Jinglun Y.

PhD Candidate @JohnsHopkins | Researcher @jhuioiv | Focused on Medical Image Analysis, Optical Imaging, and Vision-Guided Surgery

[SASHIMI Workshop @ MICCAI 2026 @SashimiWorkshop]

Call for papers! Deadline is June 25th!
https://t.co/FqhX2IRQ7l #MICCAI2025 #SASHIMI2025

[Jack Jingyu Zhang @jackjingyuzhang]

Please read more in our preprint & upvote if you like it: https://t.co/UB9KyPvuH0

Many thanks to my amazing collaborators Jiacan Yu, @ruyimarone, @DanielKhashabi, @ben_vandurme! Work done at @jhuclsp @JHUCompSci.

[ARPA-H @ARPA_H]

Let’s explore how we can work together to catalyze health breakthroughs at #BIO2025 in Boston! Learn more⬇️

Express your interest by June 10: https://t.co/Dy9eVILQ9U

Explore our sessions: https://t.co/8MPMWOjvXk

[Vishal Patel @vishalm_patel]

🚨Excited to share that the JHU VIU Lab will be presenting the following papers at CVPR next week, including 3 Highlights! 🎉
Come stop by our posters and say hi — we’d love to connect! 👋
#CVPR2025 @JHUCompSci @JHUECE @HopkinsDSAI @HopkinsEngineer

[Vishal Patel @vishalm_patel]

💥 New paper: Think Before You Diffuse

Meet DiffPhy — LLM-guided, physics-aware video diffusion 🎥🧠🌍
SOTA on real-world motion & dynamics!
🔗 https://t.co/1trr2BhPCx

@JHUCompSci @HopkinsDSAI @HopkinsEngineer @myq_1997 #DiffusionModels #VideoGeneration

[Denis Wirtz @deniswirtz]

We introduce InterpolAI, an optical flow-based AI model to enhance 3D imaging (MRI, CODA, ssTEM, light sheet)

Read about it here in our new NM paper: https://t.co/LIpzl3heoB

[Jinglun Y. @fishisworking]

It's truly a pleasure and an honor to be involved in such a well-executed project!

[Stephanie Hicks, PhD @stephaniehicks]

New paper out in @genomeresearch on using contrastive self-supervised learning for spatial domain detection with multi-omics data! Huge congratulations to @JNinnnngg and coauthors Jinglun Yu, Brian Caffo Stephanie Page & @martinowk! 🧬

https://t.co/mSQa5F9oeU

[Jinglun Y. @fishisworking]

@yaningwang511 Congrats!!!

[yaningwang @yaningwang511]

Just dropped on arXiv!
We use diffusion models to recover sharp, high-resolution OCT images from sparse corneal data.
Outperforms UNet. Retains structure.
Imagine real-time surgical imaging—done right.
🔗 https://t.co/6w9XXcryK8
#AI #DiffusionModel #OCT #BiomedicalImaging

[iOIV Lab @jhuioiv]

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🔁 RT to help us find amazing students!
#AIinHealthcare #MedTech #SummerResearch #JHU #Robotics #OCT