Kayhan Batmanghelich

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Kayhan Batmanghelich

Assistant Professor
Department of Biomedical Informatics

kayhan@pitt.edu
Phone: 412-648-9037
Pitt DBMI Website
My CV

Admin Support: Maria Bond (bond@pitt.edu)

Room 531
5607 Baum Blvd, Suite 500
Pittsburgh, PA 15206-3701

I am an Assistant Professor of Department of Biomedical Informatics and Intelligent Systems Program with secondary appointments in the Computer Science and Electrical Engineering Departments 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. Read More

Recent News

One paper is accepted to AAAI 2021!

Dec 02, 2020

Congratulations to Li Sun and Ke Yu for their joint paper in AAAI 2021! Their paper show how to incorporate anatomically relevant context to self-supervised learning!

Ke’s journal is accepted to ACM JCIM!

Oct 22, 2020

Congratulations to Ke Yu! His paper is accepted to the Journal of Chemical Information and Modeling. The method integrates drug taxonomy with chemical structure and enables localizing novel molecules in the context of the clinically approved drugs.

Brian and Stephen won an award for the liver project!

Oct 16, 2020

Congratulations to Brian! His collaborative work with Stephen Cai and Amir Borhani on estimating liver stiffness using a machine learning method received Cum Laude Award from the 43rd Society of Body Imaging Conference.

Our paper is accepted to the Oxford Bioinformatics Journal!

Sep 26, 2020

Congratulations to Mingming Gong! His awesome paper (Preprint) is accepted to the Oxford Bioinformatics Journal! Fundamental and rigorous research for inference of statical independence which uses unpaired data!

Giving talk at the Oxford ML Summer School!

Aug 21, 2020

I am excited to present at the Oxford ML Summer School (OxML 2020)! I will talk about various applications and challenges of Machine Learning in Medical Imaging!

Selected Publications

Probabilistic Modeling of Imaging, Genetics and the Diagnosis

K.N. Batmanghelich, A. Dalca, G. Quon, M. Sabuncu, P. Golland
IEEE Trans Med Imaging

Explanation by Progressive Exaggeration

S. Singla, B. Pollack, J. Chen, K. Batmanghelich

Eighth International Conference on Learning Representations (ICLR)

 

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

S. Singla, M. Gong, S. Ravanbakhsh, F. Sciurba, B. Poczos, K.  Batmanghelich
Medical Image Computing & Computer-Assisted Intervention (MICCAI)

Twin Auxiliary Classifiers GAN

M.*, Y. Xu*, Ch. Li, Kun Zhang, K. Batmanghelich (*: equal contribution)
NeurIPS 2019 [Spotlight 2.4%]

Lab Members

Junxiang Chen

Post Doctoral Researcher (PhD)

Brian Pollack

Post Doctoral Researcher (PhD)

Sumedha Singla

Research Assistant (Pitt-CS)

Li Sun

Research Assistant (Pitt-ISP)

Yanwu Xu

Research Assistant (Pitt-ISP)

Ke Yu

Research Assistant (Pitt-ISP)

Rohit Kumar Jena

Intern (CMU-Robotics)

Sead Nikšić

Intern (Pitt-ECE)

Tigmanshu Chaudhary

Machine Learning Engineer

Alumni

Jiaming Bai

Lisa Hou

Fan Qian

Keyi Yu