Robert is responsible for directing software development, enabling research, coordinating company projects, quality control, proposing external collaborations, and securing funding. He believes firmly in open-source, having spent 12 years accruing over 1000 academic citations building open-source software in domains such as machine learning, image analysis, and coupled physical processes. He received his PhD from Université Grenoble Alpes, France, in computational mechanics. Apart from Flowdapt (large-scale model serving) and FreqAI (adaptive modeling), Robert's open-source software portfolio includes Melissa (large-scale deep learning), DataSieve (data pipelining), Yade (discrete element method), SPAM (image analysis), IterativeStatistics (in-situ statistics), and JaiRevAI (machine learning art generation).
Elin ensures top-to-bottom transparency in Emergent Methods' research. She combines her experience designing interdisciplinary research projects with her talents at communciating findings. Some examples of her work include the development of experiments for exploring news narrative clustering and tracking, the enforcement and reporting of source diversity in AskNews journalism, as well as the end-user interpretation of our news reporting. She has performed extensive research for both Flowdapt (large-scale model serving) and FreqAI (adaptive modeling). Elin received her PhD from Lund University, Sweden, and is certified by ECMWF in machine learning methods for meteorology and climate.
Tim is in charge of large-scale systems engineering, which includes leaning on over 10 years of full-stack software development to design and deploy highly-available and performant infrastructure to support the Emergent Methods tech stack. He is also an accomplshed software architect, being one of the primary creators of Flowdapt (large-scale model serving). His experience extends even further with large-scale communications in FreqAI.