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.

Education

• 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

Optimization

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

Microscopy

Lens-free imaging | Holography | Two-photon imaging

Biomedical Applications

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

Projects

A (very incomplete) selection of some of the topics I work on (past and present). More pages under construction.

Structured Matrix Factorization

Learning Matrix Factorizations with Structured Factors

Neural Network Loss Landscapes

Characterizing the loss surface of neural network training problems.

Understanding Dropout

Understanding the effects of Dropout regularization when training neural networks.