Zaid Tashman
R&D Data Scientist, Accenture Labs

Zaid Tashman is a R&D data scientist at Accenture Labs exploring new research problems in the areas of probabilistic programming, casual inference, and stochastic optimization. Zaid has a progressive experience in recommendation systems, customer behavior analysis, survival modeling, failure time prediction, hierarchical Bayesian networks, and anomaly detection. Previously, Zaid was a senior data scientist at ABB where he led the analytics efforts within ABB’s IoT platform serving all of their business units and a senior data scientist at Spacetime Insights, a Silicon Valley IoT startup where he successfully led and completed many machine learning projects in areas of predictive maintenance, anomaly detection, fraud detection, and optimization. Zaid holds a MSc in electrical engineering from Washington State University.

Sessions

11:05–11:45 Thursday, 17 October 2019

Location: Buckingham Room - Palace Suite

Rethinking predictive maintenance

Implementing AI

Secondary topics: Ethics, Security, and Privacy, Machine Learning, Mobile Computing, IoT, Edge, Temporal data and time-series

Zaid Tashman (Accenture Labs)

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Today traditional approaches to predictive maintenance fall short. Zaid Tashman dives into a novel approach to predict rare events using a probabilistic model, the mixed membership hidden Markov model, highlighting the model's interpretability, its ability to incorporate expert knowledge, and how the model was used to predict the failure of water pumps in developing countries. Read more.