Keigo Hirakawa joined University of Dayton as Assistant Professor of Electrical and Computer Engineering in 2010. Prior to UD, he was with Harvard University as a Research Associate of Department of Statistics and School of Engineering and Applied Sciences. He simultaneously earned Ph.D in Electrical and Computer Engineering from Cornell University and M.M. in Jazz Performance from New England Conservatory of Music. He received his B.S. in Electrical Engineering from Princeton University. Previously, he was with HP/Agilent Technologies’ camera division as an ASIC engineer.

Prof. Hirakawa has published in the literature of engineering, computer science, and statistics. His research focuses on algorithmic development of image processing, computer vision, biomedical imaging, and sensor designs. He is best known for his expertise in digital camera designs, and his contributions span color science, estimation theory, statistical modeling, and wavelet theory.

He has received a number of recognitions, including a paper award from IEEE and keynote speeches at IS&T CGIV, PCSJ-IMPS, and CSAJ, and IAPR CCIW. He has strong track record of collaborating with industry partners. He is an associate editor for SPIE/IS&T Journal of Electronic Imaging, and serves on the organization committees of IEEE ICIP 2012, SPIE EI/VIPC 2010-11, and OSA DIPA 2010.

PROFESSIONAL ACTIVITIES:

Organizing Committee, IEEE ICIP 2012, OSA DIPA 2010

Senior Member, IEEE

Associate Editor, SPIE Journal of Electronic Imaging

SELECTED RESEARCH AREAS:

• Image Processing

Our work concentrates on development of robust algorithms for contemporary digital cameras, 3D displays, video processing, and SAR imagery. We are primarily concerned with recovering a signal from (noise) corrupted undersampled data while relying heavily on statistical models.

• Computer Vision

We develop new techniques to recover color and geometry of the scene from a given image. We exploit spatial, spectral, and BRDF models to reduce the dimensionality of image signals and to extract meaningful information.

• Biomedical Imaging

Computed tomography scans and flourescence microscopy are examples of noninvasive medical procedures whose performance is severely limited by the availability of photons. We provide novel techniques for estimating Poisson intensity, the underlying data that we are after.

• Sensors

Color, multispectral, and infrared image sensors are subject to spatial, temporal, and dynamic range resolution trade-offs due to hardware limitations. We invented a breakthrough technology to significantly boost the resolution and throughput using existing sensor hardware.