Yining Jiao

About Me

I am a Postdoctoral Researcher at the Department of Neurological Surgery, UC San Diego. I received my Ph.D. in Computer Science from the Biomedical Image Analysis Group (BIAG), UNC-Chapel Hill in 2025, advised by Prof. Marc Niethammer. Previously, I received my M.Sc. degree from the School of Biomedical Engineering, Shanghai Jiao Tong University in 2020, under the supervision of Prof. Qian Wang in the Medical Imaging Computing (MIC) Lab. Before that, I received my B.Eng. degree from Honors College at Northwestern Polytechnical University in 2017.

Research Highlights

I build AI that knows what it knows — and recognizes what it doesn't. My research focuses on spatiotemporal representation learning, with a dedication to interpretability and uncertainty quantification within the healthcare domain. My research revolves around three questions:

Learning to see shapes — advanced techniques for image and geometry processing.
Learning to model populations — representing how anatomical shapes vary and evolve.
Learning to say "I don't know" — statistical machine learning for robust uncertainty quantification.

News

[2026/02] Our paper PRISM on uncertainty-aware shape modeling is now available as preprint.
[2026/02] I joined UC San Diego as a Postdoctoral Researcher.
[2025/12] I defended my PhD dissertation at UNC-Chapel Hill!

Selected Publications

PRISM: A 3D Probabilistic Neural Representation for Interpretable Shape Modeling

Yining Jiao, Sreekalyani Bhamidi, Carlton Zdanski, Julia Kimbell, Andrew Prince, Cameron Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, Jisan Mahmud, Marc Niethammer

preprint

paper

LucidAtlas: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations

Yining Jiao, Sreekalyani Bhamidi, Carlton Zdanski, Huaizhi Qu, Julia Kimbell, Andrew Prince, Cameron Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, Jisan Mahmud, Tianlong Chen, Marc Niethammer

preprint

paper

NAISR: A 3D Neural Additive Model for Interpretable Shape Representation

Yining Jiao, Carlton Zdanski, Julia Kimbell, Andrew Prince, Cameron Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, William Dunn, Jisan Mahmud, Marc Niethammer

ICLR 2024. Spotlight, top 5%.

project video paper code

cuRadiomics: A GPU-Based Radiomics Feature Extraction Toolkit

Yining Jiao, Oihane Mayo Ijurra, Lichi Zhang, Dinggang Shen, Qian Wang

MICCAI Workshop on Radiomics and Radiogenomics in Neuro-oncology using AI. Oral, top 10 of submissions.

paper code

iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images

Qin Liu, Zhenlin Xu, Yining Jiao, Marc Niethammer

MICCAI 2022.

paper code

Intracluster Structured Low-Rank Matrix Analysis Method for Hyperspectral Denoising

Wei Wei, Lei Zhang, Yining Jiao, Chunna Tian, Cong Wang, Yanning Zhang

IEEE Transactions on Geoscience and Remote Sensing

paper code

Honors & Awards

[2021] ICML Workshop on Computational Biology Fellowship.
[2020] Outstanding Graduate of Shanghai (only 4 from department).
[2019] SJTU Excellent Graduate Student Award (only 2 from department).
[2017] Excellent Undergraduate Thesis in NWPU.

Research Experiences

Department of Neurological Surgery, UC San Diego Feb 2026 – Present

Postdoctoral Researcher

Topics: Individualized Spatiotemporal Learning, Uncertainty Quantification for Shapes.

Biomedical Image Analysis Group (BIAG), UNC-Chapel Hill Jan 2021 – Dec 2025

Ph.D. Student, advised by Prof. Marc Niethammer

Topics: Pediatric Airway Shape Analysis, Airway OCT Analysis, Interpretable and Uncertainty-Aware Spatiotemporal Learning for Healthcare.

Medical Imaging Computing (MIC) Lab, Shanghai Jiao Tong University Sep 2017 – Mar 2020

M.Sc. Student, advised by Prof. Qian Wang

Topics: GPU-Accelerated Radiomics, Data Science for Cancer Research.

Shaanxi Provincial Key Lab of Speech & Image Information Processing May 2016 – Jun 2017

Student Researcher

Topics: Convex Optimization for Hyperspectral Image Denoising.

Academic Services

Conference Reviews: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AISTATS, AAAI, MICCAI.

Journal Reviews: IEEE TPAMI, IEEE JBHI, Neural Networks.

Fun Facts About Me

Outside of research, I practice Tarot de Marseille and create knowledge-sharing content about tarot reading on Bilibili. My favorite tarot readers are Alejandro Jodorowsky and Camelia Elias. Feel free to reach out if you're interested!

I enjoy gardening — especially growing roses.

I also write poems. I was invited to the Chinese Poetry New Discovery Poetry Camp in 2018 as one of twelve selected campers, and some of my works have been published in Poetry Periodical (《诗刊》), Chinese Poetry (《中国诗歌》), among others.