William Au

William Au has over 20 years of experience in the software engineering industry. William began their career in 2000 as a Principal Engineer at Mentor Graphics. In 2003, they joined Cadence Design Systems as a Senior Member of Consulting Staff, where they invented the concept of electrical isomorphism and improved the performance of hierarchical circuit simulation. In 2004, they joined Sun Microsystems as a Staff Engineer, where they increased the capacity of the circuit simulator by more than 10 times and invented a new algorithm for linear parallel solver. In 2010, they joined Oracle as a Senior Principal Engineer, where they were the technical lead and architect in electromigration analysis tool in processor design. In 2019, they joined Nutanix as a Staff Data Scientist, where they initiated a project of sentiment analysis of all customer communication and developed a forecasting program with deep neural network (DNN) under tensorflow platform for customer future purchases. William is currently a Principal Software Engineer at Rain Neuromorphics, a position they have held since 2022.

William Au obtained a M.A. B.A. in Engineering from the University of Cambridge and a Doctor of Philosophy - PhD from the Massachusetts Institute of Technology. William has also obtained a number of certifications, including XCS234 - Reinforcement Learning from Stanford Online in September 2022, Sequences, Time Series and Prediction from Coursera in September 2019, Natural Language Processing in TensorFlow from Coursera in August 2019, Databases and SQL for Data Science from Coursera in July 2019, Open Source tools for Data Science from Coursera Course Certificates in July 2019, What is Data Science? from Coursera in June 2019, Sequence Models from Coursera in March 2018, Divide and Conquer, Sorting and Searching, and Randomized Algorithms from Coursera in February 2018, SQL for Data Science from Coursera in January 2018, Convolutional Neural Networks from Coursera in November 2017, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization from Coursera in October 2017, Machine Learning from Coursera in October 2017, and Neural Networks and Deep Learning from Coursera in October 2017.