Muhammad Bilal | Computer Vision for Robotics and Autonomous Systems | Editorial Board Member

Assoc. Prof. Dr. Muhammad Bilal | Computer Vision for Robotics and Autonomous Systems | Editorial Board Member

Gunagzhou Nanfang College | China

Dr. Muhammad Bilal is an Associate Professor at Nanfang College, China, specializing in artificial intelligence, machine learning, and underwater acoustic communication. His research focuses on bio-inspired covert communication, low probability detection systems, and AI-driven signal processing, with applications in marine technology, cybersecurity, and healthcare. He has authored numerous peer-reviewed publications in leading international journals and conferences. Dr. Bilal actively collaborates with global research communities and serves as a reviewer for reputed journals. His work advances secure communication systems and contributes to the development of sustainable and intelligent ocean technologies with broad societal impact.

Citation Metrics (Scopus)

600

400

200

0

Citations
381

Documents
41

h-index
11

🟦 Citations 🟥 Documents 🟩 h-index

View Scopus Profile    View ORCID Profile
     View Google Scholar  Profile
     View ResearchGate Profile

Featured Publications


Biologically inspired covert underwater acoustic communication—A review.

–Physical Communication, 30, 107–114. (2018). Cited By: 55

A frequency hopping pattern inspired bionic underwater acoustic communication.

– Physical Communication, 46, 101288. (2021). Cited By: 43

Bionic Morse coding mimicking humpback whale song for covert underwater communication.

– Applied Sciences, 10(1), 186.. (2020). Cited By: 35

Deep-neural-network-based receiver design for downlink non-orthogonal multiple-access underwater acoustic communication.

– Journal of Marine Science and Engineering, 11(11), 2184. (2023). Cited By: 25

Riadh Harizi | Deep Learning For Computer Vision | Research Excellence Award

Dr. Riadh Harizi | Deep Learning For Computer Vision | Research Excellence Award

Teacher | Ecole Nationale d’IngĂ©nieurs de Sfax | Tunisia

Dr. Riadh Harizi is a researcher at the École Nationale d’Ingénieurs de Sfax, Tunisia, with expertise in Machine Learning, Artificial Intelligence, Computer Vision, Deep Learning, and Data Science. He has authored 5 research outputs, receiving 33 citations across 25 citing documents and achieving an h-index of 3. His work spans scene text understanding, reinforcement learning, and AI-driven educational analytics, with publications in Applied Soft Computing, Multimedia Tools and Applications, and leading international conferences. He has collaborated with interdisciplinary teams and contributed an open Latin and Arabic scene character dataset to IEEE Dataport, supporting reproducible research and societal impact in education and intelligent visual systems.

 

Citation Metrics (Scopus)

80

60

40

20

0

Citations
33

Documents
5

h-index
3

🟦 Citations 🟥 Documents 🟩 h-index

View Scopus Profile
           View ORCID Profile
     View Google Scholar Profile

Featured Publications


Deep-learning based end-to-end system for text reading in the wild.

-Multimedia Tools and Applications. (2022) Cited By: 10

SIFT-ResNet synergy for accurate scene word detection in complex scenarios.

– In Proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART) . (2024). Cited By: 3

Simy Baby | Applications of Computer Vision | Best Researcher Award

Mrs. Simy Baby | Applications of Computer Vision | Best Researcher Award

Researcher | National Institute of Technology | India

Mrs. Simy Baby is a pioneering researcher at the National Institute of Technology, Tiruchirappalli, with extensive expertise in machine learning, semantic communication, computer vision, and mmWave radar signal processing. Her research bridges the gap between radar sensing and intelligent communication frameworks, focusing on efficient feature extraction, complex-valued encoding, and task-oriented inference.Her seminal work, “Complex Chromatic Imaging for Enhanced Radar Face Recognition” (Computers and Electrical Engineering,  introduced a novel representation that preserves amplitude and phase information of mmWave radar signals, achieving an exceptional recognition accuracy. Another significant contribution, “Complex-Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication” (IEEE Transactions on Cognitive Communications and Networking ), proposed a CLDA-based encoding framework enhancing feature interpretability and robustness under channel variations. Current investigations include Data Fusion Discriminant Analysis (DFDA) for multi-view activity recognition and Semantic Gaussian Process Regression (GPR) for vehicular pose estimation, highlighting her commitment to multitask semantic communication systems.Dr. Baby has 21 publications with 20 citations and an h-index of 3.  demonstrating a rapidly growing impact in her field. She is an active member of the Indian Society for Technical Education (ISTE) and contributes to the scientific community through innovative research that combines theory and practical applications. Her work on radar-based recognition, semantic feature transmission, and multi-task inference frameworks holds significant potential for intelligent transportation systems, human activity recognition, and bandwidth-efficient communication technologies.Through her research, Dr. Baby has established herself as a leading figure in advancing radar imaging and semantic communication, providing scalable solutions that merge high-performance computing with real-world societal applications. Her vision continues to shape the future of intelligent sensing and communication systems globally.

Profiles: Google Scholar | ORCID | Scopus 

Featured Publications

1. Ansal, K. A., Rajan, C. S., Ragamalika, C. S., & Baby, S. M. (2022). A CPW fed monopole antenna for UWB/Ku band applications. Materials Today: Proceedings, 51, 585–590. Cited By : 5

2. Ansal, K. A., Ragamalika, C. S., Rajan, C. S., & Baby, S. M. (2022). A novel ACS fed antenna with comb shaped radiating strip for triple band applications. Materials Today: Proceedings, 51, 332–338. Cited By : 4

3. Ansal, K. A., Kumar, A. S., & Baby, S. M. (2021). Comparative analysis of CPW fed antenna with different substrate material with varying thickness. Materials Today: Proceedings, 37, 257–264. Cited By : 4

4. Baby, S. M., & Gopi, E. S. (2025). Complex chromatic imaging for enhanced radar face recognition. Computers and Electrical Engineering, 123, 110198. Cited By : 3

5.Ansal, K. A., Shanmuganatham, T., Baby, S. M., & Joy, A. (2015). Slot coupled microstrip antenna for C and X band application. International Journal of Advanced Research Trends in Engineering and Technology.Cited By : 3

Dr. Simy M. Baby’s research advances the integration of semantic communication and computer vision, enabling high-accuracy radar-based recognition and task-oriented inference. Her work has significant implications for intelligent transportation, human activity monitoring, and bandwidth-efficient communication, driving innovation in both science and industry globally.

Mohamed Hebaishy | Computer Vision | Excellence in Computer Vision Award

Assoc. Prof. Dr. Mohamed Hebaishy | Computer Vision | Excellence in Computer Vision Award

Associate Prof. in ERI at Electronics Research Institute, Egypt

Dr. Mohamed Ahmed Hebaishy is a distinguished researcher with extensive expertise in biometrics, iris recognition, image processing, computer vision, and satellite imaging. He has made remarkable contributions through his work in human identification systems, advanced image representation, and security technologies. His career spans academia, research institutions, and international collaborations, combining theoretical innovation with real-world applications in areas such as space research and remote sensing. He has published in reputed journals and conferences, including IEEE and Springer platforms, and actively engages in research that bridges science and technology. Beyond his research output, he has held significant leadership roles, mentored graduate students, and reviewed research projects for universities and conferences. His diverse professional experiences, strong academic foundation, and continuous pursuit of impactful research highlight his commitment to advancing scientific knowledge and addressing global challenges, making him a valuable contributor to the academic and research community.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Mohamed Ahmed Hebaishy completed his Bachelor of Science in Electronic Engineering with a focus on automatic control and measurements at Menoufia University, where he built a strong foundation in control systems and electronics. He later pursued a Master of Science degree in Electronics and Communication at Cairo University, with his thesis centered on developing a fuzzy controller for flexible joint manipulators, reflecting his early focus on control and automation. His academic journey culminated in earning a Doctor of Philosophy in Information Technology from Vladimir State University in the Russian Federation, specializing in control system analysis and data processing. His doctoral thesis focused on using iris image processing in human identification systems, marking the beginning of his long-term contributions to the field of biometrics. Through these academic achievements, he has combined expertise in engineering, computing, and data-driven technologies, equipping him with the knowledge and skills to contribute meaningfully to interdisciplinary research.

Professional Experience

Dr. Mohamed Ahmed Hebaishy has built a rich professional career across academia and research institutions, holding positions that span lecturer, assistant professor, and department head roles. He has served as a researcher at the Electronics Research Institute, contributing to significant projects in informatics and computer science. His work extended to leadership in national space programs, where he played a key role in satellite image processing and payload command systems for EgyptSat missions. He also gained international academic experience as an assistant professor at Shaqra University in Saudi Arabia, where he later became head of the computer science department. His contributions include guiding research projects, supervising theses, and leading academic initiatives. Additionally, he has been a reviewer for major universities and scientific conferences, reflecting his involvement in shaping the academic community. His experience demonstrates a balance of teaching, research, and leadership, making him a well-rounded academic and professional.

Research Interest

Dr. Mohamed Ahmed Hebaishy’s research interests lie at the intersection of biometrics, image processing, computer vision, and artificial intelligence, with a strong emphasis on human identification systems and security technologies. He has worked extensively on iris recognition, exploring innovative approaches to enhance accuracy and efficiency in biometric applications. His interests also extend to satellite imaging and remote sensing, where he has contributed to projects in national space programs, including the development of image processing systems for EgyptSat satellites. In recent years, his focus has broadened to include advanced methods in pattern recognition, machine learning, and computer-aided automation systems. He is also engaged in applied research addressing real-world challenges such as waste sorting, wireless communication, and medical applications of imaging. His diverse interests reflect a commitment to advancing cutting-edge technologies that improve security, automation, and sustainability, while also fostering new interdisciplinary pathways in computer science and engineering.

Award and Honor

Throughout his career, Dr. Mohamed Ahmed Hebaishy has received recognition for his contributions to research, teaching, and leadership within the fields of biometrics, image processing, and space technology. His involvement in the EgyptSat satellite programs and ITIDA-funded security projects demonstrated his ability to translate research into impactful applications, earning him acknowledgment within the scientific community. He has also been invited as a reviewer for universities, research conferences, and scientific committees, reflecting trust in his expertise and judgment. His leadership as head of the computer science department at Shaqra University further highlights his role in shaping academic excellence and guiding student development. While his curriculum vitae does not list specific awards, his record of sustained contributions, successful project leadership, and active engagement in international research platforms stands as a form of recognition in itself. His ongoing publications in reputed journals further strengthen his professional standing as a dedicated and accomplished researcher.

Research Skill

Dr. Mohamed Ahmed Hebaishy possesses a broad set of research skills that reflect his deep expertise in both theoretical and applied aspects of computer science and engineering. He is skilled in biometric system design, with specialization in iris recognition, image processing algorithms, and human identification technologies. His technical capabilities extend to satellite image analysis, data processing, and control systems, where he has led projects involving payload command systems for national space programs. He is proficient in developing and applying advanced algorithms, including fuzzy logic, wavelet transforms, and optimization techniques, to solve complex research problems. His experience also covers interdisciplinary areas such as wireless communication systems, security applications, and automated testing tools. Beyond technical expertise, he has strong skills in project leadership, academic supervision, and research collaboration, enabling him to contribute effectively to both academic and applied research communities. His skill set demonstrates adaptability, innovation, and problem-solving ability.

Publications Top Notes

Title: A comparative study of QTP and load runner automated testing tools and their contributions to software project scenario
Authors: M Imran, M Hebaishy, AS Alotaibi
Year: 2016
Citation: 12

Title: Road extraction from high resolution satellite images by morphological direction filtering and length filtering
Authors: TM Talal, MI Dessouky, A El-Sayed, M Hebaishy, FA El-Samie
Year: 2008
Citation: 12

Title: Increasing the Efficiency of Iris Recognition Systems by Using Multi-Channel Frequencies of Gabor Filter
Authors: AS Alotaibi, MA Hebaishy
Year: 2014
Citation: 7

Title: Extraction of roads from high-resolution satellite images with the discrete wavelet transform
Authors: TM Talal, A El-Sayed, M Hebaishy, MI Dessouky, SA Alshebeili
Year: 2013
Citation: 4

Title: Optimized Daugman’s algorithm for iris localization
Authors: MA Hebaishy
Year: 2008
Citation: 4

Title: Sibs: A sparse encoder utilizing self-inspired bases for efficient image representation
Authors: AN Omara, MA Hebaishy, MS Abdallah, YI Cho
Year: 2024
Citation: 3

Title: Poster: Optimized Daugman’s algorithm for iris localization
Authors: M Hebaishy
Year: 2008
Citation: 3

Title: Fast Fingerprint Identification based on the DoG Filter
Authors: MA Hebaishy, FA Syam
Year: 2025

Title: S-shaped patch antenna array for automotive applications in X-band for wireless communications
Authors: MA Hebaishy
Year: 2024

Title: Building an automatic waste sorting system with controller based wireless sensor smart segregation system
Authors: MA Hebaishy
Year: 2024

Title: Security system based on human iris
Authors: HS Ahmed, MA Hebaishy
Year: 2014

Title: Attitude determination for geostationary satellite using optimized real time image registration algorithm
Authors: AE OA Elsayed, A Farrag, M Hebaishy
Year: 2009

Title: Texture analysis of the human iris for high authentication
Authors: MA Hebaishy, BV Gerkov
Year: 2002

Title: Using phase demodulator for encoding iris
Authors: AS Alotaibi, MA Hebaishy

Conclusion

Dr. Mohamed Ahmed Hebaishy is highly deserving of the Best Researcher Award for his significant contributions to biometrics, image processing, and satellite imaging, which have advanced both scientific understanding and practical applications in security and space research. His extensive academic career, impactful publications, leadership roles, and dedication to mentoring students highlight his commitment to advancing knowledge and fostering innovation. With his proven expertise and strong foundation in applied research, he is well positioned to continue driving advancements in computer vision, human identification systems, and international collaborations, further strengthening his role as a leader in research and society.