Mrs. Fan Wang | Data Analysis | Best Researcher Award

Mrs. Fan Wang, Xi’an Shiyou University, China .

Mrs. Fan Wang is a Lecturer at Xi’an Shiyou University, China, specializing in imaging, image processing, data analysis, and machine learning. She earned her Ph.D. and Master’s degrees in Graphic and Image Processing from Northwestern Polytechnical University, Xi’an, China. With a strong academic foundation, Dr. Wang is passionate about advancing methodologies in image processing and applying machine learning to solve complex visual data challenges. Her expertise in data-driven approaches continues to inspire innovation and impactful contributions to the field of computational imaging.

Education and Experience

Education

Ph.D. in Theory and Methods of Graphic and Image Processing, Northwestern Polytechnical University, Xi’an, China (2018–2022)

M.S. in Theory and Methods of Graphic and Image Processing, Northwestern Polytechnical University, Xi’an, China (2015–2018)

Experience

Lecturer, Xi’an Shiyou University, Xi’an, China (2022–present)

Suitability for the Award

Mrs. Fan Wang, a dedicated researcher and Lecturer at Xi’an Shiyou University, specializes in imaging, image processing, data analysis, and machine learning. With a Ph.D. and M.S. in Theory and Methods of Graphic and Image Processing from Northwestern Polytechnical University, she has demonstrated expertise in advanced computational techniques. Her contributions to innovative research and academic excellence make her a strong contender for the Best Researcher Award.

Professional Development

Mrs. Fan Wang is a researcher and educator specializing in cutting-edge techniques in imaging and machine learning. With a Ph.D. in Graphic and Image Processing, she has developed advanced skills in data analysis and the application of AI algorithms to enhance image interpretation and processing. Currently a Lecturer at Xi’an Shiyou University, Dr. Wang is committed to fostering innovation and knowledge dissemination through teaching and collaborative research. Her work integrates computational intelligence with visual data, advancing impactful solutions in imaging technologies.

Research Focus

Mrs. Fan Wang’s research lies at the intersection of imaging and artificial intelligence. She focuses on developing innovative methods for image processing, leveraging data analysis to optimize the extraction of meaningful information from complex visual datasets. Her work also involves applying machine learning techniques to automate and enhance image interpretation for diverse applications. Dr. Wang aims to address challenges in computational imaging by combining theory with practical solutions, driving advancements in visualization technologies for academic and industrial use.

Awards and Honors

Ph.D. Scholarship Award, Northwestern Polytechnical University (2022)

Recognized for Excellence in Research during Graduate Studies (2018–2022)

Best Presentation Award in Machine Learning Symposium (2021)

Published high-impact research in top-tier journals on imaging and AI methods

Contributor to innovative methodologies in graphic and image processing

Publication Highlights

Intensifying graph diffusion-based salient object detection with sparse graph weighting (2023) – Cited by: 0

Graph construction by incorporating local and global affinity graphs for saliency detection (2022) – Cited by: 3

Saliency detection based on color descriptor and high-level prior (2021) – Cited by: 3

Graph-based saliency detection using a learning joint affinity matrix (2021) – Cited by: 4

Saliency detection via coarse-to-fine diffusion-based compactness with weighted learning affinity matrix (2021) – Cited by: 1

Salient object detection via cross diffusion-based compactness on multiple graphs (2021) – Cited by: 4

Salient Object Detection via Quaternionic Local Ranking Binary Pattern and High-Level Priors (2019, Conference Paper) – Cited by: 0

Underwater Image Restoration Based on Background Light Estimation and Dark Channel Prior (2018) – Cited by: 25

Shadi Atalla | Data Science | Best Researcher Award

Dr. Shadi Atalla, University of DUbai, United Arab Emirates.

Dr. Shadi Atalla is an accomplished academic and researcher specializing in Computing and Information Systems. With a Ph.D. in Computer Networks from Politecnico di Torino, Italy, he has extensive experience in teaching, research, and academic leadership. He is currently an Associate Professor and Director of Computing and Information Systems at the University of Dubai, UAE. Dr. Atalla is passionate about developing innovative curricula, driving accreditation efforts, and fostering research in Data Science, AI, and Machine Learning. His work has earned him multiple research excellence awards, and he actively contributes to global advancements in academic and research technologies.

Publication profile

Googlescholar

Education:

Ph.D. in Computer Networks, Politecnico di Torino, Italy (2012)
M.Sc. in Computer and Communication Networks, Politecnico di Torino, Italy (2008)
B.Sc. in Computer Engineering, An-Najah National University, Palestine (2004)

Experience:

Associate Professor & Director, Computing & Information Systems, University of Dubai (2021–Present)
Assistant Professor, University of Dubai (2016–2021)
Visiting Professor, Al Ghurair University, Dubai (2014–2016)
Post-Doctoral Researcher, Istituto Superiore Mario Boella, Italy (2012–2014)
Researcher, Istituto Superiore Mario Boella, Italy (2008–2009)
Teaching Assistant, An-Najah National University, Palestine (2004–2006)
Network Architect, Net Point Company for Wireless Communication, Palestine (2004)

Suitability For The Award

Dr. Shadi Atalla is an outstanding candidate for the Best Researcher Award due to his significant contributions to the fields of computing, information systems, and data science. With a proven track record of high-impact research, leadership in academic programs, and a commitment to advancing cutting-edge technologies, Dr. Atalla has consistently demonstrated excellence in his field. His involvement in internationally recognized projects, coupled with his ability to secure substantial research funding, positions him as a leading researcher in his domain.

Professional Development

Dr. Shadi Atalla has participated in numerous professional development programs to enhance his expertise in the ever-evolving fields of computing and data science. He has completed certifications in Applied Data Science, Machine Learning, and Python from the University of Michigan and IBM, showcasing his commitment to continuous learning. He has also participated in training on program assessment and accreditation (ABET), Generative AI, and various data science applications. His focus on innovation is evident from his active engagement in professional development programs that enable him to integrate new technologies such as AI, cloud computing, and big data analytics into academic curricula.

Research Focus

Dr. Shadi Atalla’s research primarily revolves around Data Science, Machine Learning, AI, IoT, and Computer Networks. His research interests include advanced algorithms for applied machine-to-machine communication, network optimization, and pervasive technologies in the IoT space. He has contributed to projects such as energy management systems and optical networks, demonstrating his expertise in both theoretical and applied research. His involvement in European Commission-funded projects and collaborations with international organizations underscores his commitment to advancing technological innovation, particularly in areas like indoor localization, network security, and smart life assistant applications.

Awards and Honors

Excellence in Research Award, University of Dubai (2022, 2019)
Best Paper Award, ICSPIS 2022
Honours College, An-Najah National University
TopMed 2nd Level Master Scholarship (2 years)
Full Politecnico di Torino PhD Scholarship (3 years)

Publoication Top Notes

Smart real-time healthcare monitoring and tracking system using GSM/GPS technologies
K Aziz, S Tarapiah, SH Ismail, S Atalla | Cited by: 167 | Year: 2016
Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions
SS Sohail, F Farhat, Y Himeur, M Nadeem, DØ Madsen, Y Singh, S Atalla, … | Cited by: 157 | Year: 2023
A comprehensive review of recent research trends on unmanned aerial vehicles (UAVs)
K Telli, O Kraa, Y Himeur, A Ouamane, M Boumehraz, S Atalla, … | Cited by: 117 | Year: 2023
An innovative deep anomaly detection of building energy consumption using energy time-series images
A Copiaco, Y Himeur, A Amira, W Mansoor, F Fadli, S Atalla, SS Sohail | Cited by: 83 | Year: 2023
Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics
M Daradkeh, L Abualigah, S Atalla, W Mansoor | Cited by: 56 | Year: 2022
IoT-enabled precision agriculture: Developing an ecosystem for optimized crop management
S Atalla, S Tarapiah, A Gawanmeh, M Daradkeh, H Mukhtar, Y Himeur, … | Cited by: 55 | Year: 2023
Social Media for Teaching and Learning within Higher Education Institution: A Bibliometric Analysis of the Literature (2008-2018)
KF Hashim, A Rashid, S Atalla | Cited by: 54 | Year: 2018

Fan Wang | Data Analysis | Best Researcher Award

Mrs. Fan Wang | Data Analysis | Best Researcher Award

Mrs. Fan Wang, Xi’an Shiyou University, China .

Publication Profile

Education and Experience

Education

Suitability for the Award