Carnegie Mellon University

Kayhan Batmanghelich

Kayhan Batmanghelich

Assistant Professor, Department of Biomedical Informatics and Intelligent Systems, University of Pittsburgh

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

My research is at the intersection of medical vision (medical image analysis), machine learning, and bioinformatics. I develop algorithms to analyze and understand medical images along with genetic data and other electrical health records such as the clinical report. For example, I have developed 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. I am interested in novel method development as well as real-world clinical applications.

Carlos Guestrin

Carlos Guestrin

Professor of Computer Science & Engineering, University of Washington

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

 

Estevam Hruschka

Estevam Hruschka

Associate Professor, Computer Science Department, Federal University of Sao Carlos

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

My research interests lie in Machine Learning and how to build computer systems capable of deep understanding structured, as well as unstructured data (such as text).

Kamal Nigam

Kamal Nigam

Engineering Manager, Google Pittsburgh

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

 

Shandong Wu

Shandong Wu

Assistant Professor of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Dr. Wu’s background is in computer vision with additional training in radiology and clinical imaging. His research interfaces a broad range of interdisciplinary in computational science and medicine for translational and clinical applications, with main areas in computational biomedical imaging analysis, big (health) data coupled with machine/deep learning, imaging-based clinical studies, radiomics/radiogenomics, and artificial intelligence in clinical informatics/workflows. Current research interests center on computational breast imaging and clinical studies for investigating quantitative imaging-derived biomarkers, models, and systems for breast cancer screening, risk assessment, diagnosis, prognosis, and treatment, towards improving individualized clinical decision-making and precision medicine. 

Jun Zhu

Jun Zhu

Associate Professor, Tsinghua University

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

My research focuses on developing statistical machine learning methods to understand complex scientific and engineering data. My current interests are in latent variable models, large-margin learning, Bayesian nonparametrics, sparse learning in high dimensions, and scalable learning algorithms.