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Name
Dr. Andrew Janowczyk
Title
Assistant Professor, Department of Biomedical Engineering, Case School of Engineering, Switzerland
Bio
Dr Andrew Janowczyk is an Assistant Research Professor at The Center of Computational Imaging and
Personalized Diagnostics (CCIPD) at Case Western Reserve University, and a Senior Research Scientist in the Precision Oncology Center at the Lausanne University Hospital (CHUV), Switzerland. For over 10 years he has applied computer vision algorithms to digital pathology images. One of his areas of expertise is in leveraging deep learning to build computational models to aid pathologists in many common tasks, such as disease detection and grading. Dr Janowczyk’s 2016 Journal of Pathology Informatics Paper entitled “Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases” (over 30k views), laid out a generalized approach via open-sourced code and datasets to facilitate the development of the next generation of data scientists. In 2018, his tool “HistoQC: A quality control pipeline for digital pathology slides” received the Innovation Award at the European Congress of Digital Pathology (ECDP). He helped co-found and was elected secretary of the Swiss Digital Pathology Consortium (SDiPath). His newer research focuses on the tasks of predicting prognosis and therapy response. He maintains a research-oriented blog, andrewjanowczyk.com, which aims to provide digital pathology related insights, code, and datasets to the research community.
Personalized Diagnostics (CCIPD) at Case Western Reserve University, and a Senior Research Scientist in the Precision Oncology Center at the Lausanne University Hospital (CHUV), Switzerland. For over 10 years he has applied computer vision algorithms to digital pathology images. One of his areas of expertise is in leveraging deep learning to build computational models to aid pathologists in many common tasks, such as disease detection and grading. Dr Janowczyk’s 2016 Journal of Pathology Informatics Paper entitled “Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases” (over 30k views), laid out a generalized approach via open-sourced code and datasets to facilitate the development of the next generation of data scientists. In 2018, his tool “HistoQC: A quality control pipeline for digital pathology slides” received the Innovation Award at the European Congress of Digital Pathology (ECDP). He helped co-found and was elected secretary of the Swiss Digital Pathology Consortium (SDiPath). His newer research focuses on the tasks of predicting prognosis and therapy response. He maintains a research-oriented blog, andrewjanowczyk.com, which aims to provide digital pathology related insights, code, and datasets to the research community.
