Muhammad Amir Shafiq, a recent Ph.D. graduate of the Georgia Tech School of Electrical and Computer Engineering (ECE), was chosen for the Center for Signal and Information Processing (CSIP) Outstanding Research Award for spring semester 2018. All CSIP students are eligible for this award, and after all nominations are considered, the recipient is determined by a vote of the CSIP faculty.
A Fulbright Ph.D. scholar from Pakistan, Shafiq was a member of the Omni Lab for Intelligent Visual Engineering and Science and theGeorgia Tech Center for Energy and Geo Processing (CeGP), a research center at Georgia Tech and King Fahd University of Petroleum and Minerals (KFUPM). Both the lab and the center are led by ECE Professor Ghassan AlRegib.
Shafiq's Ph.D. dissertation, “Computational Seismic Interpretation using Attention Models, Texture Dissimilarity, and Machine Learning,” introduced novel seismic attributes and automated, interactive, and interpreter-assisted workflows, which not only reduced the time for seismic interpretation, but also outperformed state-of-the-arts methods.
During his stay at Georgia Tech, Shafiq filed two invention disclosures, authored/co-authored more than 30 articles in international journals and conference proceedings, and developed three tools for computational seismic interpretation. He also received the Best Poster Award at KFUPM in Dhahran, Saudi Arabia in March 2016.
Parts of Shafiq’s research have been published in journals and conferences, including IEEE Signal Processing Magazine; Journal of Applied Geophysics; Interpretation; Geophysical Prospecting; Geophysics; The Leading Edge(TLE); Geophysical Journal International; SIAM Conference on Imaging Science; SBGf/SEG Workshop on Machine Learning; Society of Exploration Geophysicists; European Association of Geoscientists and Engineers; American Association of Petroleum Geologists; International Conference on Image Processing; International Conference on Acoustics, Speech, and Signal Processing; and Global Conference on Signal and Information Processing.
School of Electrical and Computer Engineering
Last revised May 22, 2018