News

  • May 2026 NewOur paper Distilling Photon-Counting CT into Routine Chest CT through Clinically Validated Degradation Modeling received an early accept at MICCAI 2026.

Active projects

AutoMedBench UC Santa Cruz × NVIDIA · 2026–present
Towards medical AutoResearch
  • A benchmark that puts a base LLM in the driver's seat across the full automated research pipeline: planning, setup, validation, inference, submission.
  • Five research categories — segmentation, enhancement, VQA, report, detection. 7 models; 2,000+ runs; two-container isolation.
Website GitHub
OpenVAE UCSC × UCSF × Johns Hopkins × NVIDIA · 2025–present
Scaling latent backbones with worldwide data
  • Pretrained 2D and 3D KL-VAE / VQ-VAE backbones for CT and MRI volumes.
  • Trained on 400,000+ CTs collected from 145 hospitals worldwide; used as drop-in priors for downstream medical generative work.
GitHub Hugging Face

Publications

  • Distilling Photon-Counting CT into Routine Chest CT through Clinically Validated Degradation Modeling. Junqi Liu, Xinze Zhou, Wenxuan Li, et al. · MICCAI 2026 (early accept) · arxiv.org/abs/2604.07329
  • See More, Change Less: Anatomy-Aware Diffusion for Contrast Enhancement. Junqi Liu et al. · arXiv preprint, 2026 · arxiv.org/abs/2512.07251
  • ShapeKit: Shape-Aware Postprocessing for Organ Segmentation. Junqi Liu et al. · MICCAI 2025 · arxiv.org/abs/2506.24003
  • AI-Powered Translation Tool to Enable Contrast-Aware CT Synthesis. Junqi Liu et al. · RSNA 2025 · github.com/MrGiovanni/SMILE
  • Towards Robust Out-of-Distribution Generalization via Bayesian Optimization. Junqi Liu et al. (first author) · tempmpm.readthedocs.io

Experience

Research Scholar — Johns Hopkins, CCVL 2025 – Mar 2026
Advised by Prof. Alan Yuille (Bloomberg Distinguished Professor)
  • SMILE — anatomy-aware diffusion for CT contrast enhancement. ~50% FID gain, ~10% F1 lift on early tumor detection. CVPR 2026 (under review).
  • ShapeKit — shape-aware postprocessing for organ segmentation. >10% average DSC improvement. MICCAI 2025.
SMILE ShapeKit Model Dataset
Research Intern — Kermen Lab, UCPH Oct 2024 – May 2025
Neuroscience Department · advised by Prof. Florence Kermen
  • Designed ZATA-1.5B, a multi-attention zebrafish tracking model with transformer backbones for fine-grained behavior — ~80% sensitivity, ~90% specificity.
  • Manuscript in preparation (PNAS).
Code
Quantitative Research Intern — Shanghai Quantinv Mar – Aug 2024
Investment & Decision Team · return offer
  • Designed QuantNet-6B, an attention-based factor model with transformer backbones — 180% excess return at 20% maximum drawdown.
Algorithm Research Intern — Shanghai AI Lab Oct 2022 – Oct 2023
Advised by Prof. Nanyang Ye, SJTU
  • Parallelized Bayesian optimization for interpretable deep models — +50% accuracy at −90% runtime. First-author publication.
Docs