Research Ambitions
Ambitions are research questions of which the answers will give us the opportunity to determine the future. Are you a master student and would you like to significantly contribute to our thought leadership position in the AI domain? Please reach out to Joop Snijder, Head of Research Artificial Intelligence, for more information about how you can help.
Explainable AI
An Explainable AI (XAI) or Transparent AI is an artificial intelligence (AI) whose actions can be easily understood by humans. It contrasts with the concept of the “black box” in machine learning, meaning the “interpretability” of the workings of complex algorithms, where even their designers cannot explain why the AI arrived at a specific decision. One of our ambitions is to make AI and machine learning more transparent, so customers can understand and trust the models we implement.
Advanced Machine Learning
This research ambition includes research into modern machine learning methods that take advantage of increased complexity to provide improved performance. For example deep learning, reinforcement learning, natural language understanding and computer vision.
Natural Language Processing in Dutch
Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data. There’s a lot of research done for the English language, but no so much for the Dutch language. Our ambition is to expand the research on this topic.
Are you interested in working in this area?
Don’t hesitate to reach out! Contact Joop Snijder, Head of Research Artificial Intelligence. Or apply directly to one of our assignments.
Artificial Intelligence Publications
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Using generative modelling to perform diversifying data augmentation
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Recognizing Parkinson’s and Alzheimer’s through video footage and Artificial Intelligence
Neurological movement disorders such as Parkinson’s, Alzheimer’s and Huntington’s disease are not always easy to distinguish for doctors. Giving the r…
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Thesis Talk Reinier Joosse – Deep learning models based on Z3
Modern cars have cameras that recognize traffic signs at the side of the road. For example, your car may detect that there is a “Stop” sign in front o…
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Thesis Talk Jan Smits – Mutator, the open-source mutation testing framework
Stryker Mutator, the open-source mutation testing framework developed with Info Support, would like to introduce mutation levels to their framework.
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The Combination of Investment Strategies Using the Replicator Equation
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Automated Privacy-Preserving Video Processing through Anonymized 3D Scene Reconstruction
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Using Discretization and Resampling for Privacy Preserving Data Analysis: An experimental evaluation
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Method Call Argument Completion using Deep Neural Regression
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Unit test generation using machine learning
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Quantifying Chatbot Performance by using Data Analytics
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Code Completion with Recurrent Neural Networks
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Chatbot Personality and Customer Satisfaction
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Specifying and Testing Conversational User Interfaces
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Supporting Decision-making in Fraud Sensitive Environments
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Automated Taxonomy Expansion and Tag Recommendation in a Knowledge Management System
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Building a Data-Driven Search Engine Spelling Corrector
Building a Data-Driven Search Engine Spelling Corrector