Current PhD students (sorted by last names)
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Shreya Biswas Ph.D. Student, Computer
Science, 08/2023 – now B.S., Jadavpur University, 2019-2023 1.
Shreya
Biswas, and Zhaozheng Yin, “Mitigating
Pose-Scale Discrepancy Bias and Reforming Multi-Support Reasoning for
Few-Shot Semantic Segmentation,” the 19th European Conference on
Computer Vision (ECCV), 2026. 2.
Shreya
Biswas, and Zhaozheng Yin, “DOTGraph: CLIP-Driven Feature Disentanglement and Optimal
Transport based Graph Learning for Few-Shot Segmentation,” IEEE/CVF
Winter Conference on Applications of Computer Vision (WACV), 2026. |
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Jamalia Sultana Ph.D. student, Computer Science, 10/2023 – now M.S., Bangladesh University of Engineering and Technology,
2021-2023 B.S., Bangladesh University of Engineering and Technology,
2016-2021 1.
Jamalia
Sultana, Ruwen Qin, and Zhaozheng
Yin, “RadGaze-LLM: Anatomical Region-Grounded
Radiology Report Generation via Learning from Expert Gaze,” IEEE
International Symposium on Biomedical Imaging (ISBI), 2026. 2.
Jamalia
Sultana, Ruwen Qin, and Zhaozheng
Yin, “Seeing Through Expert’s Eyes: Leveraging Radiologist Eye
Gaze and Speech Report with Graph Neural Networks for Chest X-ray Image
Classification,” the 17th Asian Conference on Computer Vision (ACCV),
2024. |
Graduated Ph.D. students (sorted by last names):
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Hritam Basak Now at Amazon Robotics, California Ph.D., Computer Science, 09/2022 – 05/2026 B.S., Jadavpur University, 2017-2021 Internship: Amazon Robotics 2024, 2025 Papers 1.
Hritam Basak, Hadi Tabatabaee, Xin Yang, Shreekant
Gayaka, Nan Qiao, Yuyin Sun, Cheng-Hao
Kuo, Zhaozheng Yin, and Min Sun, “Exo2EgoPolicy: Pose-Aligned
Cross-View Policy Learning,” the 19th European Conference on
Computer Vision (ECCV), 2026. 2.
Hritam Basak, and Zhaozheng Yin, “Fixed Reality, Diffused
Possibility: Disentangling Stochastic and Deterministic Latent for Cluttered
Grasping,” the 19th European Conference on Computer Vision (ECCV),
2026. 3.
Hritam Basak, and Zhaozheng Yin, “PhysioSplat:
Physics-Informed Dynamic Gaussian Splatting for Surgical Scene
Reconstruction,” the 29th International Conference on Medical Image
Computing and Computer Assisted Intervention (MICCAI), 2026. 4.
Hritam Basak, and Zhaozheng Yin, “VisPLA:
Visual Iterative Self-Prompting for Language-Guided 3D Affordance
Learning,” the 39th Annual Conference on Neural
Information Processing Systems (NeurIPS),
2025. 5.
Hritam Basak, and Zhaozheng Yin, “D^4Recon: Dual-stage
Deformation and Dual-scale Depth Guidance for Endoscopic
Reconstruction,” the 28th International Conference on Medical Image
Computing and Computer Assisted Intervention (MICCAI), 2025. 6.
Hritam Basak, Hadi Tabatabaee, Shreekant Gayaka, Ming-Feng Li,
Xin Yang, Cheng-Hao Kuo, Arnab Sen, Min Sun, and Zhaozheng Yin,
“Enhancing Single Image to 3D Generation using Gaussian Splatting and
Hybrid Diffusion Priors,” IEEE/RSJ
International Conference on Intelligent Robots and Systems (IROS),
2025. 7.
Hritam Basak, and
Zhaozheng Yin, “SemiDAViL: Semi-supervised
Domain Adaptation with Vision-Language Guidance for Semantic
Segmentation,” IEEE/CVF Conference on Computer Vision and Pattern
Recognition (CVPR), 2025. 8.
Hritam Basak, and Zhaozheng Yin, “Forget More to Learn
More: Domain-specific Feature Unlearning for Semi-supervised and Unsupervised
Domain Adaptation,” the 18th European Conference on Computer Vision (ECCV),
2024. 9.
Hritam Basak, and Zhaozheng Yin, “Quest for Clone:
Test-time Domain Adaptation for Medical Image Segmentation by Searching the
Closest Clone in Latent Space,” the 27th International Conference on
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2024. 10. 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. 11. 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. Award and Honor 1. Outstanding Reviewer of CVPR2025 2. IEEE SPS Scholarship, 2024 3. ECCV DEI Award, 2024 (58 out of 524 applications). 4. MICCAI NIH Travel Award, 2024 5. IEEE SPS
Scholarship, 2023 |
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Jianxiang Dong Now at ByteDance, California Ph.D. student, Computer Science, 09/2020 – 04/2026 M.S., George Washington University, 2018-2020 B.S., Northeastern University, 2014-2018 Papers 1.
Jianxiang Dong, and Zhaozheng Yin, “Annotation-efficient
Hybrid Learning for Temporal Sentence Grounding,” IEEE Transactions
on Circuits and Systems for Video Technology (TCSVT). 36(2):
2594-2606, February 2026. 2.
Jianxiang Dong, and Zhaozheng Yin, “Weakly
Semi-supervised Temporal Sentence Grounding in Videos with Point
Annotations," IEEE Transactions on Multimedia (TMM).
28:2268-2278. January 2026. 3.
Jianxiang
Dong, Zhaozheng Yin, Herbert J. Bernstein, and Jean
Jakoncic, “Content-Aware Image Compression Model for
Macromolecular Crystallography Data,” IEEE
International Symposium on Biomedical Imaging (ISBI), 2026. 4.
Jianxiang Dong, and Zhaozheng Yin, “Graph-based Dense
Event Grounding with Relative Positional Encoding,” Computer Vision
and Image Understanding (CVIU). 251:104257. February 2025. 5.
Jianxiang
Dong, Zhaozheng Yin, Dale Kreitler, Herbert J.
Bernstein, and Jean Jakoncic, “Bragg Spot Finder (BSF): A New
Machine-Learning Aided Approach to Deal with Spot Finding for Rapidly
Filtering Diffraction Pattern Images,” Journal of Applied Crystallography.
2024. 6.
Jianxiang
Dong, and Zhaozheng Yin, “Boundary-aware Temporal
Sentence Grounding with Adaptive Proposal Refinement,” the 16th
Asian Conference on Computer Vision (ACCV), 2022. |
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Liang Han 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. (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. (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. |
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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. |
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Muhammad Monjurul Karim (Co-supervised with
Dr. Qin) Now Post-doc at
University of Washinton Ph.D. student, Civil
Engineering, 2020-2023 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).
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. |
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Haohan Li Now at Xsense.ai 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. |
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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. |
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Yunxiang Mao Now at Xsense.ai Ph.D., Computer Science, 09/2012
- 03/2018 B.S., Electrical Engineering, University of Electronic Science and
Technology of China, 2012 Internship: Siemens
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. |
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Md. Moniruzzaman Ph.D. student, Computer Science,
01/2017 – 10/2024 B.S., Electronics and
Communication Engineering, Khulna University of Engineering & Technology
(KUET), Bangladesh 2014 Papers 1. Md Moniruzzaman, and Zhaozheng Yin, “Progressive Knowledge
Distillation from Different Levels of Teachers for Online Action
Detection,” IEEE Transactions on Multimedia (TMM). 2024. 2.
Md Moniruzzaman,
Zhaozheng Yin, Md Hossain, Hwan Choi, and Zhishan
Guo, “Wearable Motion Capture: Reconstructing and Predicting 3D Human
Poses from Wearable Sensors,” IEEE Journal of Biomedical and Health
Informatics (J-BHI). 27(11): 2168-2208. November 2023. 3.
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).
April 2023. (Impact Factor: 5.859) 4.
Md Moniruzzaman,
and Zhaozheng Yin, “Feature Weakening, Contextualization, and
Discrimination for Weakly Supervised Temporal Action Localization,” IEEE
Transactions on Multimedia (TMM). March 2023. (Impact Factor: 8.812) 5.
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).
December 2022. (Impact Factor: 5.859) 6.
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) 7.
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. 8.
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. |
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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. |
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Tianyi Zhao Now at Google. 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). 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). |
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Graduated M.S. students:
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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. |
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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:
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Roshan
Kenia Ph.D., at Harvard University, 09/2025
~now M.S. at Columbia University,
08/2023- 07 /2025 B.S., Computer Science, 05/2023 Undergraduate Researcher,
01/2022 – 08/2023 Paper 1.
Roshan Kenia, Jihane Mendil, Ahmed Jasim, Muthanna Al-Dahhan, and Zhaozheng Yin, “Robust TRISO-Fueled
Pebble Identification by Digit Recognition,” IEEE/CVF Winter Conference
on Applications of Computer Vision (WACV), 2024. |
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Benjamin
Ryherd Mechanical Engineering Undergraduate student, 2013-2015 |
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Chris Seto Computer Science Undergraduate student, 2012-2016 |