Shi Zenglin is a Full Professor at the School of Computer and Information, Hefei University of Technology, Hefei, China. He received his PhD degree from University of Amsterdam in Netherlands, where he worked closely with Prof. Cees Snoek and Dr. Pascal Mattes. After his PhD, He moved to Singapore to work as a research scientist at A*STAR in Singapore from 2022 July to 2023 December. His research interests include Multimedia Computing, Computer Vision and Machine Learning. Currently, his research focuses on adaptive machine learning and Multimodal Large Language Models, specifically on continual learning, test-time adaptation, prompt-based learning, instruction tuning, retrieval augmented generation, etc. He has published 25 papers (12 first/co-first) in top-tier journals and conferences, such as TPAMI, IJCV, TIP, CVPR, ICCV, MICCAI, receiving more than 1200 paper citations.

Representative works：

[1] Zenglin Shi, Pascal Mettes, Cees G. M. Snoek. ``Focus for Free in Density-Based Counting", International Journal of Computer Vision (IJCV), 2023. 

[2] Zenglin Shi, Pascal Mettes, Subhransu Maji, Cees G. M. Snoek. ``On Measuring and Controlling the Spectral Bias of the Deep Image Prior", International Journal of Computer Vision (IJCV), 2022. 

[3] Zenglin Shi, Yunlu Chen, Efstratios Gavves, Pascal Mettes, Cees G. M. Snoek. ``Unsharp Mask Guided Filtering", IEEE Transactions on Image processing (TIP), 2021. 

[4] Le Zhang*, Zenglin Shi*（Equal contribution）, Joey Tianyi Zhou, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Zeng Zeng, Chunhua Shen. ``Ordered or Orderless: A Revisit for Video based Person Re-ID", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021. 

[5] Le Zhang*, Zenglin Shi* （Equal contribution）, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Joey Tianyi Zhou, Guoyan Zheng, Zeng Zeng. ``Nonlinear Regression via Deep Negative Correlation Learning", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. 

[6] Zenglin Shi, Pascal Mettes, Cees G. M. Snoek. ``Counting with Focus for Free", International Conference on Computer Vision (ICCV), 2019. 

[7] Zenglin Shi, Le Zhang, Ming-Ming Cheng, et al. ``Crowd Counting with Deep Negative Correlation Learning", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. 

[8] Zenglin Shi, Guodong Zeng, Guoyan Zheng, et al. ``Bayesian VoxDRN: A Probabilistic Deep Voxelwise Dilated Residual Network for WholeHeart Segmentation from 3D MR Images'', International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018 

[9] Zenglin Shi, Le Zhang, Yibo Sun and  Yandong Ye. ``Multiscale Multitask Deep NetVLAD for Crowd Counting", IEEE Transactions on Industrial Informatics (TII), 2018. 

[10] Zenglin Shi, Yangdong Ye, Yunpeng Wu. ``Rank-based Pooling for Deep Convolutional Neural Networks", Neural Networks, 2016.