Assistant Professor of Mathematics
Department of Applied Mathematics and Statistics
+971 (0)2 401 8221
Dr. Samuel Feng earned his PhD in Applied and Computational Mathematics from Princeton University (Princeton, USA) in 2012. He received his Bachelor’s degree from Rice University (Houston, USA) in 2007, also in applied mathematics.
After graduation, Dr. Feng received the Ruth L. Kirschstein National Research Service Award Postdoctoral Fellowship, which he served out as a member of the Princeton Neuroscience Institute. During this time, he applied mathematical modeling and applied statistical techniques to complex and large sets of neural data. He was particularly interested in non-Gaussian noise processes in neural decision making.
Dr. Feng joined the Khalifa University of Science, Technology and Research (KUSTAR) faculty in 2014 as an assistant professor of mathematics. Since then, he has grown his collaborations both locally and abroad, working on a wide array of applications involving collaborations with Electrical Engineering, Biomedical Engineering, and even Etihad Airways.
- Multivariate Statistics (Statistical Learning)
- Mathematical and Statistical Software
- Stochastic Differential Equations
Teaching Interests: Applied statistics, stochastic modeling
- Stochastic modeling and its applications
- Applied statistics (“Data Science”)
- Applications in machine learning, neuroscience, psychology, renewable energy resources, genomics
- Srivastava V, Feng S, Cohen JD, Leonard NE, Shenhav A. (2017) A martingale analysis of first passage times of time-dependent Wiener diffusion models. Journal of Mathematical Psychology. doi:10.1016/j.jmp.2016.10.001
- Feng S, Holmes P. (2016) Will big data yield new mathematics? An evolving synergy with neuroscience. IMA Journal of Applied Mathematics. doi:10.1093/imamat/hxw026
- Schwemmer M, Feng S, Holmes P, Cohen J. (2015) A multi-area stochastic accumulator model for a covert visual search task. PLoS One 10(8):e 0136097. doi:10.1371/journal.pone.0136097
- Feng S, Schwemmer M, Gershman S, Cohen J. (2014) Multitasking vs. multiplexing: Toward a normative account of limitations in the simultaneous execution of control-demanding behaviors. Cognitive, Affective, & Behavioral Neuroscience. doi:10.3758/s13415-013-0236-9
- Feng S, Holmes P, Rorie A, Newsome WT. (2009) Can monkeys choose optimally when faced with noisy stimuli and unequal rewards? PLoS Computational Biology 5(2): e1000284. doi:10.1371/journal.pcbi.1000284