Biography
I am a final-year Ph.D. student at Clemson University. I am primarily focused on studying computer vision and deep learning, with a particular emphasis on image quality assessment, self-supervised learning, semi-supervised learning, multi-modality learning, and foundational models.
I am open to full-time positions or research internships starting in Fall 2024 or in 2025.
Interests
- Self/semi-supervised learning
- Multi-modality learning
- 3D Detection/segmentation
- Foundation models
Education
PhD in Computer Vision, 2020-Present
Clemson University
MS in Electrical and Computer Engineering, 2018-2020
The Ohio State University
BSc in Automation, 2014-2018
Northeastern University, China
Recent Publications
(2024).
Zero-shot 3D Semantic Segmentation via Learning from Zero-shot Labels.
In Submission.
(2023).
Point Cloud Self-supervised Learning via 3D to Multi-view Masked Autoencoder.
In Submission.
(2023).
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models.
In NeurIPS, 2023.
(2022).
Class-Level Confidence Based 3D Semi-Supervised Learning.
In WACV, 2023.
(2021).
Multimodal Semi-Supervised Learning for 3D Objects.
In BMVC, 2021.
Experience
Applied Scientist Intern
Amazon
- Leveraging foundation models for pre-training in image quality assessment tasks.
Research Intern
Honda Research Institute
- Working on 3D occupancy forecasting using generative cellular automata.
Research Assistant
- Self/Semi-supervised learning
- 3D classification/detection/segmentation
Contact
- zhiminc@clemson.edu
- 4 Research Drive, Greenville, SC 29607