My expertise and research includes machine learning, data science and signal processing with applications in timeseries forecating, internet measurement and digital advertising.   I am a Senior Applied Scientist at Amazon, and before that, I was the Director of the Machine Learning and Signal Processing master's program in the ECE department at the University of Wisconsin.  Before that, I was a Director and Principal Data Scientist at Comscore where I lead a team of data scientists and software engineers.  And even before that, I was a post-doc and a PhD student, and before that, I was an engineer at Motorola.   My research interests include:

• machine learning for time-series forecasting

• internet measurement and building enormous graphs (see internet device graphs, graphing by example, and crumbling cookies -- which won best paper award at AdKDD 2019)

  • $10 billion impact:  reflecting on the device graph work

• more scholarly satisfying topics - 

  • learning theory and adaptive sensing (see adaptive sensing and bandits - Lil'UCB)

  • information theory, optimization, signal processing (estimation via convex relaxations)

  • I'm very interested in building machine learning algorithms that are gracefully wrong, and correct in aggregate (see ad blockers)