Heather Lane

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 20••••09 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.

Experience

1. Senior Architect

   athenahealth

   Jan 2017 — Present · Watertown, MA, US

   Technical lead and systems architect for AI-related projects spanning from team- to organizational/strategic-scale at a 7,200+ person,$2.5B/yr, leading healthcare tech firm. Built distributed Data Science team in Boston, MA and Bengaluru, India. Grew team from 15 scientifically literate, but disparate and ML-naive, engineers to team of 40 best-in-class Data Scientists. Developed team ML/AI and software engineering skills and set engineering practice, standards, and expectations, enabling delivery of first 7 years of production AI systems at athenahealth. Led projects developing Machine Learning, Natural Language Processing, Computer Vision and GenAI to healthcare administration and usability challenges. Delivered $25M+/yr savings via AI-driven automated processing of 230M+ documents per year; reduced time-to-delivery of data to customers by 91%; reduced insurance claim rejection rate by over 50%; saved 5k+ hrs/year for clinical office staff. Lead contributor on AI Governance team responding to federal AI healthcare regulations. Lead author of final athenahealth-wide AI Governance Policy that enforceably sets AI behaviors and safety standards across 7,200+ employees and enabled successful company attestation to federal Certified EHR Technology (CEHRT) certification. Process guided 51 distinct AI projects as of 2025 EOY.

Education

• Purdue University

  PhD, Computer Engineering, Computer Science, Machine Learning, Artificial Intelligence

  1990 — 2000

• Purdue University

  Doctor of Philosophy, Electrical and Computer Engineering

• Purdue University

  Bachelor's Degree, Electrical and Computer Engineering

Skills

• Data Mining
• Machine Learning
• Artificial Intelligence
• Bioinformatics
• Matlab
• Research
• Algorithms
• Java
• Linux
• Teaching
• Software Engineering
• Programming
• Pattern Recognition
• Latex
• Computer Science
• Mathematics
• C
• Perl
• Optimization
• Neuroimaging
• Lisp
• Science
• Statistics
• Higher Education
• Unix