Dr Ben Fulcher completed a B.Sc. (Adv) (Hons) and M.Sc. in physiologically-based sleep modeling in physics, Sydney University (2008), a PhD in machine learning and time-series analysis in physics at Oxford University, UK (2012). He joined BMH in November 2013, and currently works as an NHMRC Early Career Research Fellow.
His research history spans theoretical condensed matter physics, physiologically-based modeling of sleep dynamics, time-series analysis, machine learning, and neuroscience. Ben’s current research sits at the interface of mathematical and statistical modeling and neuroscience and aims to uncover general principles of brain organization using modern data analysis methods combined with mathematical modeling. He will be moving to an independent position at Sydney University Physics in November 2017.
Fulcher, B. D. & Fornito, A. (2016). A transcriptional signature of hub connectivity in the mouse connectome. Proc. Natl. Acad. Sci. USA., 113, 1435–1440.
Fulcher, B. D. & Jones, N. S. (2014). Highly comparative feature-based time-series classification. IEEE Trans. Knowl. Data Eng., 26, 3026–3037.
Fulcher, B. D., Little, M. A. & Jones, N. S. (2013). Highly comparative time-series analysis: the empirical structure of time series and their methods. J. Roy. Soc. Interface, 10, 20130048.
Sethi, S. S., Zerbi, V., Wenderoth, N., Fornito, A. & Fulcher, B. D. (2017). Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain. Chaos, 27, 047405.
Fulcher, B. D., Phillips, A. J. K. & Robinson, P. A. (2008). Modeling the impact of impulsive stimuli on sleep-wake dynamics. Phys. Rev. E., 78, 051920.