Dr. Savakis received the B.S. (Summa Cum Laude) and M.S. degrees in Electrical Engineering from Old Dominion University and the Ph.D. in Electrical Engineering from North Carolina State University. He served as department head from 2000 to 2011. During 2011-12, he was American Council on Education (ACE) Fellow and spent the year at the University of Rochester and UMass Dartmouth. Before joining RIT, he was with the Eastman Kodak Research Labs.
His research focuses on Digital Image Processing and Computer Vision, including object detection and tracking, activity and expression recognition, interactive displays, processing on mobile platforms, and hardware acceleration of imaging algorithms. He has been the primary thesis advisor for more than 30 graduate students in Computer Engineering, Electrical Engineering, Ph.D. in Imaging Science and Ph.D. in Computing and Information Sciences. His research has generated over 100 publications and 11 patents. Dr. Savakis is ABET program evaluator for the accreditation of Computer Engineering and Electrical Engineering programs. He has served as Chair of the IEEE Signal Processing Society, Rochester Chapter, Treasurer of the IEEE Rochester Section and was co-founding member of the IEEE Western New York Image Processing Workshop. Dr. Savakis received the IEEE Third Millennium Medal (2000), the NYSTAR Technology Transfer Award for Economic Impact (2006) and the IEEE Region 1 Outstanding Teaching Award for contributions to education in Computer Engineering and Multimedia (2011). For more about Dr. Savakis, see his website.
· R. Ptucha and A. Savakis, “Joint Optimization of Manifold Learning and Sparse Representations,” IEEE Int. Conf. on Automatic Face and Gesture Recognition (FG2013), Shanghai, China, 2013.
· R. Ptucha and A. Savakis, “Fusion of Static and Temporal Predictors for Unconstrained Facial Expression Recognition,” Int. Conf. on Image Proc. (ICIP 2012), Orlando, FL, 2012.
· S. Azary and A. Savakis, “3D Action Classification Using Sparse Representations on Spatio-Temporal Features,” Int. Symp. Visual Computing (ISVC 2012), Crete, Greece, 2012.
· Savakis, M. Stump, R. Melton, G. Behm and G. Sterns, “Low Vision Assistance Using Face Detection and Tracking on Android Smartphones,” Midwest Symp. Circuits and Systems (MWSCAS 2012), Boise, ID, Aug. 2012.
· G. Tsagkatakis and A. Savakis, “Online Distance Metric Learning for Object Tracking,” IEEE Trans. Circuit and Systems for Video Technology, Nov. 2011.
· R.W. Ptucha, G. Tsagkatakis, A. Savakis, “Manifold Based Sparse Representation for Robust Expression Recognition without Neutral Subtraction,” International Conference on Computer Vision, ICCV BeFIT Workshop, Barcelona, Spain, 2011.
· Bellmore,R.W. Ptucha, A. Savakis, “Interactive Display Using Depth and RGB Sensors for Face and Gesture Control,” Proceedings of IEEE Western NY Image Processing Workshop, Rochester, NY, 2011.
· J. S. Schildkraut, N. Prosser, A. Savakis, J. Gomez, A. Singh, D. Nazareth, H. K. Malhotra, “Level Set Segmentation of Pulmonary Nodules in Megavolt Electronic Portal Images Using a CT Prior,” Medical Physics, Nov. 2010.
· G. Tsagkatakis and A. Savakis, “Face Detection in Resource Constrained Wireless Systems,” in Mobile Multimedia Processing: Fundamentals, Methods and Applications, X. Jiang, M. Ma and C. Chen Eds., Springer Verlag, 2010.
· G. Tsagkatakis and A. Savakis, “A Framework for Object Class Recognition with No Visual Examples,” IEEE Western NY Image Processing Workshop (WNYIP 2010), Rochester, New York, Nov. 2010. (Best Paper Award)
· J. Luo, A. Savakis and A. Singhal, “A Bayesian Networks-based Framework for Semantic Image Understanding,” Pattern Recognition, pp. 919-934, June 2005.
· N. Serrano, A. Savakis and J. Luo, “Improved Scene Classification Using Efficient Low-level Features and Semantic Cues,” Pattern Recognition, vol. 37, pp. 1773-1784, Sep. 2004.
· Loui and A. Savakis, “Automated Event Clustering and Quality Screening of Consumer Pictures for Digital Albuming,” IEEE Trans. Multimedia, pp. 390-402, Sep. 2003.
· Savakis, "Evaluation of Lossless Compression Methods for Continuous Tone Document Images," Journal of Electronic Imaging, pp. 79-86, Jan. 2002.
· J. Luo and A. Savakis, “Self-Supervised Texture Segmentation using Complementary Types of Features, Pattern Recognition, vol. 34, pp. 2071-2082, Nov. 2001.
· U.S. Patent 6,832,006, “System and method for controlling image compression based on image emphasis,” with M. Rabbani, Eastman Kodak Co., issued December 2004.
· U.S. Patent 6671405, “Method for Automatic Assessment of Emphasis and Appeal in Consumer Images,” with S. Etz, Eastman Kodak Co., issued December 2003.
· U.S. Patent Number 6323956, "Adaptive quantization of grayscale images," Eastman Kodak Company, issued November 2001.
· U.S. Patent Number 6044179, "Document Image Thresholding using Foreground and Background Clustering," Eastman Kodak Company, Issued March 2000.
· U.S. Patent Number 6035058, "Automatic Color Form Dropout using Luminance / Chrominance Space Processing," with J. Madigan, Eastman Kodak Company, Issued March 2000.