Gonzalo R. Arce

Biography

Dr. Gonzalo R. Arce is the Charles Black Evans Professor in the Electrical and Computer Engineering Department and a JPMorgan-Chase Faculty Fellow at the University of Delaware. His research interests lie in statistical learning in data science, computational imaging, and signal/data processing. He received the 2010-2011 and 2017-2018 Nokia-Fulbright Distinguished Chairs in Information and Communications Technologies. He is a Fellow of the IEEE and the Center for Advanced Studies.

Education

• Ph.D. in electrical engineering, Purdue University, West Lafayette, IN, 1982
• Master of science in electrical engineering, Purdue University, West Lafayette, IN, 1980
• Bachelor of science in electrical engineering, Summa Cum Laude, University of Arkansas, Fayetteville, AR, 1979

Select Publications

• A. Rauh and G. R. Arce, “Optimized Spectrum Permutation for the Multidimensional Sparse FFT,” in IEEE Transactions on Signal Processing, vol. 65, no. 1, pp. 162-172, Jan.1, 1 2017.
• C. V. Correa, C. A. Hinojosa, G. R. Arce, H. Arguello, “Multiple snapshot colored compressive spectral imager” in Special Section On Optical Computational Imaging, Optical Engineering SPIE. Dec. 2016.
• A. Parada-Mayorga and G. R. Arce, “Spectral Super-Resolution in Colored Coded Aperture Spectral Imaging,” in IEEE Transactions on Computational Imaging, vol. 2, no. 4, pp. 440-455, Dec. 2016.
• C. V. Correa, H. Arguello, and G. R. Arce, “Spatiotemporal blue noise coded aperture design for multi-shot compressive spectral imaging,” J. Opt. Soc. Am. A 33, 2312-2322 (2016)
• H. Rueda, H. Arguello, and G. R. Arce, “Compressive spectral testbed imaging system based on thin-lm color-patterned lter arrays,” Appl. Opt. 55, 9584-9593 (2016)
• W. Feng, H. Rueda, C. Fu, G. R. Arce, W. He, and Q. Chen, “3D compressive spectral integral imaging,” Opt. Express 24, 24859-24871 (2016)
• R. E. Carrillo, A. B. Ramirez, G. R. Arce, K. E. Barner, B. M. Sadler, “Robust compressive sensing of sparse signals: a review,” EURASIP Journal on Advances in Signal Processing, 2016.
• C. Fu; M. Don; G. R. Arce, “Compressive Spectral Imaging via Polar Coded Aperture,” in IEEE Transactions on Computational Imaging, October 2016.
• J. Tan, Y. Ma, H. Rueda, D. Baron and G. R. Arce, “Compressive Hyperspectral Imaging via Approximate Message Passing,” in IEEE Journal  Journal of Selected Topics in Signal Processing, vol. 10, no. 2, pp. 389-401, March 2016.
• A.P. Cuadros, C. Peitsch, H. Arguello, G. R. Arce, “Coded aperture optimization for compressive X-ray tomosynthesis”. Optics Express, Vol. 23, No. 25, pp. 32788-32802, 2015.

Awards & Honors

• JPMorgan Chase Faculty Fellow at the Institute of Financial Services Analytics
• Fulbright-Nokia Distinguished Chair in Information Technologies and Communications 2010-2011, 2017
• Elected member, Arkansas Academy of Engineering, University of Arkansas, 2008
• Fellow of the IEEE for contributions on the theory and applications of nonlinear signal processing
• Fellow, Center for Advanced Studies, University of Delaware
• Sperry Corporation Research Award, 1985
• National Science Foundation Research Initiation Award, 1983

Website

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