Andrew Slavin Ross (he/him)

• Staff Data Scientist
• Led development of the mixed-integer optimization and stochastic timeseries forecasting frameworks controlling dispatch at our 5 GWh thermal energy storage facility.
• Led development of our state of charge inference pipeline.
• Built the core of our primary optimization model for project evaluation, system sizing, and technoeconomic analysis.

• Senior Applied Scientist
• Led technical design and development of a linear programming-based API product to optimize battery dispatch and sizing for a given utility tariff, solar installation, and consumption profile.
• Led research and engineering for services predicting monthly consumption and high-resolution interval data for given utility meters.

• Postdoctoral Fellow
• Researched ML approaches to parameterize subgrid-scale processes in ocean models with M²LInES.
• Published a first-author paper on symbolic regression and an evaluation framework now actively used by others at M²LInES.

• Core Team Member
• Served as a volunteer on the core team of Climate Change AI, an organization dedicated to catalyzing impactful work at the intersection of climate change and machine learning.
• (Meta-)reviewed numerous grant applications and papers and contributed to strategic decisions.
• Built most of the CCAI website, including a web framework for hybrid digital/in-person workshops.

• Software Engineering Intern
• Developed Bayesian predictive caching techniques in an OLAP database powering ads reports.
• Worked on federated learning and contributed to Tensorflow.js with PAIR at Google Brain.

• Software Engineer
• Designed and built full stack web applications for clients in industry, academia, and local government.
• Architected significant parts of a widely-used oncology clinical decision support app for McKesson, a digital humanities project for Harvard, and a building management app for Autodesk.