Kaibo Tang

Kaibo Tang

he/him

Visiting Student, Massachusetts General Hospital, Harvard Medical School | PhD Student, Department of Electrical and Computer Engineering, Boston University

I recently graduated from UNC Chapel Hill with a Bachelor of Science in Public Health in Biostatistics, a Bachelor of Science in Mathematics, and a minor in Chemistry.

During my time at UNC Chapel Hill, I had worked at the UNC BRAIN Lab in the Biomedical Research Imaging Center (BRIC) as a Research Assistant since September 2021 under the supervision of Dr. Gang Li. My work focuses on developing infant-dedicated deep learning tools for image registration and volumetric atlas construction for the early developing brain.

I previously worked as a Learning Assistant for BIOL 252L: Fundamentals of Human Anatomy and Physiology Laboratory for 4 semesters. I had also been volunteering at the Emergency Department at UNC Hospitals for 2 years since January 2023.

Currently, I am a visiting student at the Advanced MRI Acquisition Lab at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital under the supervision of Dr. Fuyixue Wang and Dr. Zijing Dong. My research focuses on developing deep learning reconstruction and accelerated acquisition methods to achieve fast and robust mesoscale diffusion MRI in vivo. I will be joining Boston University as a Ph.D. student in Electrical Engineering in Fall 2025.

In my free time, I enjoy snowboarding, badminton, cooking Chinese food, and photography.

You may find my CV here: Kaibo’s Curriculum Vitae.

NEWS

2/20/2025 - I was awarded the Trainee Stipend for the 2025 ISMRM & ISMRT Annual Meeting & Exhibition. See y’all in Hawaii :)

1/31/2025 - My abstract on accelerating mesoscale in vivo dMRI was selected for an in-person oral power pitch presentation at the 2025 ISMRM & ISMRT Annual Meeting & Exhibition.

5/21/2024 - MONAI 1.3.1 was released! I contributed three PRs for the release, which added two new modules for image registration task, i.e., VoxelMorph and DiffusionLoss. To try out the latest version of MONAI, please run pip install monai or conda install conda-forge::monai.

5/13/2024 - One co-authored paper was early accepted to MICCAI 2024. Check out the paper here.

4/11/2024 - My paper accepted to IEEE ISBI 2024 was selected as an oral presentation.

2/2/2024 - My first paper as the first author was accepted to IEEE ISBI 2024. Check out the paper, the released code, and the 4D infant brain atlases we generated:

4D Infant Brain Atlases

10/31/2023 - I was inducted into Phi Beta Kappa at UNC Chapel Hill.

3/8/2023 - I was admitted to the Biostatistics (B.S.P.H.) major in Gillings School of Global Public Health.

4/4/2022 - My project, Registering Infant Brain MR Image with Auxiliary Data, was selected for funding by the Summer Undergraduate Research Fellowship (SURF).

EDUCATION

RESEARCH INTERESTS

I have always wanted to improve the health outcomes of patients using my quantitative background. Of course, this is a very broad aim, and it encompasses a wide range of stuff. For example, it involves pushing the resolution and SNR limits of MRI to allow identification of potential biomarkers that are previously inaccessible due to hardware and software limitations; it involves using biostatistics to establish the relationship between these biomarkers and disease progression/prognosis; it also involves developing deep learning tools that assist and accelerate the workflow of radiologists during diagnosis/treatment planning.

Here is a list of areas that I am particularly interested in:

  • Image acquisition and reconstruction
    • Deep learning reconstruction
    • Accelerated acquisition
  • Medical image analysis
    • Volume and surface registrations
    • Atlas construction
    • Cortical surface reconstruction
  • Explainable Deep Learning

PUBLICATIONS

Manuscripts Under Review:

  1. Yanyao Du, Dan Hu, Zhengwang Wu, Ya Wang, Jiahe Wang, Jiale Cheng, Xinrui Yuan, Kaibo Tang, Jun Liu, Karen Grewen, Gang Li. Abnormal Perivascular Space Parameters in Infants with Prenatal Substance Exposure. Under review at Radiology.

  2. Rong Lu, Kaibo Tang, Run Pan, Shangxuan Shi, Xiao’ao Xue, Tingfang Hwang, Yang Song, Weijun Tang, Yue Yu, He Wang, Yao Lu, Ting Lin. The Biological Association Between Programmed Cell Death Function and OA Using Multi-Omic Mendelian Randomization. Under review at eBioMedicine.

  3. Xiuyu Dong, Kaibo Tang, Zhengwang Wu, Dan Hu, Weili Lin, Gang Li. Lifespan Cortical Surface Reconstruction from Thick-Slice Clinical MRI. Under review at MICCAI 2025.

Conference Publications:

  1. Kaibo Tang, Zijing Dong, Lawrence L. Wald, Fuyixue Wang. Accelerated Romer-EPTI using physics-driven, joint x-q attention-network regularized reconstruction for fast mesoscale diffusion MRI. ISMRM 2025 (power pitch).

  2. Xiuyu Dong, Zhangwang Wu, Laifa Ma, Ya Wang, Kaibo Tang, He Zhang, Weili Lin, Gang Li. Cycle-consistent Learning for Fetal Cortical Surface Reconstruction. MICCAI 2024 (early acceptance).

  3. Kaibo Tang, Liangjun Chen, Zhengwang Wu, Fenqiang Zhao, Ya Wang, Weili Lin, Li Wang, Gang Li. Generation of Anatomy-Realistic 4D Infant Brain Atlases with Tissue Maps Using Generative Adversarial Networks. ISBI 2024 (oral).

Journal Publications:

  1. Rong Lu, Tingfang Hwang, Kaibo Tang, Qing Li, Caixia Fu, Ying-Hua Chu, Shangxuan Shi, Tobias Kober, Tom Hibert, Bin Lu, Yiming Li, Yao Lu, Weijun Tang, Lijin Ji. A noninvasive accelerated quantitative MR technique to distinguish drug resistance in prolactinomas: Early results. Biomedical Technology. 2025.

  2. Ruike Chen, Mingyang Li, …, Kaibo Tang, …, Dan Wu. Advances in Magnetic Resonance Imaging of the Developing Brain and its Application in Pediatrics. World Journal of Pediatrics. 2025.

  3. Jiaqi Zhang, Yanyao Du, …, Kaibo Tang, …, Tianzi Jiang. Stage-dependent Neural Mechanisms in Human Methamphetamine Abstinence: Insights from the Digital Twin Brain Model. Biological Psychiatry. 2025.

  4. Rong Lu, Kaibo Tang, Weijun Tang. Editorial for “Improving Accuracy and Repeatability of Cartilage \(T_2\) Mapping in the OAI Dataset through Extended Phase Graph Modeling”. Journal of Magnetic Resonance Imaging. 2025.

AWARDS & HONORS

  1. Accelerated Research Program at UNC Chapel Hill.
  2. Honors Carolina at UNC Chapel Hill.
  3. Summer Undergraduate Research Fellowship (SURF).
  4. Phi Beta Kappa.

TEACHING

  1. Learning Assistant for BIOL 252L: Fundamentals of Anatomy and Physiology Laboratory.