure for rapid development and experimentation with new ranking algorithms.
• The design and implementation of MapReduce. This programme helps simplify the development of large-scale data processing applications.

He has also been involved in certain production and design aspects of Google’s BigTable, Google Translate, certain internal tools used by Google, and the training and deployment of certain deep learning models. Of the latter, TensorFlow is now an open source project hosted on GitHub.

Jeff has received much recognition for his work in the field of Ai and deep learning. He was elected to the National Academy of Engineering, named a Fellow of the Association for Computing Machinery (ACM), and named a Fellow of the American Association for the Advancement of Sciences (AAAS).

In 2011, Jeff and his wife started the Hopper-Dean Foundation. The foundation makes philanthropic grants. In 2016, it gave a million dollars

Dean and his wife, Heidi Hopper, started the Hopper-Dean Foundation and began making philanthropic grants in 2011. In 2016, the foundation contributed $1 million to MIT to support programs that promote diversity in STEM.

Jeff Dean – Speaker

As a speaker, Jeff Dean is more than imminently qualified to talk on all aspects of AI, deep learning, their current applications, and how they will influence humanity’s future. Someone who regularly contributes to various scientific journals, Jeff is also a world-class speaker who has addressed various audiences globally on various topics pertaining to his field.

Speaking Topics

• Algorithms and Theory
• Data Management
• Distributed Systems and Parallel Computing
• Information Retrieval and the Web
• Machine Intelligence
• Machine Perception
• Machine Translation
• Natural Language Processing