Jeremy Johnson serves as professor of computer science and electrical and computer engineering and as department head of the Department of Computer Science at the College of Computing & Informatics (CCI) at Drexel University. His research interests include algebraic algorithms, computer algebra systems, problem solving environments, programming languages and compilers, high performance computing, and automated performance tuning. He directs Drexel's Applied Symbolic Computation lab which focuses on the use of symbolic computation to derive and optimize the implementation of algorithms with mathematical structure. He currently serves as chair of the ACM special interest group on symbolic and algebraic manipulation (SIGSAM) and serves on the editorial board of the journal of Applicable Algebra in Engineering, Communication and Computing. He previously served on the steering committee of the International Symposium on Symbolic and Algebraic Computation (ISSAC). He was guest editor of two issues of the Journal of Symbolic Computation devoted to Computer Algebra and Signal Processing and a collection of papers related to ISSAC 2009 for which he was general chair. He also co-edited the book Quantifier Elimination and Cylindrical Algebraic Decomposition. He was a founding member of the SPIRAL project on the automatic generation and optimization of digital signal processing algorithms and was a key part of the DARPA-funded "Very High Dimensionality Study," which developed the mathematical framework and a prototype domain specific language (Tensor Product Language) and special purpose compiler that led to the SPL language. He was also a member of the Department of Energy-funded Power Grid Project which developed hardware to accelerate load flow computation and various sparse linear algebra kernels.
- Computer Security and Privacy
- Programming Systems & Software Engineering
- Theoretical Foundations
Computer algebra, design and analysis of algorithms, programming languages and compilers, automated performance tuning, algorithms for DSP, parallel processing, and high-performance computing
- PhD, Computer and Information Science, The Ohio State University
- MS, Computer Science, University of Delaware
- BA, Mathematics, University of Wisconsin-Madison