Mr. Wang Xiaofeng | Artificial Intelligence | Best Researcher Award

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Mr. Wang Xiaofeng | Artificial Intelligence | Best Researcher Award

PhD Student at Artificial Intelligence, INTI International University, Malaysia

👨‍🎓He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

👨‍🎓 Xiaofeng Wang (1980) is a PhD candidate in the Faculty of Data Science and Information Technology at INTI International University, Nilai, Malaysia. Originally from Shanxi, China, he graduated from Xinzhou Normal University with a major in Computer Science and Technology. He furthered his education at Shanxi University, specializing in Computer Systems Engineering.

Other Activity:

👨‍🏫 Currently, Xiaofeng Wang is a lecturer in the Department of Computer Science at Xinzhou Normal University in Shanxi. His primary research interests revolve around the Internet of Things, cyberspace security, artificial intelligence, and deep learning. Over the past few years, he has made significant contributions to his field, with 3 SCI papers, 1 EI paper, 2 Scopus papers, 1 book, and involvement in several research projects.

Publications:

  1. Wang, X., Othman, M., Dewi, D.A., Wang, Y. (2024). WSLC: Weighted semi-local centrality to identify influential nodes in complex networks. Journal of King Saud University – Computer and Information Sciences, 36(1), 101906.
  2. Wang, X., Wang, Y., Javaheri, Z., Moghadamnejad, N., Younes, O.S. (2023). Federated deep learning for anomaly detection in the internet of things. Computers and Electrical Engineering, 108, 108651.
  3. Wang, Y., Wang, X., Ariffin, M.M., Alqhatani, A., Almutairi, L. (2023). Attack detection analysis in software-defined networks using various machine learning methods. Computers and Electrical Engineering, 108, 108655.
  4. Wang, X. (2013). The research of digital recognition technology based on bp neural network. BioTechnology: An Indian Journal, 8(2), 180–185.

 

 

Ms. Mohaddeseh Koosha | Artificial Intelligence | Best Researcher Award

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Ms. Mohaddeseh Koosha : Leading Researcher in Artificial Intelligence

PhD Student at Artificial Intelligence, Amirkabir University of Technology, Iran

She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Ms. Mohaddeseh Koosha is an expert in signal and image processing with a passion for extracting features from natural patterns. She enjoys applying evolutionary algorithms to solve regression and classification problems and has a keen interest in studying scientific papers for new ideas. Ms. Koosha holds a Master’s degree in Electronics from Sharif University of Technology and is currently completing her Ph.D. in Computer Engineering with a focus on Artificial Intelligence at Amirkabir University of Technology. While she initially worked in electrical engineering, specifically in microelectronics and VHDL, she transitioned her focus to Artificial Intelligence eight years ago. Ms. Koosha has published in high-impact journals such as Knowledge-Based Systems (Elsevier) and IET Image Processing, as well as in conference publications. She has served as a peer-reviewer for IET Image Processing and has collaborated with Professor Mohammad Mehdi Ebadzadeh on Genetic Programming within the field of Evolutionary Algorithms. Throughout her career, Ms. Koosha has successfully completed several engineering projects for various companies, showcasing her expertise and practical skills in the field.

Research, Innovations and Extension:

Ms. Mohaddeseh Koosha has completed 12 research projects and has ongoing research activities. She has a citation index of 12 in Scopus/Web of Science or PubMed/Indian Citation Index. Additionally, she has been involved in 8 consultancy and industry-sponsored projects. Ms. Koosha has published 2 books with ISBN (text, reference, chapters, and conference proceedings) and has a cumulative project cost of USD/INR 30,000. She has published patents and has 2 journals indexed in SCI and SCIE. She has also held editorial appointments in journals/conferences and has 2 publications in Scopus, Web of Science, and PubMed indexes. Furthermore, she has a notable H-index based on Scopus/Web of Science, has organized research conferences/workshops, and has been involved in collaborative activities and received numerous awards and recognition. Ms. Koosha is a member of professional bodies and has functional MoUs with other universities/industries/corporates.

Research & Development:

👩‍🔬 Ms. Mohaddeseh Koosha is currently focusing on using artificial intelligence in developing biometric research, particularly in extracting biometric features from face and eyes. She is also using probabilistic genetic programming to resolve regression problems, such as making predictions from data gathered from CT Scan devices and making pollution condition forecasts. Additionally, she is enthusiastic about gathering healthcare-relevant features and observing their influence on life expectancy.