Apryse
Hossein Khatoonabadi is a Machine Learning Researcher and Software Engineer at Apryse since July 2015, specializing in deep-learning-based document understanding solutions, including table detection and document layout analysis. From September 2010 to July 2015, Hossein worked as a Research Assistant at Simon Fraser University, focusing on saliency-based video quality assessment. Additionally, a research scholar position at the University of California, San Diego involved visual saliency estimation projects. Prior experience includes senior software development roles at Sourena-Med Inc, where Hossein developed software for various medical applications, and earlier software development positions at Niroo Research Institute and the International Center for Science & High Tech. Hossein holds a PhD in Engineering Science from Simon Fraser University and an MSc in Computer Engineering from Amirkabir University of Technology.
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Apryse
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Apryse, previously known as PDFTron, takes document solutions to the next level, making work better and life simpler. As a global leader in document processing technology, Apryse gives developers, enterprise customers and small businesses the tools they need to reach their document goals faster and easier. Our product portfolio includesApryse SDK, Fluent, iText and XODO. Apryse technology works with all major platforms and a wide variety of unique file types.