Xin Li

Currently Seeking: 1-2 openings for PhD students in the above research areas to begin Fall 2024. Please email [email protected] with your CV, a description of your professional experience or interest in the research area. Offers will be made in (March) Spring 2024.

Appointments 

Aug. 2023 – Present     Professor, Dept. of Computer Science, University at Albany
May 2015 – Aug. 2023    Professor, Lane Department of CSEE, West Virginia University
May 2009 – May 2015    Associate Professor, Lane Department of CSEE, West Virginia University
Jan. 2003 – May 2009    Assistant Professor, Lane Department of CSEE, West Virginia University
Aug. 2000 – Dec. 2002  Member of Technical Staff, Sharp Labs of America

Publications / Patents

1. T. Huang, W. Dong, F. Wu, X. Li and G. Shi, "Uncertainty-Driven Knowledge Distillation for Language Model Compression," in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 2850-2858, 2023, doi: 10.1109/TASLP.2023.3289303
2. Lu, Xiaotong, Weisheng Dong, Xin Li, Jinjian Wu, Leida Li, and Guangming Shi. "Adaptive Search-and-Training for Robust and Efficient Network Pruning." IEEE Transactions on Pattern Analysis and Machine Intelligence (2023).
3. Ning, Qian, Weisheng Dong, Xin Li, and Jinjian Wu. "Searching Efficient Model-Guided Deep Network for Image Denoising." IEEE Transactions on Image Processing 32 (2022): 668-681.
4. Hu, Chuanbo, Minglei Yin, Bin Liu, Xin Li, and Yanfang Ye. "Detection of illicit drug trafficking events on instagram: A deep multimodal multilabel learning approach." In Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 3838-3846. 2021. Best Paper Runner-up Award
5. Dong, Weisheng, Jinjian Wu, Leida Li, Guangming Shi, and Xin Li. "Bayesian Deep Learning for Image Reconstruction: From structured sparsity to uncertainty estimation." IEEE Signal Processing Magazine 40, no. 1 (2023): 73-84.
6. Fang, Zhenxuan, Fangfang Wu, Weisheng Dong, Xin Li, Jinjian Wu, and Guangming Shi. "Self-supervised Non-uniform Kernel Estimation with Flow-based Motion Prior for Blind Image Deblurring." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 18105-18114. 2023.
7. Fang, Zhenxuan, Weisheng Dong, Xin Li, Jinjian Wu, Leida Li, and Guangming Shi. "Uncertainty learning in kernel estimation for multi-stage blind image super-resolution." In European Conference on Computer Vision, pp. 144-161. Cham: Springer Nature Switzerland, 2022.
8. Yang, Zhou, Weisheng Dong, Xin Li, Jinjian Wu, Leida Li, and Guangming Shi. "Self-feature Distillation with Uncertainty Modeling for Degraded Image Recognition." In European Conference on Computer Vision, pp. 552-569. Cham: Springer Nature Switzerland, 2022.
9. Yang, Zhou, Weisheng Dong, Xin Li, Mengluan Huang, Yulin Sun, and Guangming Shi. "Vector Quantization with Self-Attention for Quality-Independent Representation Learning." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 24438-24448. 2023.
10. Ning, Qian, Jingzhu Tang, Fangfang Wu, Weisheng Dong, Xin Li, and Guangming Shi. "Learning degradation uncertainty for unsupervised real-world image super-resolution." In Proc. 31st Int. Joint Conferences Artif. Intell., pp. 1261-1267. 2022.

Synergistic Activities

Awards (Selected)

• 2022 Top 2% Leading Global Scientist Subfield: AI & Image Processing
• 2022 Outstanding Member of Editorial Board IEEE Transactions on Image Processing
• 2021 Outstanding Researcher Award College of Engineering and Mineral Resource, WVU
• 2021 Best Applied Paper Runner-UP Award ACM Conference, CIKM
• 2020 Runner-UP Award AIM 2020 Challenge on Video Extreme Super-Resolution
• 2018 Outstanding Researcher Award College of Engineering and Mineral Resource, WVU
• 2017 IEEE Fellow Signal Processing Society, IEEE

Professional Service (Selected)

• Senior Area Editor for IEEE Trans. on Image Processing, 2021-present
• Associate Editor for IEEE Trans. on Image Processing, 2018-2020
• Senior Area Editor for IEEE Signal Processing Letters, 2018-2020
• Member of Image, Video, and Multidimensional Signal Processing Technical Committee, 2011-2016
• Member of Computational Imaging Technical Committee,2023-2025
• Tutorial Chair for ICIP'2013, Area Chairs for ICIP'2012-2018 and ICASSP'2012-2017
• NSF Panelist for CIF, CCSS, HCC, ASCENT, NRI, and CRII.

Development of research datasets: 

• Design and construction of several datasets to support video and image processing research including IMAX dataset for image demosaicing, Wax Figure Face Database for face spoofing detection, Instagram data for illicit drug dealer detection, and CITeR face morphing dataset for Morphing Attack Detection.

Contribution to ChatGPT-based interdisciplinary research: 

• In our latest study, we proposed an iterative model to fine-tune instructions for guiding a ChatGPT in generating code for bioinformatics data analysis tasks. We demonstrated the feasibility of the model by applying it to various bioinformatics topics. Additionally, we discussed practical considerations and limitations regarding the use of the model in chatbot-aided bioinformatics education.