2026 Fady Alajaji: Computer Science Researcher – H-Index, Publications & Awards

Overview

Fady Alajaji is affiliated with Queen's University in Canada and has contributed extensively to the field of computer science. Their research output encompasses over 50 publications, with focal interests in areas such as computer networks, artificial intelligence, electrical engineering, and statistical physics.

Their main fields of study include:

Computer Networks and Communications
Artificial Intelligence
Electrical and Electronic Engineering
Statistical and Nonlinear Physics
Computer Vision and Pattern Recognition

Alajaji's work also covers a variety of specialized topics within these fields, including:

Wireless Communication Security Techniques
Adversarial Robustness in Machine Learning
Complex Network Analysis Techniques
Cooperative Communication and Network Coding
Generative Adversarial Networks and Image Synthesis
Error Correcting Code Techniques
Distributed Sensor Networks and Detection Algorithms

The scientist has regularly published in several venues, with a strong presence in:

arXiv (Cornell University)
Entropy
Neural Computation
SIAM Journal on Control and Optimization
IEEE Transactions on Information Theory

Recent papers authored by Alajaji or in collaboration include:

A Unifying Generator Loss Function for Generative Adversarial Networks, 2024, Entropy
Classification Utility, Fairness, and Compactness via Tunable Information Bottleneck and Rényi Measures, 2023, IEEE Transactions on Information Forensics and Security
Rényi Cross-Entropy Measures for Common Distributions and Processes with Memory, 2022, Entropy
Unsupervised Discovery, Control, and Disentanglement of Semantic Attributes With Applications to Anomaly Detection, 2021, Neural Computation
Consensus Using a Network of Finite Memory Pólya Urns, 2022, IEEE Control Systems Letters

Fady Alajaji has collaborated frequently with other researchers including Bahman Gharesifard, Tamás Linder, Philippe Burlina, Somya Singh, and Ling-Hua Chang. The number of collaborations ranges from five to twelve joint publications with these individuals, indicating ongoing research partnerships.

Best Publications

Channel codes that exploit the residual redundancy in CELP-encoded speech

F.I. Alajaji;N.C. Phamdo;T.E. Fuja

204
Citations
The Kullback-Leibler divergence rate between Markov sources

Z. Rached;F. Alajaji;L.L. Campbell

173
Citations
Hybrid Digital–Analog Source–Channel Coding for Bandwidth Compression/Expansion

M. Skoglund;N. Phamdo;F. Alajaji

131
Citations
Rényi divergence measures for commonly used univariate continuous distributions

Manuel Gil;Fady Alajaji;Tamás Linder

126
Citations
A communication channel modeled on contagion

F. Alajaji;T. Fuja

125
Citations
Estimation Efficiency Under Privacy Constraints

Shahab Asoodeh;Mario Diaz;Fady Alajaji;Tamas Linder

112
Citations
On the joint source-channel coding error exponent for discrete memoryless systems

Yangfan Zhong;F. Alajaji;L.L. Campbell

95
Citations
Information Extraction Under Privacy Constraints

Shahab Asoodeh;Mario Diaz;Fady Alajaji;Tamás Linder

88
Citations
A lower bound on the probability of a finite union of events

H. Kuai;F. Alajaji;G. Takahara

87
Citations
Tight error bounds for nonuniform signaling over AWGN channels

H. Kuai;F. Alajaji;G. Takahara

83
Citations
Turbo codes for nonuniform memoryless sources over noisy channels

Guang-Chong Zhu;F. Alajaji

82
Citations
Design and performance of VQ-based hybrid digital-analog joint source-channel codes

M. Skoglund;N. Phamdo;F. Alajaji

81
Citations
Detection of binary Markov sources over channels with additive Markov noise

F. Alajaji;N. Phamdo;N. Farvardin;T.E. Fuja

75
Citations
Quantization of memoryless and Gauss-Markov sources over binary Markov channels

Nam Phamdo;F. Alajaji;N. Farvardin

74
Citations
Joint source-channel turbo coding for binary Markov sources

Guang-Chong Zhu;F. Alajaji

69
Citations
Transmission of nonuniform memoryless sources via nonsystematic turbo codes

Guang-Chong Zhu;F. Alajaji;J. Bajcsy;P. Mitran

68
Citations
Renyi's divergence and entropy rates for finite alphabet Markov sources

Z. Rached;F. Alajaji;L. Lorne Campbell

67
Citations
Image segmentation and labeling using the Polya urn model

A. Banerjee;P. Burlina;F. Alajaji

66
Citations
Feedback does not increase the capacity of discrete channels with additive noise

F. Alajaji

66
Citations
Pairwise optimization of modulation constellations for non-uniform sources

B Moore;G Takahara;F Alajaji

58
Citations

Frequent Co-Authors

Tamas Linder Queen's University

Philippe Burlina Johns Hopkins University

Yunghsiang S. Han University of Electronic Science and Technology of China

Mikael Skoglund Royal Institute of Technology

Nariman Farvardin Stevens Institute of Technology

Norman C. Beaulieu Beijing University of Posts and Telecommunications

Rama Chellappa Johns Hopkins University

External Links

Personal website of Fady Alajaji

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

As technology and science continue to shape the job market, there’s growing demand for flexible and specialized education options. For those looking to advance quickly, a 1 year computer science degree online can provide accelerated learning and entry into high-demand tech roles. These programs are ideal for motivated individuals seeking fast-tracked career opportunities in software development, data science, and more.

Related fields such as online environmental engineering degree science and engineering offer specialized training for those interested in sustainable technologies and environmental solutions. Mechanical engineering is another strong pathway, with an online mechanical engineering degree providing the skills needed for careers in robotics, manufacturing, and design.

For students more focused on fundamental sciences, pursuing an online physics degree can open doors to research, teaching, and high-tech industries. Each of these online degrees is designed to be accessible, affordable, and adaptable for working professionals or those seeking career changes within the STEM sector.