Current PhD students (sorted by last names)

Hritam Basak

Ph.D. student, Computer Science, 09/2022 – now

B.S., Jadavpur University, 2017-2021

 

Papers

1.     Hritam Basak, and Zhaozheng Yin, “Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning,” the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.

2.       Hritam Basak, and Zhaozheng Yin, “Pseudo-label Guided Contrastive Learning for Semi-supervised Medical Image Segmentation,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

 

Jianxiang Dong

Ph.D. student, Computer Science, 09/2020 – now

M.S., George Washington University, 2018-2020

B.S., Northeastern University, 2014-2018

 

Papers

1.     Jianxiang Dong, and Zhaozheng Yin, “Boundary-aware Temporal Sentence Grounding with Adaptive Proposal Refinement,” the 16th Asian Conference on Computer Vision (ACCV), 2022.

 

Jignesh Gutta

Ph.D. student, Computer Science, 01/2023 – now

B.E., Vellore Institute of Technology, 2018-2022

 

Papers

1.     Jignesh Gutta, and Zhaozheng Yin, “Diffusion Transformer U-Net for Medical Image Segmentation,” the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.

 

Muhammad Monjurul Karim

(Co-supervised with Dr. Qin)

Ph.D. student, Civil Engineering, 2020-now

B.S., Bangladesh University of Science and Technology, 2014

 

Papers

1.      Muhammad Monjurul Karim, Zhaozheng Yin, and Ruwen Qin, “An Attention-guided Multistream Feature Fusion Network for Early Localization of Risky Traffic Agents in Driving Videos,” IEEE Transactions on Intelligent Vehicles (TIV). Accepted. May 2023. (Impact Factor: 5.009)

2.       Muhammad Monjurul Karim, Yu Li, Ruwen Qin, and Zhaozheng Yin, “A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidents,” IEEE Transactions on Intelligent Transportation Systems (ITS). 23(7): 9590-9600. July 2022. (Impact Factor: 9.551)

3.      Muhammad Monjurul Karim, Ruwen Qin, Zhaozheng Yin, and Genda Chen, “A Semi-supervised Self-training Method to Develop Assistive Intelligence for Segmenting Multiclass Bridge Elements from Inspection Videos,” Structure Health Monitoring (SHM). 21(3). May 2021. (Impact Factor: 5.929)

4.      Muhammad Monjurul Karim, Yu Li, Ruwen Qin, and Zhaozheng Yin, “A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention. The 100th Transportation Research Board (TRB) Annual Meeting, January 5-29, 2021.

 

 

Md. Moniruzzaman

Ph.D. student, Computer Science, 01/2017 - present

B.S., Electronics and Communication Engineering, Khulna University of Engineering & Technology (KUET), Bangladesh 2014

 

Papers

1.      Md Moniruzzaman, and Zhaozheng Yin, “Collaborative Foreground, Background, and Action Modeling Network for Weakly Supervised Temporal Action Localization,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). Accepted. April 2023. (Impact Factor: 5.859)

2.      Md Moniruzzaman, and Zhaozheng Yin, “Feature Weakening, Contextualization, and Discrimination for Weakly Supervised Temporal Action Localization,” IEEE Transactions on Multimedia (TMM). Accepted. March 2023. (Impact Factor: 8.812)

3.      Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming Leu, and Ruwen Qin, “Jointly-Learnt Networks for Future Action Anticipation via Self-Knowledge Distillation and Cycle Consistency,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). Accepted. December 2022. (Impact Factor: 5.859)

4.      Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ruwen Qin, and Ming Leu, “Human Action Recognition by Discriminative Feature Pooling and Video Segment Attention Model,” IEEE Transaction on Multimedia (TMM). 24: 689-701. 2021. DOI: 10.1109/TMM.2021.3058050. (Impact Factor: 8.182)

5.      Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ruwen Qin, and Ming Leu, “Action Completeness Modeling with Background Aware Networks for Weakly-Supervised Temporal Action Localization,” ACM Multimedia Conference (ACMMM), 2020.

6.      Md Moniruzzaman, Zhaozheng Yin and Ruwen Qin, “Spatial Attention Mechanism for Weakly Supervised Fire and Traffic Accident Scene Classification,” In Proceedings of the 5th IEEE International Conference on Smart Computing (SMARTCOMP’19), Washington DC. June 12-14, 2019.

 

Award and Honor

2. The 3rd Best Poster Award in the ISC poster competition, November 2018.

1. The 2nd Best Paper Award in the ISC graduate research symposium, April 2018.

 

Graduated Ph.D. students (sorted by last names):

Liang Han

Assistant Professor at Shenzhen, China, now.

Postdoc Fellow, 08/2022 – 02/2023

Ph.D., Computer Science, 09/2015 – 08/2022

M.S., School of Mathematics. Shandong University, 2014

B.S., School of Mathematics. Shandong University, 2011

 

Internship: Alibaba, Damo Academy, Seattle. 08/2018-08/2019

 

Papers

13. Liang Han, Hang Su and Zhaozheng Yin, “Phase Contrast Image Restoration by Mathematically Formulating Its Imaging Principle and Reversing the Formulation with Deep Neural Networks,” IEEE Transactions on Medical Imaging (TMI). 2023. Accepted. (Impact Factor: 11.037)

12. Liang Han, and Zhaozheng Yin, “Global Memory and Local Continuity for Video Object Detection,” IEEE Transaction on Multimedia (TMM). 2022. Accepted. (Impact Factor: 8.182)

11. Liang Han, Pichao Wang, Zhaozheng Yin, Fang Wang, and Hao Li, “Context and Structure Mining Network for Video Object Detection,” International Journal of Computer Vision (IJCV). 129: 2927-2946, 2021. (Five-year Impact Factor: 13.284)

10. Liang Han, Pichao Wang, Zhaozheng Yin, Fang Wang, and Hao Li, “Class-aware Feature Aggregation Network for Video Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). July 2021. (Impact Factor: 5.859)

9. Liang Han, and Zhaozheng Yin, “Unsupervised Network Learning for Cell Segmentation,” the 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

8. Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, Rong Jin, “Price Suggestion for Online Second-Hand Items,” the 25th International Conference on Pattern Recognition (ICPR), 2020.

7. Liang Han, Pichao Wang, Zhaozheng Yin, Fan Wang, Hao Li, “Exploiting Better Feature Aggregation for Video Object Detection,” ACM Multimedia Conference (ACMMM), 2020.

6. Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, and Rong Jin. “Price Suggestion for Online Second-hand Items with Texts and Images,” ACM Multimedia Conference (ACMMM), 2020.

5. Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, and Rong Jin. “Vision-based Price Suggestion for Online Second-hand Items,” ACM Multimedia Conference (ACMMM), 2019.

4. Liang Han and Zhaozheng Yin, “Learning to Transfer Microscopy Image Modalities,” Machine Vision and Applications. DOI: 10.1007/s00138-018-0946-7, June 2018.

3. Liang Han and Zhaozheng Yin, “A Cascaded Refinement GAN for Phase Contrast Microscopy Image Super Resolution,” the 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018.

2. Liang Han and Zhaozheng Yin, “Refocusing Phase Contrast Microscopy Images,” the 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017.

1. Liang Han and Zhaozheng Yin, “Transferring Microscopy Image Modalities with Conditional Generative Adversarial Networks,” CVPR Workshop on Computer Vision for Microscopy Image Analysis, 2017.

 

Wenchao Jiang

Now at Google

Ph.D., Computer Science, Missouri S&T, 01/2013 – 01/2017

B.S., Electronic Information Engineering, University of Electronic Science and Technology of China, 2012

 

Internship: Intuitive Surgical

 

Papers

9. Wenchao Jiang and Zhaozheng Yin, “Indoor Localization with a Signal Tree,” Multimedia Tools and Applications.  Springer. 76(19): 20317-20339. October 2017.

8. Wenchao Jiang and Zhaozheng Yin, “Combining Passive Visual Cameras and Active IMU Sensors for Persistent Pedestrian Tracking,” Journal of Visual Communication and Image Representation. Elsevier. 48: 419-431. October 2017.

7. Wenchao Jiang and Zhaozheng Yin, “Seeing the Invisible in Differential Interference Contrast Microscopy Images,” Medical Image Analysis (MedIA). 34: 65-81. December 2016.

6. Wenchao Jiang and Zhaozheng Yin, “Human Tracking using Wearable Sensors in the Pocket,” IEEE Global Conference on Signal & Information Processing (GlobalSIP), 2015.

5. Wenchao Jiang and Zhaozheng Yin, “Human Activity Recognition using Wearable Sensors by Deep Convolutional Neural Networks,” ACM Multimedia Conference (ACMMM), 2015.

4. Wenchao Jiang and Zhaozheng Yin, “Combining Passive Visual Cameras and Active IMU Sensors to Track Cooperative People,” the 18th International Conference on Information Fusion (FUSION), 2015.

3. Wenchao Jiang and Zhaozheng Yin, “Indoor Localization by Signal Fusion,” the 18th International Conference on Information Fusion (FUSION), 2015.

2. Wenchao Jiang and Zhaozheng Yin, “Restoring the Invisible Details in Differential Interference Contrast Microscopy Images,” the 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015.

1. Wenchao Jiang, Haohan Li, Zhaozheng Yin and Yaojan Wu, “Vehicle Reidentification in Low-Resolution Videos for Travel Time Estimation,” The Transportation Research Board (TRB) 94th Annual Meeting, 2015.

 

Award and Honor

3. Young Scientist Award Runner-Up, MICCAI 2015.

2. CS Academic Achievement Award, 2015.

1. CS Academic Achievement Award, 2014.

 

Haohan Li

Now at NIH

Ph.D. student, Computer Science, 01/2016 - 05/2020

B.S., South China University of Technology, 2011

 

Internship: 12 Sigma Technologies, San Diego, 05/2019-08/2019

 

Papers

5. Haohan Li and Zhaozheng Yin “Attention, Suggestion and Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation,” the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.

4. Haohan Li, Zhaozheng Yin, Paul Manley, Joel Burken, Nadia Shakoor, Noah Fahlgren, and Todd Mockler, “Early Drought Stress Detection with Bidirectional Long Short-Term Memory Networks,” Journal Photogrammetric Engineering & Remote Sensing. 84(7): 459-468, July 2018.

3. Haohan Li, Yunxiang Mao, Zhaozheng Yin, and Yingke Xu, “A Hierarchical Convolutional Neural Network for Vesicle Fusion Event Classification,” Journal of Computerized Medical Imaging and Graphics. Elsevier. Vol 60: 22-34, September 2017.

2. Haohan Li, Zhaozheng Yin and Yingke Xu, “A Deep Learning Framework for Automated Vesicle Fusion Detection,” IEEE International Symposium on Biomedical Imaging (ISBI), 2017.

1. Haohan Li, Zhaozheng Yin and Yingke Xu, “A Gaussian Mixture Model for Automated Vesicle Fusion Detection and Classification,” the 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) workshop on Computational Methods for Molecular Imaging (CMMI), 2015.

 

Mingzhong Li

Now at Google

Ph.D., Computer Science, Missouri S&T, 09/2012 – 05/2016

B.S., South China University of Technology, 2011

Internship: Siemens

 

Papers

6. Mingzhong Li and Zhaozheng Yin, “Debugging Object Tracking by a Recommender System with Correction Propagation,” IEEE Transaction on Big Data. 3(4): 429-442, December 2017.

5. Nolan Ferral, Kyara Holloway, Mingzhong Li, Zhaozheng Yin, and Chen Hou, “Heterogeneous Activity Causes a Nonlinear Increase in the Group Energy Use of Ant Workers Isolated from Their Social Environment,” Insect Science. DOI: 10.1111/1744-7917.12433. 2017.

4. Mingzhong Li and Zhaozheng Yin, “Cell Segmentation using Stable Extremal Regions in Multi-exposure Microscopy Images,” IEEE International Symposium on Biomedical Imaging (ISBI), 2016.

3. Mingzhong Li and Zhaozheng Yin, “Co-restoring Multimodal Microscopy Images,” the 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015

2. Mingzhong Li and Zhaozheng Yin, “Debugging Object Tracking Results by a Recommender System with Correction Propagation,” Asian Conference on Computer Vision (ACCV) workshop on User-Centered Computer Vision (UCCV), 2014.

1. Mingzhong Li, Zhaozheng Yin, Matthew Thimgan, and Ruwen Qin, “Track Fast-moving Tiny Flies by Adaptive LBP Feature and Cascaded Data Association,” IEEE Intl. Conf. on Image Processing (ICIP), 2013.

 

Award and Honor

3. The 3rd Best Poster Award in the research poster competition, Computer Science, April 2016.

2. The 3rd Best Poster Award in the Computer Science research poster competition, April 2015.

1. The second Best Paper Award in the ISC graduate research symposium, April 2013.

 

Yunxiang Mao

Now at 12 Sigma Inc.

Ph.D., Computer Science, 09/2012 - 03/2018

B.S., Electrical Engineering, University of Electronic Science and Technology of China, 2012

 

Internship: Siemens


Papers

7. Yunxiang Mao, Liang Han, and Zhaozheng Yin, “Cell Mitosis Event Analysis in Phase Contrast Microscopy Images Using Deep Learning,” Medical Image Analysis (MedIA). 57: 32-43, 2019. 

6. Yunxiang Mao and Zhaozheng Yin, “Two-Stream Bidirectional Long Short-Term Memory for Mitosis Event Detection and Stage Localization in Phase-Contrast Microscopy Images,” the 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017.

5. Yunxiang Mao and Zhaozheng Yin, “A Hierarchical Convolutional Neural Network for Mitosis Detection in Phase-Contrast Microscopy Images,” the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016.

4. Yunxiang Mao, Zhaozheng Yin and Joseph M. Schober, “A Deep Convolutional Neural Network Trained on Representative Samples for Circulating Tumor Cell Detection,” IEEE Winter Conference on Applications of Computer Vision (WACV), 2016.

3. Yunxiang Mao, Zhaozheng Yin and Joseph M. Schober, “Iteratively Training Classifiers for Circulating Tumor Cell Detection,” IEEE International Symposium on Biomedical Imaging (ISBI), 2015.

2. Yunxiang Mao and Zhaozheng Yin, “Training a Scene-Specific Pedestrian Detector Using Tracklets,” IEEE Winter Conference on Applications of Computer Vision (WACV), 2015.

1. Yunxiang Mao, Haohan Li, and Zhaozheng Yin, “Who Missed the Class? – Unifying Multi-face Detection, Tracking and Recognition in Videos,” IEEE International Conference on Multimedia & Expo (ICME), 2014.

 

Award and Honor

5. Best Poster Award in the research poster competition, Computer Science, April 2016.

4. NSF I-Corps Entrepreneurial Lead, 2015.

3. ICME Doctoral Consortium participant, July 2014.

2. The Best Poster Award in the Computer Science research poster competition, April 2014.

1. The 2nd Best Poster Award in the ISC poster competition, November 2013.

 

Srinivas Thandu

Now at Amazon

Ph.D., Computer Science, 01/2012 – 05/2016

(Dr. Sriram Chellappan as the Co-Advisor)

 

Paper:

2. Srinivas Thandu, Pratool Bharti, Sriram Chellappan, Zhaozheng Yin, “Leveraging Multi-modal Smartphone Sensors for Ranging and Estimating the Intensity of Explosion Events,” Pervasive and Mobile Computing. Elsevier. Vol 40: 185-204. September 2017.

1. Srinivas Thandu, Sriram Chellappan and Zhaozheng Yin, “Ranging Explosion Events Using Smartphones,” the 11th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2015.

 

Award and Honor:

1. The 2nd Best Paper Award in the Intelligent System Center graduate research symposium, April 2016.

 

Tianyi Zhao

Now at Aibee

Ph.D. student, Computer Science, 09/2017 – 02/2022

M.S., Computer Science. UNC at Charlotte, 2016

B.S., Software Engineering. Xiamen University, 2015

 

Internship: 12 Sigma Technologies Inc., San Diego, 05/2018-08/2018; PAII Inc. Washing DC, 05/2020-12/2020

 

Papers

6. Tianyi Zhao, and Zhaozheng Yin, “Airway Anomaly Detection by Prototype-based Graph Neural Network,” the 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

5. Tianyi Zhao, Kai Cao, Jiawen Yao, Isabella Nogues, Le Lu, Lingyun Huang, Jing Xiao, Zhaozheng Yin, and Ling Zhang, “3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

4. Tianyi Zhao, and Zhaozheng Yin, “Weakly Supervised Cell Segmentation by Point Annotation,” IEEE Transactions on Medical Imaging (TMI). 2020. (Impact Factor: 9.710). Accepted.

3. Tianyi Zhao, Zhaozheng Yin, Jiao Wang, Dashan Gao, Yunqiang Chen, and Yunxiang Mao. “Bronchus Segmentation and Classification by Neural Networks and Linear Programming,” the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

2. Tianyi Zhao and Zhaozheng Yin, “Pyramid-based Fully Convolutional Networks for Cell Segmentation,” the 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018

1. Tianyi Zhao, Dashan Gao, Jiao Wang, and Zhaozheng Yin, “Lung Segmentation in CT Images Using a Fully Convolutional Neural Network with Multi-instance and Conditional Adversary Loss,” IEEE International Symposium on Biomedical Imaging (ISBI), 2018.

 

Award and Honor

1. NIH Student Paper and Travel Award in ISBI2018 (10 out of 625 submissions).

 

Graduated M.S. students:

Haohan Li

M.S., Computer Science, 09/2013 – 05/2015

B.S., South China University of Technology, 2011

 

Paper

1. Haohan Li, Zhaozheng Yin and Yingke Xu, “A Gaussian Mixture Model for Automated Vesicle Fusion Detection and Classification, the 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) workshop on Computational Methods for Molecular Imaging (CMMI), 2015.

Wei Luo

Now at Amazon

M.S. student, Computer Science, 09/2016 – 05/2018

B.S., Software Engineering, Northeast University, China, 2016

 

Graduated Undergraduate students:

Roshan Kenia

M.S. at Columbia University, 08/2023 ~

B.S., Computer Science, 05/2023

Undergraduate Researcher, 01/2022 – 08/2023

Benjamin Ryherd

Mechanical Engineering

Undergraduate student, 2013-2015

Chris Seto

Computer Science

Undergraduate student, 2012-2016