Wednesday May 18th
19:45 live music Downtown Grooves
Historically, now we have an unprecedently large amount of data available in various systems, and the growth of data volumes is rapid and continuous. The numbers of scientific papers published per year are higher than ever before. Which data and scientific findings get shared, for which purposes, and how? How to address open and closed data, and reproducibility crisis? How to convert Big Data into Smart Data, that is interpretable by a both machine and human? And how to make sure that the resulting Smart Data is trustworthy?
In this Science Café, dr. Anna Fensel will discuss these questions, particularly, from the technical perspective, and give examples for relevant solutions implemented with Semantic Web technology, linked data, knowledge graphs and FAIR (Findable, Accessible, Interoperable, Reusable) data management. Dr. Anna Fensel is Associate Professor at Wageningen University & Research, Wageningen, the Netherlands, and at Semantic Technology Institute, Department of Computer Science, University of Innsbruck, Austria. Her research field is artificial intelligence and data science. Previously she lived and worked in Austria, United Kingdom, and Russian Federation. Her university degrees are in computer science and applied mathematics. She has taken lead or part in ca. 30 collaborative scientific projects at EU, international and national levels, authored ca. 140 refereed publications, and has been a supervisor of ca. 50 PhD, Master and Bachelor theses students.
In the second talk Applied deep learning in agri-food: What is Wageningen up to? , together with dr. Aneesh Chauhan, we will look at some of the agri-food problems where deep learning, an increasingly dominant sub-domain of machine learning in the last decade, is being used to solve some of the industrial challenges. We will also look some nice examples of the dark side of the technology. Dr. Aneesh Chauhan is a Senior research and Expertise leader of Computer Vision in Wageningen Food and Biobased Research. He has background in Computer Science and Engineering, Ph.D. in Informatics and Robotics, and has been working on AI (mainly machine learning) and Robotics for almost 20 years. Some interesting research over the years have been on building child-like (pre-toddler) language acquisition in robots through human-robot interaction, giving intelligence to a Humanoid robot in restaurant serving settings, autonomous control of micro-aerial vehicles and, of course, a variety array of agri-food challenges in the last 5 years.