Jeremy Johnson

Professor

Department of Computer Science
Drexel University
100 University Crossings
3141 Chestnut Street
Philadelphia, PA 19104

Phone: (215) 895-2893
Fax: (215) 895-0545
Email: jjohnson AT cs DOT drexel DOT edu

Links
Research
Schedule
Teaching
Vita
Bobble Head

Jeremy Johnson is a Professor in the Departments of Computer Science and Electrical and Computer Engineering.  He just completed a ten year term as Department Head of the Computer Science Department.  He received a B.A. in Mathematics from the University of Wisconsin-Madison in 1985, a M.S. in Computer Science from the University of Delaware in 1988, and a Ph.D. in Computer Science from The Ohio State University in 1991.

Dr. Johnson's research interests include algebraic algorithms, computer algebra systems, problem solving environments, programming languages and compilers, high performance computing, hardware generation, and automated performance tuning.  He is currently working on SPIRAL, a joint research project with Carnegie Mellon University, University of Illinois at Urbana-Champaign, ETH Zurich, to develop techniques to automatically implement and optimize signal processing algorithms. He Director of the Applied Symbolic Computing Lab (ASYM) with projects in signal processing, communications, scientific computing, computer algebra and power systems funded by DARPA,NSF, DOE, and intel. He currently serves as chair of ACM SIGSAM, the special interest group in symbolic and algebraic manipulation, and the Franklin Institute Computer and Cognitive Science cluster in the Committee on Science and the Arts.


Teaching

  • Spring
  • Fall

    Office Hours

    M (3-4 in UC 139 and online), T (2-3 in UC 139 and online), T (7-8 online), (additional hours, including online, can be arranged by appointment)
    I can be reached via email as well: jjohnson AT cs DOT drexel DOT edu

    Senior Design Projects

    Previous Courses


    Students

  • PhD
    1. Ken Owens, High Assurance SPIRAL.
    2. Mark Boady, Symbolic Tensor Analysis.
    3. Gavin Harrison, High-Performance Exact Linear Algebra.
    4. Lingchuan Meng, High-Performance Integer and Polynomial Arithmetic.
    5. Xu Xu, Symmetric FFT Algorithms
    6. Petya Vachranukunkiet (co-advisor Prawat Nagvajara), Power Flow Computation Using Field Programmable Gate Arrays, 2007.
    7. Anthony Breitzman, Automatic Derivation and Implementation of Fast Convolution Algorithms, 2003.
    8. Anatole Ruslanov (co-advisor Werner Krandick), Architecture Aware Taylor Shift by 1, 2006.
      • Assistant Professor, Department of Computer and Information Sciences, SUNY Fredonia, Fredonia, NY.
    9. Pinit Kumhom (co-advisor Prawat Nagvajara), Design, Optimization, and Implementation of a Universal FFT Processor, 2001.
  • MS
    1. Kevin Cunningham (co-advisor Prawat Nagvajara) - High-Performance Architectures for Accelerating Sparse LU Computation, 2011.
    2. Michael Andrews (MS) - Performance Models
    3. Doug Jones - Data Pump Architecture Simulator and Performance Model, 2010.
    4. Gavin Harrison (co-advisor Prawat Nagvajara) - Hardware for Sparse Matrix-Vector Multiplication, 2010.
    5. Timothy Chagnon - Architectural Support for Direct Sparse LU Algorithms, 2010.
    6. Anupuma Kurpad (co-advisor Prawat Nagvajara) - Comparative Performance Analysis of Phase Recovery Algorithm for Microstructure Reconstruction, 2009.
    7. Pranab Shanoy, Universal FFT Core Generator, 2007.
    8. Mihai Furis, Cache Miss Analysis of Walsh-Hadamard Transform Algorithms, 2003.
    9. Xu Xu, A Recursive Implementation of the Dimesionless FFT, 2003.
    10. Michael Balog (co-advisor Prawat Nagvajara), A Flexible Framework for Implementing FFT Processors, 2002.
    11. Kang Chen, A Prototypical Self-Optimizing Package for Parallel Implementation of Fast Signal Transforms, 2002.
    12. Hung-Jen Huang, Performance Analysis of an Adaptive Algorithm for the Walsh-Hadamard Transform, 2002.
    13. Peter Becker, A High Speed VLSI Architecture for the Discrete Haar Wavelet Transform, 2001.
    14. Rich Pedersen, A Simple Model for the Runtime Performance of Finite Fourier Transform Algorithms, 1995.
  • Undergraduate
    1. Tim Chagnon
    2. Aliaksei Sandryhaila
    3. Yevgen Voronenko

  • Research

    Research interests include algebraic algorithms, computer algebra systems, problem solving environments, programming languages and compilers, high performance computing, hardware generation, and automated performance tuning.

    Research Labs and Projects


    Created: 7/18/96 (last revised 1/2/02) by jjohnson@cs.drexel.edu