Hongwei Wu, Ph.D.

Assistant Professor, Electrical and Computer Engineering
Contact
Office: PARB A220
Phone: (912)965-2386
Email: hongwei.wu@gatech.edu
Research Thrusts
Computational Biology
Bioinformatics
Education
Ph.D. Electrical Engineering, University of Southern California, 2004
M.S. Electrical Engineering, University of Southern California, 2002
M.Eng. Pattern Recognition and Intelligent Systems, Tsinghua University, Beijing, China, 1999
B.Eng. Automatic Control, Tsinghua University, Beijing, China, 1997
Research Interests
  • Computational Biology / Bioinformatics, particularly in comparative genomic analysis and computationally reconstructing
  • Computational Intelligence, particularly in applications to computational biology / bioinformatics, pattern recognition and signal processing

Computational Biology / Bioinformatics, particularly in comparative genomic analysis and computationally reconstructing; Computational Intelligence, particularly in applications to computational biology / bioinformatics, pattern recognition and signal processing. Before joining Gatech, Dr. Wu worked as a post-doctoral research associate in Oak Ridge National Lab and University of Georgia, in the field of Computational Biology/Bioinformatics. Computational biology/bioinformatics is highly inter-disciplinary, ranging from the acquisition and understanding of comprehensive and high-definition data sets, to the construction of quantitative models and computer simulations, and to the systemic analyses of complex biological phenomena. Having been trained in Electrical Engineering, Dr. Wu is well equipped with computational and mathematical skills to tackle some of the most interesting and challenging problems in computational biology/bioinformatics. She has also gained tremendous knowledge in molecular and evolutionary biology, genetics and microbiology through her post-doctoral training. Dr. Wu’s research interests are focused on multi-dimensional genome annotations, from functional genomics (functional annotations of individual genes, cis-regulatory elements, etc) to system biology (quantitative specification of interactions among cellular components), using the mathematical, computational and engineering techniques.