Machine Learning, Image/Video Processing, Computer Vision, Perception, Scene Understanding, Seismic Interpretation, Learning in the Wild, Learning for Autonomous Vehicles, Medical Image Analysis, Computational Ophthalmology
Developing algorithms that can robustly operate under real-world challenging conditions through weakly supervised learning, backpropogated gradients, hyperpolar classification, and transfer learning.
Working on applications including but not limited to autonomous driving, remote repositioning, smart and connected healthcare, activity recognition, semantic segmentation, object classification and detection, defense models design, and computational seismic interpretation.
Learning with Limited Labels
Learning to characterize data using limited labels using weakly-/semi-supervised learning and sequence modeling for various applications such as subsurface lithology, structure, and stratigraphy characterization, and material characterization, OCT analysis, and medical imaging.
Introduced four datasets for subsurface characterization using weak labels and auxiliary data such as well-logs: LANDMASS-1, LANDMASS-2, Facies classification benchmark, and one large-scale dataset for material characterization of textile fabrics: CoMMonS. Also introduced one interactive tool for salt interpretation benchmarking in large subsurface volumes : Salt Dome Interpretation Tool.
Prof. AlRegib is currently a professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. His group is the Omni Lab for Intelligent Visual Engineering and Science (OLIVES) at Georgia Tech. In 2012, he was named the Director of Georgia Tech’s Center for Energy and Geo Processing (CeGP). He is a faculty member of the Center for Signal and Information Processing (CSIP). He also served as the Director of Georgia Tech’s Initiatives and Programs in MENA between 2015 and 2018. He has authored and co-authored more than 230 articles in international journals and conference proceedings. He has been issued several U.S. patents and invention disclosures. He is a Senior Member of the IEEE.
Prof. AlRegib received the ECE Outstanding Graduate Teaching Award in 2001 and both the CSIP Research and the CSIP Service Awards in 2003. In 2008, he received the ECE Outstanding Junior Faculty Member Award. In 2017, he received the 2017 Denning Faculty Award for Global Engagement.
Prof. AlRegib participated in a number of activities. He is a Technical Program co-Chair for ICIP 2020 in Abu Dhabi. He is a voted member of the IEEE SPS Technical Committees on Multimedia Signal Processing (MMSP) and Image, Video, and Multidimensional Signal Processing (IVMSP), 2015-2017 and 2018-2020. He is a member of the Editorial Boards of both the IEEE Transactions on Image Processing (TIP), 209-present, and the Elsevier Journal Signal Processing: Image Communications, 2014-present. He was a member of the editorial board of the Wireless Networks Journal (WiNET), 2009-2016 and the IEEE Transaction on Circuits and Systems for Video Technology (CSVT), 2014-2016. He was an Area Chair for ICME 2016/17 and the Tutorial Chair for ICIP 2016. He served as the chair of the Special Sessions Program at ICIP’06, the area editor for Columns and Forums in the IEEE Signal Processing Magazine (SPM), 2009–12, the associate editor for IEEE SPM, 2007-09, the Tutorials co-chair in ICIP’09, a guest editor for IEEE J-STSP, 2012, a track chair in ICME’11, the co-chair of the IEEE MMTC Interest Group on 3D Rendering, Processing, and Communications, 2010-12, the chair of the Speech and Video Processing Track at Asilomar 2012, and the Technical Program co-Chair of IEEE GlobalSIP, 2014. He lead a team that is organizing the IEEE VIP Cup, 2017.
His research group is working on projects related to machine learning, image and video processing, image and video understanding, seismic imaging, perception in visual data processing, healthcare intelligence, and video analytics. The primary applications of the research span from Autonomous Vehicles to Portable AI-based Ophthalmology and Eye Exam and from Microscopic Imaging to Seismic Interpretation. The group was the first to introduce modern machine learning to seismic interpretation.
Prof. AlRegib has provided services and consultation to several firms, companies, and international educational and R&D organizations. He has been a witness experts in a number of patents infringement cases.