Wyman S441
Research Areas Discrete mathematics Graph theory Multilinear algebra Image analysis Experimental math

Edinah Gnang is an assistant professor of applied mathematics and statistics. His research interests include discrete mathematics, graph theory, multilinear algebra, image analysis, and experimental math.

Gnang is best known for his work on numerical/symbolic multilinear algebra and enumerative combinatorics. He successfully developed the first formulation and constructive proof of existence of a hypermatrix spectral decomposition theorem, first conjectured in the 90s by Prabir Bhattacharya. He is currently working to highlight combinatorial, numerical, and various other algorithmic applications of the algebra of hypermatrices. This area of study has applications in signal analysis, medical imaging, and machine learning.

His research in the field of enumerative combinatorics centers on the complexity of expressing solutions to systems of algebraic equations. Gnang and his colleagues have initiated a systematic study of enumerative and algorithmic aspects of arithmetic formulas. These works have led to the development of optimal algorithms for recursively constructing canonical arithmetic formula encodings, as well as a procedure for efficiently sampling and determining minimal size arithmetic formulas.

Gnang’s most recent work aims to bridge the gap between extending classical linear algebra numerical algorithms to hypermatrices and determining the complexity of expressing solutions to non-linear systems of equations. His research has been funded by Applied Physics Laboratory (APL) and the National Science Foundation. He is the recipient of a Spira Teaching Award for excellence in undergraduate teaching from Purdue University and a Professor Joel Dean Award for excellence in teaching from JHU. He was also awarded a Rutgers University Integrated Graduate Traineeships in Perceptual Science.

Gnang earned his B.S. degree in mathematics and physics from the University of Montreal in 2005 and his Ph.D. in computer science from Rutgers University in 2013. From 2013 to 2014, he held a joint postdoctorate position at the Institute for Advanced Study and the Princeton University Center for Computational Intractability. He joined Johns Hopkins in 2017 after spending three years at Purdue University as a Golomb Visiting Assistant Professor of Mathematics.