Embedded Files
About Me
About Me
I am a Research Scientist at Bosch AI Research. I received my Ph.D. in Computer Science and Engineering from The Ohio State University, co-advised by Professor Han-Wei Shen and Professor Wei-Lun (Harry) Chao, and my B.S. in Computer Science from the University of Minnesota, Twin Cities.
My doctoral research centered on developing visual analytics techniques to interpret Federated Learning and Continual Learning processes, as well as designing dimensionality reduction methods tailored for federated environments. I also explored AI-driven solutions for scientific applications, including medical imaging, remote sensing, and high-fidelity surrogate models for large-scale scientific simulations using implicit neural representations and 3D/4D Gaussian splatting. At Bosch, I develop machine learning and foundation model methods for autonomous driving.
Featured Projects and Publications
Featured Projects and Publications
Federated Learning
Federated Learning
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction
Ziwei Li, Xiaoqi Wang, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao
In NeurIPS 2024
On the Importance and Applicability of Pre-training for Federated Learning
Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han-Wei Shen, Wei-Lun Chao
In ICLR 2023
Understanding Federated Learning through Loss Landscape Visualizations: A Pilot Study
Ziwei Li, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao
In NeurIPS Workshop on Federated Learning: Recent Advances and New Challenges, 2022
Continual Learning
Continual Learning
Visual Analytics on Network Forgetting for Task-Incremental Learning
Ziwei Li, Jiayi Xu, Wei-Lun Chao, Han-Wei Shen
In Computer Graphics Forum (Proc. EuroVis 2023)
3D
3D
GS-Surrogate: Deformable Gaussian Splatting for Parameter Space Exploration of Ensemble Simulations
Ziwei Li*, Rumali Perera*, Angus G. Forbes, Kenneth Moreland, David Pugmire, Scott Klasky, Wei-Lun Chao, Han-Wei Shen
Under Review
FA-INR: Adaptive Implicit Neural Representations for Interpretable Exploration of Simulation Ensembles
Ziwei Li, Yuhan Duan, Tianyu Xiong, Yi-Tang Chen, Wei-Lun Chao, Han-Wei Shen
In IEEE Transactions on Visualization and Computer Graphics (TVCG) 2026
3D Semantic Trajectory Reconstruction from 3D Pixel Continuum
Jae Shin Yoon, Ziwei Li, Hyun Soo Park
In CVPR 2018
AI for Medical Imaging and Remote Sensing
AI for Medical Imaging and Remote Sensing
Super-resolution Deep Neural Networks for Water Classification from Free Multispectral Satellite Imagery
Ziwei Li, Wei Ji Leong, Michael Durand, Ian Howat, Kylie Wadkowski, Bidhyananda Yadav, Joachim Moortgat
In Journal of Hydrology 626, 130248
Deep Learning Models for River Classification at Sub-meter Resolutions from Multispectral and Panchromatic Commercial Satellite Imagery
Joachim Moortgat, Ziwei Li, Michael Durand, Ian Howat, Bidhyananda Yadav, Chunli Dai
In Remote Sensing of Environment 282, 113279
Artificial Intelligence-assisted Automated Prediction of Advanced Neoplasia in IPMNs: A Functional Model
Ziwei Li, Erica Park, Wei-Lun Chao, Stacey Culp, Phil Hart, Wei Chen, Daniel Jones, Zarine Shah, Timothy Pawlik, Somashekar Krishna
In Gastrointestinal Endoscopy, Volume 99, Issue 6, June 2024, AB7
Artificial Intelligence Advances Digital Pathomics for Confocal Endomicroscopy Diagnosis of Pancreatic Cysts
Ahmed Abdelbaki, Ziwei Li, Tai-Yu Pan, Justin Lee, Arpita Chowdhury, et al.
In Techniques and Innovations in Gastrointestinal Endoscopy, Volume 27, Issue 3, 2025, 250924
Somashekar G Krishna, Ahmed Abdelbaki, Ziwei Li, Stacey Culp, et al.
In Pancreatology, Volume 25, Issue 5, August 2025, Pages 658–666
Assistive AI for Coping with Memory Loss
Libby Ferland, Ziwei Li, Shridhar Sukhani, Joan Zheng, Luyang Zhao, Maria Gini
In AAAI Workshop on Health Intelligence, 2018
Page updated
Google Sites
Report abuse