Boston University, USA
Electrical and Computer Engineering - Ph.D
2003 - 2009
Alexandria University, Egypt
Electrical Engineering - M.S
2000 - 2003
Alexandria University, Egypt
Electrical Engineering - B.S
1996 - 2000
George Atia
Associate professor
Education
Work Experience
University of Central Florida
Associate Professor at Department of Electrical and Computer Engineering
August 2018 - Now
University of Central Florida
Assistant Professor at Department of Electrical and Computer Engineering
August 2012 - August 2018
University of Illinois at Urbana-Champaign
Postdoctoral Researcher at Coordinated Science Laboratory (CSL)
September 2009 - August 2012
Research interest
Big data analytics and machine learning, statistical learning and signal processing, reinforcement learning, controlled sensing for inference, optical and brain signal processing
Hosted Research Projects
NSF CIF: Medium: Emerging Directions in Robust Learning and Inference (CCF 2106339)
NSF DUE: Florida Information Technology Graduation Attainment Pathways (CCF 2130298)
NSF CAREER: Inference-Driven Data Processing and Acquisition: Scalability, Robustness and Control (CCF 1552497)
NSF CIF: Advanced Ion Channel Models for Neurological Signal Processing -- Theory and Application to Brain-Computer Interfacing (CCF 1525990)
CIF: Small: Collaborative Research: A Unifying Approach for Identification of Sparse Interactions in Large Datasets (CCF 1320547)
Selected publications
Journals
- A. Beckus and G. Atia, "Sketch-based community detection in evolving networks", Accepted to Physical Review E, Sep 2022.
- Y. He and G. Atia, “Coarse to Fine Two-Stage Approach to Robust Tensor Completion of Visual Data”, Accepted to the IEEE Transactions on Cybernetics, Aug 2022.
- Y. He and G. Atia, “Patch Tracking-based Streaming Tensor Ring Completion for Visual Data Recovery”, Accepted to the IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), July 2022.
- M. Sedghi and G. Atia, “Sketches by MoSSaRT: Representative Selection from Manifolds with Gross Sparse Corruptions", Accepted to Pattern Recognition, Nov 2021.
- M. Sedghi, M. Georgiopoulos and G. Atia, “A Multi-Criteria Approach for Fast and Robust Representative Selection from Manifolds”, IEEE Transactions on Knowledge and Data Engineering, Accepted August 2020.
- A. Beckus, M. Rahmani, A. Karimian and G. Atia, “Scalable and Robust Community Detection with Randomized Sketching”, IEEE Transactions on Signal Processing, Vol. 68, No. 1, Jan 2020.
- A. Anwar, G. Atia and M. Guirguis, “A Game-Theoretic Framework for the Virtual Machines Migration Timing Problem", To Appear in the IEEE Transactions on Cloud Computing, 2019.
- A. Beckus, A. Tamasan and G. Atia, “Multi-Modal Non-line-of-sight Passive Imaging", IEEE Transactions on Image Processing, Vol. 28, Iss. 7, pp. 3372-3382, July 2019.
- M. Rahmani and G. Atia, “Low Rank Matrix Recovery with Simultaneous Presence of Outliers and Sparse Corruption", IEEE Journal of Selected Topics in Signal Processing, special issue on Data Science, Vol 12, No. 6, pp. 1-13, Dec 2018.
- M. Rahmani and G. Atia, “Innovation Pursuit: A New Approach to Subspace Clustering”, IEEE Transactions on Signal Processing, Vol. 65, No. 23, pp. 6276-6291, Dec 2017.
Conference Papers
- Y. Wang, A. Velasquez, G. Atia, A. Bennette and S. Zou, “Robust Average-Reward Markov Decision Processes”, 37th Conference on Artificial Intelligence (AAAI), Washington DC, USA, Feb 2023.
- Y. He, G. Atia, “Multi-mode tensor space clustering based on low-tensor-rank representation”, Thirty-Sixth Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2022.
- A. Velasquez, B. Bissey, L. Barak, A. Beckus, I. Alkhouri, D. Melcer, and G. Atia, “Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search”, 35th AAAI Conference on Artificial Intelligence (AAAI), Jan 2021.
- G. Atia, A. Beckus, I. Alkhouri, and A. Velasquez “Steady-State Policy Synthesis in Multichain Markov Decision Processes,” International Joint Conference on Artificial Intelligence (IJCAI), Yokohama Japan (Virtual), Jan 2021.
- M. Rahmani and G. Atia, “Robust and Scalable Column/Row Sampling from Corrupted Big Data", International Conference on Computer Vision Workshops, ICCV, Venice Italy, Oct 2017.
- M. Rahmani and G. Atia, “Innovation Pursuit: A New Approach to the Subspace Clustering Problem," 34th International Conference on Machine Learning (ICML), Sydney, August 2017.
- M. Rahmani and G. Atia, “A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling,” The 33rd International Conference on Machine Learning (ICML), NY, June 2016.