Heather Lane

Background

About Heather Lane

I received my PhD in from Purdue, where I studied machine learning with Carla Brodley. My PhD work focused on developing machine learning methods for the computer security problem of anomaly detection. Most of that work was based on various forms of time series analysis.After graduating, I spent two years at the MIT AI Lab (now CSAIL) working with Leslie Kaelbling on reinforcement learning and decision-theoretic planning, Markov decision processes, and the tradeoff between stochastic and deterministic planning.In 2002, I moved to the University of New Mexico as an assistant professor in the Department of Computer Science. There I worked on a number of application areas of ML, including the bioinformatics of RNA interference, genomics, and computational neuroscience (inference of brain activity networks from neuroimaging data). Much of that work involved Bayesian networks and dynamic belief networks.In 2008, I was promoted to associate professor at UNM and was granted tenure. During the 2008-2009 year, I spent some time on sabbatical with colleagues at the Universidad Polytecnica de Madrid (UPM), Universidad Complutense de Madrid (UCM), and the University College London (UCL). I returned to UNM in F'2009, and continued research on scientific data mining and teaching machine learning and software engineering.In 2012, I moved from academia to industry, joining Google in Cambridge, MA. In the five years I spent at Google, I worked on Knowledge Graph, Google Books, Project Sunroof, and Ads Latency.In 2017, I joined athenahealth, leading a Data Science team working to use athena's immense store of healthcare data to improve healthcare experiences for clinicians and patients.Specialties: Machine learning; deep neural networks/deep learning; data analysis; bioinformatics; computational neuroscience; information security; time series analysis; reinforcement learning; stochastic/decision-theoretic planning; Bayesian networks; anomaly detection.