Prof. Alfred O. Hero received the 2013 IEEE Signal Processing Society (SPS) Technical Achievement Award, “for information-theoretic advances in statistical signal processing and machine learning.” This award honors a person who, over a period of years, has made outstanding technical contributions to theory and/or practice in technical areas within the scope of the SPS, as demonstrated by publications, patents, or recognized impact on the field.
Prof. Hero is the R. Jamison and Betty Williams Professor of Engineering. He holds courtesy appointments in the departments of Biomedical Engineering and Statistics, and is affiliated with the Medical School’s Program in Biomedical Science (PIBS) and the Graduate Program in Applied and Interdisciplinary Mathematics (AIM).
Prof. Hero is an internationally recognized expert in the field of signal and image processing. His research is focused on statistical signal processing, bioinformatics and imaging. Based on a strong theoretical foundation, his research is being applied to a broad array of topics, including predictive health, biomedical diagnostics, network data, and astronomical data. Much of his research falls under the umbrella of big data, from the perspective of using signal processing approaches to finding the important “signals,” or pieces of data, in massive data sets that include a preponderance of “noise,” or data that is irrelevant to what is being investigated.
For example, one project aims to predict health and disease propagation (epidemics) over a close knit human population based on a combination of genetic, metabolic, and social network data. A second project focuses on social networks and developing methods to aggregate different layers of social network information. A third project aims to make it possible to search large multimedia databases of images and videos and find results based on what’s happening in the scenes, as well as people and object recognition.
Prof. Hero is also director of an ARO-MURI that is investigating value-centered information-driven sensing. This program is investigating ways to improve the value of information delivered to the end-user in sensor networks that are limited by finite bandwidth, temporal dynamics, latency, and other factors. The sensing methods include radar, sonar, video, LIDAR, and atmospheric sensors.
Several of Prof. Hero’s papers have earned best paper awards, including the following from recent years:
- Marginal Likelihoods for Distributed Estimation of Graphical Model Parameters, Best Paper Award at the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2013);
- Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods, Notable Paper Award at the Sixteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2013) [more info];
- Correcting camera shake by incremental sparse approximation, Best Paper Award at the 2013 IEEE International Conference on Image Processing (ICIP) [more info];
- Locating the nodes: cooperative localization in wireless sensor networks, 2009 IEEE Signal Processing Magazine Best Paper Award, in recognition of the importance of this 2005 paper [more info]; and
- Analysis of clinical flow cytometric immunophenotyping data by clustering on statistical manifolds: Treating flow cytometry data as high-dimensional objects, Best Original Paper published in Clinical Cytometry between 2008-2009 [more info].
Prof. Hero served on the Board of Directors of IEEE (2009-2011) where he served as Director of Division IX (Signals and Applications), and he served as President of the IEEE Signal Processing Society (2006-07). He has received an IEEE Signal Processing Society Meritorious Service Award and the IEEE Third Millenium Medal, and he received a U-M Distinguished Faculty Achievement Award. He co-authored the textbook, Foundations and Applications of Sensor Management in 2008. Prof. Hero has published more than 450 journal and conference papers, has 3 patents, and is a Fellow of IEEE.
The award will be presented to Prof. Hero at the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) in Florence, Italy.