Jeremiah Johnson is an Assistant Professor of Data Science in the Department of Applied Engineering & Sciences.
Dr. Johnson is a mathematician and machine learning researcher specializing in neural networks and artificial intelligence. Dr. Johnson’s recent research spans a variety of application areas, including Bayesian modeling of water contamination, algorithmic style classification of fine art, automatic nucleus segmentation in microscopy images, and generative modeling techniques for structured prediction in computer vision. Dr. Johnson developed and now co-directs the Bachelor of Science in Analytics & Data Science, an innovative new program that offered on two campuses of the University of New Hampshire.
Dr. Johnson is an alumnus of the University of New Hampshire, earning his Ph.D in mathematics in 2010.
Ph.D., University of New Hampshire
M.S., University of New Hampshire
B.S., University of New Hampshire
Electronic Neural Networks
COMP 750/850: Neural Networks
COMP/DATA 750/850/750: Neural Networks
COMP/GRAD 899/900: Master's Thesis
DATA 557: Introduction to Analytics
DATA 674: Predictive Analytics I
DATA 675: Predictive Analytics II
DATA 750: Neural Networks
DATA 790: Capstone Project
DATA 801: Foundations of Data Analytics
DATA 803: Intro Analytics Applications
GRAD 900: Master's Continuing Research
MATH 420: Finite Mathematics
MATH 425: Calculus I
MATH 426: Calculus II
MATH 527: Diff Equation w/Linear Algebra
MATH 645: Linear Algebra for Application
MATH 696: IS/Linear Alg for Applications
UMIS 599: IndStdy/Capstone Project
Halpin, P. A., Johnson, J., & Badoer, E. (2021). Students from a large Australian university use Twitter to identify difficult course concepts to review during face-to-face lectorial sessions. Advances in Physiology Education, 45(1), 10-17. doi:10.1152/advan.00147.2020
Johnson, J. (n.d.). A Diophantine Equation with an Elementary Solution.
Johnson, J. (n.d.). Teaching Neural Networks in the Deep Learning Era.