Kayhan Batmanghelich

  • Assistant Professor

I am an Assistant Professor of Department of Biomedical Informatics and Intelligent Systems Program at the University of Pittsburgh and an adjunct faculty in the Machine Learning Department at the Carnegie Mellon University. My research is at the intersection of medical vision (medical image analysis), machine learning, and bioinformatics. I develop algorithms to analyze and understand medical image along with genetic data and other electrical health records such as the clinical report. For example, we are developing a probabilistic model to extract information from brain images (Magnetic Resonance Images) of patients with Alzheimer's disease and relate them the underlying genetic markers involved in the disease. We are interested in method development as well as translational clinical problems because after all, exciting research directions are coming from real applications.

Institution of Highest Degree

  • University of Pennsylvania

Representative Publications

A Likelihood-Free Approach for Characterizing Heterogeneous Diseases in Large-Scale Studies
J. Schabdach, S. Wells, M. Cho, N. Batmanghelich
International Conference on Information Processing in Medical Imaging

Transformations Based on Continuous Piecewise-Affine Velocity Fields
O. Freifeld, S. Hauberg, J. Fisher III, N. BatmanghelichIEEE Transactions on Pattern Analysis and Machine Intelligence

Nonparametric Spherical Topic Modeling with Word Embeddings
N. Batmanghelich, A. Saeediy, K. Narasimhan, S. Gershman
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL)

Inferring Disease Status by non-Parametric Probabilistic Embedding
N. Batmanghelich, A. Saeedi, R. J. Estepar, M. Cho, S. Wells
Workshop on Medical Computer Vision: Algorithms for Big Data (MCV)

Unsupervised Discovery of Emphysema Subtypes in a Large Clinical Cohort
P. Binder N. Batmanghelich, R. J. Estepar, P. Golland
7th International Workshop on Machine Learning in Medical Imaging (MLMI)

Probabilistic Modeling of Imaging, Genetics and the Diagnosis
K.N. Batmanghelich, A. Dalca, G. Quon, M. Sabuncu, P. Golland
IEEE Trans Med Imaging

Research Interests

Application of Machine Learning in Healthcare Medical Vision
Computational Biology
Probabilistic Graphical Model
Bayesian Data Analysis
Deep Learning