Bangwei Guo

I am a Ph.D. candidate in Computer Science at Rutgers University, advised by Distinguished Professor Dimitris N. Metaxas. Previously, I received my M.S. in Applied Statistics and B.S. in Mathematics from the University of Science and Technology of China (USTC).

My research lies at the intersection of vision-language models, large language models, and computer vision, with a strong emphasis on medical imaging. I develop generalizable and adaptive multimodal systems for visual understanding, reasoning, and interaction—spanning universal and interactive medical image segmentation, in-context learning, and agent-based vision systems. My long-term goal is to build scalable AI that unifies perception, language, and reasoning, and transfers effectively across tasks, modalities, and data distributions.

I am currently a research intern at NEC Laboratories America, where I work on large multimodal models and multi-agent systems for structured reasoning and complex information extraction. I am actively seeking Fall 2026 / Summer 2027 internships and 2027 full-time opportunities in computer vision, medical imaging, and large language / multimodal models.

experience

2026.5 – 2026.8

Research Intern United Imaging Intelligence, America · Boston, MA

Building a cardiac clinical-diagnosis system powered by vision-language models (VLMs) and LLM agents.

2025.8 – Present

Collaboration Research Intern NEC Laboratories America · Princeton, NJ

Working on large multimodal models and multi-agent systems for structured reasoning and complex information extraction.

2023.9 – Present

Research Assistant Rutgers University · Piscataway, NJ

2020.9 – 2023.6

Research Assistant University of Science and Technology of China · Anhui, China

news

May 26, 2026	💼 I started my research internship at United Imaging Intelligence in Boston, MA, focusing on VLM and AI Agent.
May 11, 2026	🎉 One paper has been accepted to ICML2026. Congratulations to all collaborators!
Jan 26, 2026	🎉 Our paper K-Prism has been accepted to ICLR2026. Congratulations to all collaborators!
Aug 01, 2025	💼 I started my part-time research internship at NEC Laboratories America in Princeton, New Jersey, focusing on the VLM reasoning and image understanding.
May 25, 2025	I will attend IPMI2025 in Kos, Greece.

selected publications

ICML

All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs

Xi Chen, Mingyu Jin, Jingcheng Niu, Yutong Yin, Jinman Zhao, Bangwei Guo, Dimitris N. Metaxas, Zhaoran Wang, Yutao Yue, and Gerald Penn

In International Conference on Machine Learning (ICML), 2026

arXiv Bib PDF Code

@inproceedings{chen2026all,
  title = {All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs},
  author = {Chen, Xi and Jin, Mingyu and Niu, Jingcheng and Yin, Yutong and Zhao, Jinman and Guo, Bangwei and Metaxas, Dimitris N. and Wang, Zhaoran and Yue, Yutao and Penn, Gerald},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
}

ICLR

K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Model

Bangwei Guo, Yunhe Gao, Meng Ye, Difei Gu, Yang Zhou, Leon Axel, and Dimitris Metaxas

In International Conference on Learning Representations (ICLR), 2026

arXiv Bib PDF Code

@inproceedings{guo2025k,
  title = {K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Model},
  author = {Guo, Bangwei and Gao, Yunhe and Ye, Meng and Gu, Difei and Zhou, Yang and Axel, Leon and Metaxas, Dimitris},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
}

IPMI

Verse: Integrating multiple queries as prompts for versatile cardiac mri segmentation

Bangwei Guo, Meng Ye, Yunhe Gao, Bingyu Xin, Leon Axel, and Dimitris Metaxas

In International Conference on Information Processing in Medical Imaging, 2025

Bib PDF Code

@inproceedings{guo2025verse,
  title = {Verse: Integrating multiple queries as prompts for versatile cardiac mri segmentation},
  author = {Guo, Bangwei and Ye, Meng and Gao, Yunhe and Xin, Bingyu and Axel, Leon and Metaxas, Dimitris},
  booktitle = {International Conference on Information Processing in Medical Imaging},
  pages = {373--387},
  year = {2025},
  organization = {Springer},
}

CMIG

A robust and lightweight deep attention multiple instance learning algorithm for predicting genetic alterations

Bangwei Guo, Xingyu Li, Miaomiao Yang, Hong Zhang, and Xu Steven Xu

Computerized Medical Imaging and Graphics, 2023

Bib PDF

@article{guo2023robust,
  title = {A robust and lightweight deep attention multiple instance learning algorithm for predicting genetic alterations},
  author = {Guo, Bangwei and Li, Xingyu and Yang, Miaomiao and Zhang, Hong and Xu, Xu Steven},
  journal = {Computerized Medical Imaging and Graphics},
  volume = {105},
  pages = {102189},
  year = {2023},
  publisher = {Elsevier},
}

J Path CR

Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: achieving state-of-the-art predictive performance with fewer data using swin transformer

Bangwei Guo, Xingyu Li, Miaomiao Yang, Jitendra Jonnagaddala, Hong Zhang, and Xu Steven Xu

The Journal of Pathology: Clinical Research, 2023

Bib PDF Code

@article{guo2023predicting,
  title = {Predicting microsatellite instability and key biomarkers in colorectal cancer from H\&E-stained images: achieving state-of-the-art predictive performance with fewer data using swin transformer},
  author = {Guo, Bangwei and Li, Xingyu and Yang, Miaomiao and Jonnagaddala, Jitendra and Zhang, Hong and Xu, Xu Steven},
  journal = {The Journal of Pathology: Clinical Research},
  volume = {9},
  number = {3},
  pages = {223--235},
  year = {2023},
  publisher = {Wiley Online Library},
}