Daniel Trosten is a machine learning researcher with a PhD and eight years of hands-on experience applying deep learning and neural networks to real-world problems. Based in Tromsø and currently a researcher at NORCE, he blends rigorous mathematical curiosity with practical research developed during his PhD and prior industry roles in ML/AI consultancy. His background spans teaching physics and computing, publishing work on deep clustering for variable-length time series, and applied projects in audio and vibration analysis. Known for turning theoretical insight into reproducible research and prototypes, he brings both academic depth and product-minded engineering to interdisciplinary teams.
9 years of coding experience
Master of Science - MS, Anvendt Fysikk og Matematikk - Maskinlæring og Statistikk, Master of Science - MS, Anvendt Fysikk og Matematikk - Maskinlæring og Statistikk at UiT Norges Arktiske Universitet
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at UiT Norges arktiske universitet
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