Bruce is a top rated problem solver, communicator, and data scientist. Bruce has a unique strength in bridging software engineering with mathematical algorithms. He has over 15 years of IT experience, engaging in high-visibility, large-scale projects in marketing automation, cloud solutions, Big Data engineering and predictive analytics for top technology companies like Amazon, TeraData, and Life Technologies. He is a certified AWS solutions Architect, with a specialty in Big Data practices, particularly Spark architecture. Bruce published over 100 scientific papers during his academic career, which culminated with a Harvard faculty appointment. In his business pursuits, he continues to draw the best ideas from state-of-the-art research to fuel his Data Science practice.
His previous work includes pioneering research in hospital digitization where he served as a principal investigator for an NIH Grant to investigate efficient network transfer of high density medical images. He subsequently founded a tech startup pursuing eCommerce automation, for which he raised the funding and built up the team and operation. Since then, he has consulted widely for industries ranging from IoT and eCommerce to Ad tech, Finance, BioPharma Research, and Healthcare.
Bruce is well versed in the application of advanced Machine Learning techniques such as Dynamic Hidden Markov Model, MCMC, Vector Autoregression, and Deep Learning models including CNN, LSTM and RBM across multiple domains. His most recent fascinations are with video classification and spoken dialogue system, both of which leverage innovative use of the latest Neural Network techniques.
Bruce holds a BS in Physics from MIT, an MS in Electrical Engineering and PhD in Applied Physics, both from Caltech.