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Jiashuo Zhang

张家硕

Johns Hopkins University
Baltimore, MD, USA
jzhan427 (at) jhu.edu
sethzhangjs (at) gmail.com

About Me

I am a Research Assistant at Johns Hopkins University, advised by Prof. Michael Oberst. I also work part-time as a Machine Learning Engineer at Visilant Inc. I’m primarily interested in how AI can be applied to the biomedical and healthcare sectors. 🤖🧬🏥

I received my M.S. in Computer Science from Johns Hopkins University, where I was fortuned to be advised by Prof. Michael Oberst from the Department of Computer Science and Prof. Kunal Parikh from the School of Medicine. I am also privileged to collaborate with Prof. Liang Zhao from Emory University.

Prior to that, I completed my B.E. with honors in Software Engineering from Shandong University, under the supervision of Prof. Leyi Wei, working on bioinformatics research.

Publications

  1. CHIL
    Revisiting Performance Claims for Chest X-Ray Models Using Clinical Context
    Andrew Wang, Jiashuo Zhang, Michael Oberst
    The 7th Annual Conference on Health, Inference, and Learning · 2026
    TLDR PDF
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    Clinical context is used to provide a more holistic evaluation of current state-of-the-art SOTA models for CXR diagnosis and it is demonstrated that performance degrades when the correlation is broken between prior context and the current CXR label, suggesting that model performance may depend in part on inference of pre-CXR clinical context.
  2. arXiv
    Explainable Cross-Disease Reasoning for Cardiovascular Risk Assessment from LDCT
    Yifei Zhang, Jiashuo Zhang, Mojtaba Safari, Xiaofeng Yang, Liang Zhao
    arXiv preprint · 2025
    TLDR PDF
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    An Explainable Cross-Disease Reasoning Framework is proposed that enables interpretable cardiopulmonary risk assessment from a single LDCT scan, bridging the gap between image-based prediction and mechanism-based medical interpretation.
  3. JCIM
    MucLiPred: Multi-Level Contrastive Learning for Predicting Nucleic Acid Binding Residues of Proteins
    Jiashuo Zhang, Ruheng Wang, Leyi Wei
    Journal of Chemical Information and Modeling · 2024
    TLDR PDF CODE
    Powered by Semantic Scholar
    A novel deep learning model equipped with a dual contrastive learning mechanism aimed at improving the prediction of multiple molecule-protein interactions and the identification of potential molecule-binding residues, which represents a significant advancement in protein-molecule interaction prediction.

Presentations & Talks

  1. Guideline and Evidence-Based Shared Decision-Making: Healthcare Knowledge Q&A System
    Jiashuo Zhang, Erik Skalnes, Yvonne Commodore-Mensah, Cheryl Dennison Himmelfarb, Yuling Chen, Michael Oberst
    The 9th Annual Johns Hopkins Research Symposium on Engineering in Healthcare · Poster
    December 2025 · Baltimore, MD

Industry

Visilant
Feb. 2026 – Present  ·  Baltimore, MD
Machine Learning Engineer  ·  Part-time
Bosch
Nov. 2023 – Mar. 2024  ·  Suzhou, China
Software Engineer  ·  Internship
Bosch Connected Industry, Engineering Software. BCI/ESW1-CN Team.

Education

Johns Hopkins University
Aug. 2024 – Dec. 2025  ·  Baltimore, MD
Master of Science  ·  Computer Science
GPA: 3.96 / 4.0 Courses: Machine Learning for Healthcare, Machine Learning: Deep Learning, Computer Vision, Vision as Bayesian Inference, Software System Design, etc.
Shandong University
Sept. 2020 – June 2024  ·  Jinan, China
Bachelor of Engineering  ·  Software Engineering
GPA: 89.29 / 100 Courses: Data Structures, Operating System, Computer Networks, Database System, Organization and Structure of Computer, Algorithm Design and Analysis, etc.

Honors & Awards

News

Apr. 2026 A paper was accepted to CHIL 2026.
Revisiting Performance Claims for Chest X-Ray Models Using Clinical Context.
Mar. 2026 Began employment at Johns Hopkins University.
Research Assistant in the lab of Prof. Michael Oberst.
Feb. 2026 Joined Visilant Inc.
Started working part-time as a Machine Learning Engineer.
Dec. 2025 Graduated from Johns Hopkins University.
Received a M.S. degree in Computer Science with GPA 3.96/4.0.
Dec. 2025 Presented a poster at JHU Engineering in Healthcare Symposium.
Presented 'Guideline and Evidence-Based Shared Decision-Making: Healthcare Knowledge Q&A System' at the 9th Annual Johns Hopkins Research Symposium on Engineering in Healthcare.
June 2024 Graduated from Shandong University in China.
Received a B.E. degree in Software Engineering with honors.
Feb. 2024 My first paper was published in Journal of Chemical Information and Modeling.
MucLiPred: Multi-Level Contrastive Learning for Predicting Nucleic Acid Binding Residues of Proteins.
Nov. 2023 Joined Bosch as a Software Engineer Intern.
BCI/ESW1-CN Team.
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