Best-in-Class Data Science Solutions for Aerospace, Energy, and Health Systems
ATS is an engineering and risk management consulting practice delivering data science, machine learning, and probabilistic risk analysis to aerospace, energy, and healthcare clients. With more than a decade of experience supporting the Air Force, Navy, Intelligence Community, and private sector, it helps organizations make high-quality decisions through quantitative analysis, asset management, and AI-driven risk platforms.
Richard KimPresident and Chief Engineer
Giovanni MalloyChief Data Scientist
Travis TrammellSenior Engineer
Ray TaylorSenior Engineer
Madison CootsSenior Data Scientist
Advanced data science and machine learning capabilities that have reduced clients' operational and capital expenditures while lowering risk costs from operations.
Probabilistic and AI-based risk analysis for complex engineered systems, from substation asset risk to wildfire spread modeling and space system threat assessment.
Decision theory and economic analysis that guides organizations through large volumes of data to determine optimal courses of action within resource constraints.
Aerospace · Space · Defense · Intelligence & National Security · Electric Utilities · Healthcare · Pharmaceutical
Aerospace
Application of ATS's Markov Decision Process model to optimize satellite constellation management as commercial and educational entities expand their orbital presence, addressing complex challenges in multi-asset system coordination.
Defense
Development of advanced threat detection capabilities for space-based systems.
Electric Utilities
Probabilistic risk analysis of electric utility substations encompassing circuit breakers, relays, switches, buswork, towers, poles, and conductors, enabling utilities to shift from reactive maintenance to predictive asset management.
Electric Utilities
AI-driven asset management for complex engineered systems, replacing reactive or schedule-based maintenance with predictive models that reduce failure risks before they occur.