- Associate Professor
Main Office3119 Coover
Ames, IA 50011-3060
Ph.D., Electrical Engineering and Computer Science, University of Illinois at Chicago (2001)
M.S., Electrical Engineering and Computer Science, University of Illinois at Chicago (1997)
Dipl Ing, Electrical Engineering, University of Belgrade, Yugoslavia (1995)
Core Research Areas: Communications and signal processing, statistical signal processing
Strategic Area: Data, decisions, networks & autonomy; bioengineering
Brief BiographyAleksandar Dogandzic received the Dipl. Ing. degree (summa cum laude) in electrical engineering from the University of Belgrade, Belgrade, Serbia, in 1995, and the M.S. and Ph.D. degrees in electrical engineering and computer science from the University of Illinois at Chicago, Chicago, IL, USA, in 1997 and 2001, respectively. In August 2001, he joined the Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA, where he is currently an Associate Professor. His research interests include statistical signal processing: theory and applications. Dr. Dogandziˇ c has served on editorial boards of the IEEE T ´ RANSACTIONS ON SIGNAL PROCESSING, THE IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, and the IEEE SIGNAL PROCESSING LETTERS. He has served as a General Co-chair of the Fourth and Fifth International Workshops on Computational Advances in Multi-Sensor Adaptive Processing in 2011 and 2013 and a Technical Co-chair of the 2014 and 2016 IEEE Sensor Array and Multichannel Workshops. He received the 2003 Young Author Best Paper Award and the 2004 Signal Processing Magazine Best Paper Award, both by the IEEE Signal Processing Society. In 2006, he received the CAREER Award by the National Science Foundation.
Selected PublicationsGoogle Scholar Profile: https://scholar.google.com/citations?user=Ej6rYR0AAAAJ
- R. Gu and A. Dogandžić, “Blind X-ray CT image reconstruction from polychromatic Poisson measurements,” IEEE Trans. Comput. Imag., vol. 2, no. 2, pp. 150–165, 2016. A brief video presentation.
- Z. Song and A. Dogandzic, “A max-product EM algorithm for reconstructing Markov-tree sparse signals from compressive samples,” IEEE Trans. Signal Process., vol. 61, no. 23, pp. 5917–5931, 2013.
- K. Qiu and A. Dogandzic, "Sparse signal reconstruction via ECME hard thresholding". IEEE Transactions on Signal Processing, vol. 60, pp. 4551-4569, Sep. 2012.
- Qiu, K. and A. Dogandzic. "Variance-component Based Sparse Signal Reconstruction and Model Selection". IEEE Transactions on Signal Processing 58, (June 2010): 2935-2952.
- R. Gu and A. Dogandžić, “Projected Nesterov’s proximal-gradient algorithm for sparse signal recovery,” IEEE Trans. Signal Process. , vol. 65, no. 13, pp. 3510–3525, 2017.