Minglang Yin

Minglang Yin

Postdoc Fellow, Johns Hopkins University

About me

  • I am Minglang Yin. I am a Postdoc Fellow in the Department of Biomedical Engineering, Johns Hopkins University. I am working with Prof.Natalia Traynova on developing AI models for addressing needs in cardiac electrophysiology.

  • My research interests are on developing AI and computational models to address pressing needs in clinical pipelines and to elucidate disease mechanisms. I am also interested in AI, cardiovascular biomechanics, computational mechanics, and uncertainty quantification.

Recent News:

  • (Mar. 2025) I was invited to give a presentation at the Pasteur Lab.
  • (Mar. 2025) I gave a presentation at SIAM CSE 2025.
  • (Dec. 2024) Our study on developing AI for predicting geometry-dependent solution operators of PDEs got accepted in Nature Computational Science! It attracted a high level of attention from media! NSF News, JHU HUB, Communications of the ACM (to be appeared), MIT Tech Review (chinese)
  • (Oct. 2024) Oral presentation at SIAM MDS 2024.
  • (Jun. 2024) Oral presentation at CMBE 2024.
  • (Jun. 2024) I received the Best PhD Thesis Award in Biomedical Engineering (Runner-Up), International Journal for Numerical Methods in Biomedical Engineering (IJNMBE)
  • (May. 2024) I was invited to give two oral presentations in HRS 2024 (Boston) on our latest AI research for advancing the quality of clinical care. See you in Boston.
  • (Apr. 2024) Invited talk in Lu’s group at Yale. “Learning Solution Operators of Partial Differential Equations Across Geometries”
  • (Mar. 2024) We proposed a computational-based shape categorization for left atrial appendage. This pipelines greatly improve the shortage in interoperatability in the current appendage classification system and will be tested on a very large cohort in the next few months!
  • (Feb. 2024) Check out our latest paper. DIMON enables geometry-dependent operator learning with validation on over 1,000 personalized hearts digital twins derived from cardiac imaging of patients with heart disease.
  • (Nov. 2023) I was selected by Hopkins as institutional candidates for the Moore Inventor Fellow.
  • (Jul. 2023) I received the Kenneth M. Rosen Fellowship in Cardiac Pacing and Electrophysiology, Heart Rhythm Society 2023
  • (Jun. 2023) Invited talk, Biophysics-informed Machine Learning, The Platform for Advanced Scientific Computing (PASC) Conference (Online) 2023
  • (May. 2023) Poster session, Heart Rhythm 2023, New Orleans, LA
  • (Apr. 2023) Invited talk at CIS/MINDS seminar, Johns Hopkins University
  • (Apr. 2023) Check out our paper on DL for constitutive modeling. The framework learns the constitutive laws for a family of materials and infer the new samples without retraining! A generative modeling framework for inferring families of biomechanical constitutive laws in data-sparse regimes
  • (Feb. 2023) Invited Lightening talk, School of Medicine/Whiting School of Engineering Research Retreat, Johns Hopkins University
  • (Mar. 2023) Travel Award, 17th U. S. National Congress on Computational Mechanics
  • (Oct. 2022) Invited talk, Finalist of Robert J. Melosh Competition, Civil & Environmental Engineering, Duke University
  • (Sep. 2022) Invited talk at Complex Fluids and Soft Matters (CFSM) seminar series, Department of Mechanical Engineering, Clemson University (Online)
  • (Aug. 2022) I start my new position as a postdoc in the department of biomedical engineering, Johns Hopkins University.
  • (Jul. 2022) I have my thesis defense in late July, 2022.