Associate Research Scientist

Johns Hopkins Univeristy

Ben Haeffele

I am a research faculty member in the Johns Hopkins Mathematical Institute for Data Science (MINDS) and Center for Imaging Science (CIS). My current research is broadly on developing theory and algorithms for processing high-dimensional data at the intersection of machine learning, optimization, and computer vision. In addition to basic research in data science I also work on a variety of applications in medicine, microscopy, and computational imaging.


  • PhD in Biomedical Engineering

    Johns Hopkins University

  • BS in Electrical Engineering

    Georgia Institute of Technology

Research Interests

Machine Learning

Deep learning theory | Sparse and low-rank methods | Matrix/tensor factorizations | Subspace clustering | Generative models | Non-linear/manifold clustering | Physics constrained learning

Computer Vision

Image/Video segmentation | Image classification | Compressed sensing | Object detection | Multi-object tracking


Non-convex optimization | Low-rank problems | Convex relaxation/lifting methods


Lens-free imaging | Holography | Two-photon imaging

Biomedical Applications

Image analysis for microscopy | Hematology microscopy | Infection detection and monitoring | Digital pathology

Recent Publications

Learning globally smooth functions on manifolds

Unsupervised manifold linearizing and clustering

Variational information pursuit for interpretable predictions

White-Box Transformers via Sparse Rate Reduction

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models

Understanding Doubly Stochastic Clustering

Adaptive sparse reconstruction for lensless digital holography via PSF estimation and phase retrieval