Tag: AI Scholar Award

Xiaohan Tu | Artificial Intelligence | Women Researcher Award

Published on by World Science Awards

Prof. Xiaohan Tu | Artificial Intelligence | Women Researcher Award

Zhengzhou Police University, China

Dr. Xiaohan Tu is an accomplished researcher and educator in computer science, currently serving as an Associate Professor at Zhengzhou Police University, China. She earned her M.Sc. (2017) and Ph.D. (2021) degrees in Computer Science and Technology from Hunan University, Changsha, China, where she developed strong expertise in cyber-physical systems, computer vision, and machine learning. In her professional career, Dr. Tu has demonstrated outstanding academic leadership, having successfully led four provincial and ministerial-level research projects and six departmental-level projects, while also contributing as a participant in the National Natural Science Foundation of China project on Smart Inspection Robots for catenary systems. Her research interests span applied artificial intelligence, deep learning, computer vision, robotics, and intelligent security technologies, with more than 23 publications indexed in IEEE and Scopus, earning 224 citations and an h-index of 9. She possesses strong research skills in algorithm optimization, feature extraction, LiDAR and point cloud analysis, monocular depth estimation, and real-time AI deployment on embedded and edge devices. Alongside research, she has compiled a provincial-level textbook and shown exceptional dedication to student mentorship, guiding her students to win 17 national awards, 58 provincial or ministerial awards, and 8 university-level awards in robotics, artificial intelligence, and Ministry of Education Category A competitions. Dr. Tu’s outstanding contributions have been recognized with multiple honors, including first prize in university-level teaching achievement, Outstanding Instructor awards for four consecutive years at the China Robot and Artificial Intelligence Competition, and the Outstanding Organization Award from the National Video Investigation Technology and Special Photography Professional Committee. Additionally, she serves as a reviewer for several prestigious IEEE journals, further underlining her professional recognition in the international research community. In conclusion, Dr. Xiaohan Tu’s exceptional academic qualifications, innovative research outputs, mentorship achievements, and professional honors establish her as a highly influential scholar with strong potential to advance AI-driven cyber-physical systems and intelligent security applications at both national and international levels.

Profile: Scopus

Featured Publication

  1. Tu, X., Yang, L. T., Liu, S., & Li, R. (2024). Accelerated feature extraction and refinement for improved aerial scene categorization. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–17.

  2. Tu, X., Zhang, C., Liu, S., Xu, C., & Li, R. (2023). Point cloud segmentation of overhead contact systems with deep learning in high-speed rails. Journal of Network and Computer Applications, 216, 103671.

  3. Tu, X., Zhang, C., Zhuang, H., Liu, S., & Li, R. (2024). Fast drone detection with optimized feature capture and modeling algorithms. IEEE Access, 12, 108374–108388.

  4. Liu, S., Tu, X., Xu, C., & Li, R. (2022). Deep neural networks with attention mechanism for monocular depth estimation on embedded devices. Future Generation Computer Systems, 131, 137–150.

  5. Liu, S., Yang, L. T., Tu, X., Li, R., & Xu, C. (2022). Lightweight monocular depth estimation on edge devices. IEEE Internet of Things Journal, 9(17), 16168–16180.

Mona Jamjoom | AI | Best Researcher Award

Published on by World Science Awards

Assoc Prof Dr. Mona Jamjoom | AI | Best Researcher Award

Assoc Prof Dr. Mona Jamjoom, Princess Nourah bint Abdulrahman University, Saudi Arabia

Assoc Prof Dr. Mona Jamjoom is an accomplished researcher in the field of artificial intelligence, recognized for her innovative contributions and impactful studies. With a strong focus on machine learning and data analytics, she has published numerous papers in leading journals and has been awarded the Best Researcher Award for her groundbreaking work. Mona is passionate about harnessing AI to solve complex problems and improve decision-making processes across various industries. Her commitment to advancing technology while addressing ethical considerations makes her a prominent figure in the AI community.

Profile:

Scholar

Academics:

Assoc Prof Dr. Mona Jamjoom holds a PhD in Artificial Intelligence from King Saud University, awarded in May 2016. She also earned her Master’s degree in Computer Science from the same institution in 2004, following her Bachelor’s degree in Computer Science, which she completed in 1992. Her academic background provides a strong foundation for her research and contributions to the field of AI.

Professional Experiences:

Assoc Prof Dr. Mona Jamjoom has extensive professional experience in academia. Since 2021, she has served as an Associate Professor at Princess Nourah bint Abdulrahman University in Riyadh, Saudi Arabia. Prior to this, she was an Assistant Professor at the same institution from 2017 to 2021. Mona began her academic career as a Lecturer at Princess Nourah bint Abdulrahman University from 2007 to 2016, and before that, she worked as a Teaching Assistant from 1998 to 2007. Her career in the field began in 1993, when she provided technical support at the university, further solidifying her commitment to education and technology.

Activities:

Assoc Prof Dr. Mona Jamjoom is actively engaged in various professional activities that enhance her contributions to the field of artificial intelligence. In 2024, she joined the work team at the Center for Advanced Studies in Artificial Intelligence at King Saud University, collaborating on the KSU AI Satellite Lab project with SDAIA. She served as an external examiner for a doctoral thesis on deep learning applications for visual pollution detection in Riyadh. Additionally, she reviewed applications for the Apple Developer Academy’s second challenge for female students and participated in consulting sessions during the Gulf Hackathon Program focused on AI in public education. Mona also acted as a consultant for the UNESCO project “AI Capacity Building in Arabic-speaking Countries,” supported by Huawei Technologies. She has reviewed numerous papers for ISI journals and attended the research day at Princess Nourah bint Abdulrahman University. Furthermore, she co-supervised a PhD student specializing in Cognitive Computing at Universiti Kuala Lumpur, Malaysia.

Publication Top Notes:

M. Adil, Z. Yinjun, M. M. Jamjoom, and Z. Ullah. “OptDevNet: An Optimized Deep Event-Based Network Framework for Credit Card Fraud Detection.” IEEE Access, vol. 12, pp. 132421-132433, 2024. doi: 10.1109/ACCESS.2024.3458944.

Rabbani, H., Shahid, M. F., Khanzada, T. J. S., Siddiqui, S., Jamjoom, M. M., Ashari, R. B., Ullah, Z., Mukati, M. U., and Nooruddin, M. “Enhancing Security in Financial Transactions: A Novel Blockchain-Based Federated Learning Framework for Detecting Counterfeit Data in Fintech.” PeerJ Computer Science, vol. 10, e2280, 2024.

Malik, M. S. I., Nawaz, A., and Jamjoom, M. M. “Hate Speech and Target Community Detection in Nastaliq Urdu Using Transfer Learning Techniques.” IEEE Access, 2024.

Kurtoğlu, A., Eken, Ö., Çiftçi, R., Çar, B., Dönmez, E., Kılıçarslan, S., Jamjoom, M. M., Abdel Samee, N., Hassan, D. S. M., and Mahmoud, N. F. “The Role of Morphometric Characteristics in Predicting 20-Meter Sprint Performance Through Machine Learning.” Scientific Reports, vol. 14, no. 1, 16593, 2024.

Shah, S. M. A. H., Khan, M. Q., Rizwan, A., Jan, S. U., Samee, N. A., and Jamjoom, M. M. “Computer-Aided Diagnosis of Alzheimer’s Disease and Neurocognitive Disorders with Multimodal Bi-Vision Transformer (BiViT).” Pattern Analysis and Applications, vol. 27, no. 3, 76, 2024.

Ishtiaq, A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Product Helpfulness Detection with Novel Transformer Based BERT Embedding and Class Probability Features.” IEEE Access, 2024.

Abbas, M. A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection from Social Media.” IEEE Access, 2024.

Elhadad, A., Jamjoom, M., and Abulkasim, H. “Reduction of NIFTI Files Storage and Compression to Facilitate Telemedicine Services Based on Quantization Hiding of Downsampling Approach.” Scientific Reports, vol. 14, no. 1, 5168, 2024.

Malik, M. S. I., Younas, M. Z., Jamjoom, M. M., and Ignatov, D. I. “Categorization of Tweets for Damages: Infrastructure and Human Damage Assessment Using Fine-Tuned BERT Model.” PeerJ Computer Science, vol. 10, e1859, 2024.

Malik, M. S. I., Nawaz, A., Jamjoom, M. M., and Ignatov, D. I. “Effectiveness of ELMo Embeddings and Semantic Models in Predicting Review Helpfulness.” Intelligent Data Analysis, (Preprint), 1-21, 2023.