Rashid Khan received a Master's degree in Computer Engineering from Near East University, Cyprus, in 2014, and a Ph.D. in Artificial Intelligence from the University of Science and Technology of China, Hefei, in 2022. He served as a postdoctoral researcher in Biomedical Engineering at Shenzhen University and Shenzhen Technology University from 2022 to 2024. Since 2024, he has been an Associate Researcher at Shenzhen Technology University. His main research interests include Artificial Intelligence, Computer Vision, Medical Image Processing, Natural Language Processing, Medical Image Segmentation, XUV, CDI, and laser beam optimization. He focuses on developing deep learning algorithms for high-resolution cancer cell imaging and AI-driven laser diagnostics, with applications in precision oncology. His research results include approximately 32 SCI journal and conference publications.

Google Scholar: https://scholar.google.com/citations?user=Ee3ctL4AAAAJ&hl=en

Selected Publications

1. Rashid Khan, Chao Chen, Asim Zaman, Jiayi Wu, Haixing Mai, Liyilei Su, Yan Kang, and Bingding Huang. "RenalSegNet: automated segmentation of renal tumor, veins, and arteries in contrast-enhanced CT scans." Complex & Intelligent Systems 11, no. 2 (2025): 1-20.

2. Rashid Khan, Bingding Huang, and Yan Kang, “Customized m-RCNN and Hybrid Deep Classifier for Liver Cancer Segmentation and Classification." Heliyon 10, no. 10 (2024): e30528

3. Rashid Khan, Chuda Xiao, Yang Liu, Jinyu Tian, Zhuo Chen, Liyilei Su, Dan Li, Haseeb Hassan, Haoyu Li, Weiguo Xie, Wen Zhong, Bingding Huang. "Transformative Deep Neural Network Approaches in Kidney Ultrasound Segmentation: Empirical Validation with an Annotated Dataset." Interdisciplinary Sciences: Computational Life Sciences (2024): 1-16.

4. Rashid Khan, Asim Zaman, Chao Chen, Chuda Xiao, Wen Zhong, Yang Liu, Haseeb Hassan et al. "MLAU-Net: Deep supervised attention and hybrid loss strategies for enhanced segmentation of low-resolution kidney ultrasound." Digital Health 10 (2024): 20552076241291306.

5. Rashid Khan, and Bingding Huang. "Visual Insight: Deep Multilayer Fusion with Inception-Based LSTM for Descriptive Image Captioning." In 2024 4th International Conference on Computer Communication and Artificial Intelligence (CCAI), pp. 124-131. IEEE, 2024.

6. Rashid Khan, Bingding Huang, Haseeb Hassan, Asim Zaman, and Zhongfu Ye. "A Comparative Study of Pre-trained CNNs and GRU-Based Attention for Image Caption Generation." In 2023 5th International Conference on Robotics and Computer Vision (ICRCV), pp. 92-99. IEEE, 2023.

7. Rashid Khan, Zhongfu Ye, Nuzhat Naqvi, and M. Shujah Islam. "A novel automatic image caption generation using bidirectional long-short term memory framework." Multimedia Tools and Applications 80 (2021): 25557-25582.

8. Rashid Khan, M. Shujah Islam, Khadija Kanwal, Mansoor Iqbal, Md Imran Hossain, and Zhongfu Ye. "Attention based sequence-to-sequence framework for auto image caption generation." Journal of Intelligent & Fuzzy Systems 43, no. 1 (2022): 159-170.

9. Rashid Khan, Furqan Rustam, Khadija Kanwal, Arif Mehmood, and Gyu Sang Choi. "US Based COVID-19 tweets sentiment analysis using textblob and supervised machine learning algorithms." In 2021 international conference on artificial intelligence (ICAI), pp. 1-8. IEEE, 2021.

10. Rashid khan. "Underwater Image Restoration Using Fusion and Wavelet Transform Strategy." J. Comput. 10, no. 4 (2015): 237-244.

11. Asim Zaman, Yingwei Guo, Xueqiang Zeng, Rashid Khan, Jiaxi Lub, Huihui Yang, Xiao Qiang Miao, Anbo Cao, Yingjian Yang, Haseeb Hassan, Yan Kanga, "AFMS-Net: An Adaptable Deep Learning Paradigm for High-Performance 3D Brain Lesion Segmentation in Medical Imaging." Front in Neuroscience 18 (2024): 1363930.

12. Ruan, Ruyun, Shoujin Huang, Liyilei Su, Rashid Khan, and Bingding Huang. "Predicting Microsatellite Instability from Pathological Images Using Self-Supervised Learning Methods." In Pro of the 2023 International Conf on Advances in  AI and Applications, pp. 223-228. (2023).

13. Zaka-Ud-Din Muhammad, Zhangjin Huang, and Rashid Khan. "A review of 3D human body pose estimation and mesh recovery." Digital Signal Processing 128 (2022): 103628.

14. Islam, M. Shujah, Khush Bakhat, Mansoor Iqbal, Rashid Khan, ZhongFu Ye, and M. Mattah Islam. "Representation for action recognition with motion vector termed as: SDQIO." Expert Systems with Applications 212 (2023): 118406.

15. Abdussalam, Amr, Zhongfu Ye, Ammar Hawbani, Majjed Al-Qatf, and Rashid Khan. "NumCap: A number-controlled multi-caption image captioning network." ACM Transactions on Multimedia Computing, Communications and Applications 19, no. 4 (2023): 1-24.

Awards and Honors

1. Best Paper Presentation Award, IEEE 4th International Conference on Computer Communication and AI (CCAI), 2024

2. Chinese Government Scholarship (CAS-TWAS), Ph.D., 2018–2022

3. TA Award, ISCAI International Summer Camp on AI, USTC, 2019

4. Merit-based Scholarship, Near East University, Master’s Degree, 2012–2014

Professional Activities

Volunteer Reviewer: ACM Computing Surveys, Bioengineering, Frontiers in Neuroscience, BMC Neurology, Computer in Bio and Med, Neural Computing and Applications, IEEE TMI, Biomedical Signal Processing and Control, Scientific Report, Discover Artificial Intelligence, and IEEE Transactions on Consumer Electronics.