Valentino Constantinou
I love the process of building impactful products and services, from zero to one. Currently building at Infactory: https://www.infactory.ai/
At Terran Orbital, I established a strong internal artificial intelligence capability, building and leading a team of data scientists and machine learning engineers, developing cloud-native, event-driven scalable platforms for remote sensing geospatial analytics and supporting cross-functional internal process automation sprints. The team reduced hardware related production-related commissioning times by over 85%, enabling scalable production of that externally sold component.
At the NASA Jet Propulsion Laboratory ("JPL", operated by the California Institute of Technology, "CalTech"), I served as the Principal Investigator to a multi-year alarm analytics effort, co-organized a monthly meetup of the Lab's open source developers (the Open Developer Meetup), and lead innovative applied machine and deep learning research and development efforts. I released the open-source PyNomaly software during my time there and continue to maintain the software - a core library in anomaly detection.
Sessions
PyNomaly's Local Outlier Probability (LoOP) implementation provides interpretable and reliable detection capabilities for classical anomaly types in Python for both static and streaming data.