Projects

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PU learning from relational data KU Leuven

Jesse Davis
Informatics Section

An algorithm, like a human, is said to learn if its performance on a task improves as it gains more experience. For example, consider the task of labeling an abnormality on a mammogram as benign or malignant, where experience consists of a radiologist’s description of an abnormality and its known label. Traditional machine learning approaches for binary classification require having access to fully labeled data, containing positive and ...

Unlocking the TCR repertoire for personalized cancer immunotherapies. University of Antwerp

Kris Laukens
Center for Oncological Research (CORE), Laboratory for Experimental Hematology (LEH), ADReM Data Lab (ADReM)
Cancer is one of the leading causes of death worldwide. Over the past decades, new therapies have been developed that target the patients' immune system to mount an antitumor response. The efficacy of these immunotherapies has already been demonstrated in various clinical trials. Nevertheless, these therapies show a large variation in their individual responses as some patients respond well to the therapy, while others do not. In this project, ...

Optimized Hardware Architectures for Ultra Low-Latency Object Detection Applications Hasselt University

Applied Computer Science Lab, Computational Sensing Systems, Zhejiang University
Although artificial intelligence (AI) has been an important research topic for over sixty years, it is only in 2012 that with the application of deep neural network (DNN) models based on convolutional neural networks (CNN's), with the use of computationally effective non-linear activations and the availability of sufficient computational power that deep learning has ignited a new wave of machine learning. Current deep learning applications need ...

Simulation based testing of large scale internet of things applications. University of Antwerp

Peter Hellinckx
Co-Design of Cyber-Physical Systems (Cosys-Lab), Antwerp Systems and software Modelling (AnSyMo), Internet Data Lab (IDLab)
The goal of this project is to introduce a simulation based methodology which will be used to cope with the scalability constraints of modern IoT software testing, and more specifically the testing of ultra large scale systems with emergent behavior. With IoT becoming more mainstream and with the rise in the amount of devices getting interconnected, the complexity and scale of the IoT landscape will largely increase. This interoperability ...

Sabbatical Leave Project, 2018-2019 University of Antwerp

Walter Daelemans
Centre for Computational Linguistics and Psycholinguistics (CLiPS)
Two sub-projects are addressed: in stylometry, methodological issues are addressed, especially related to personality prediction from text: feature optimization, data acquisition and quality, model selection, and especially explanation of trained machine learning models. In machine learning for natural language, approaches are investigated on how to combine knowledge and reasoning with the currently predominant deep learning "black boxes".

A Connected Brain-sized network – Design of a distributed connectivity layer for combining different heterogeneous deep learning systems. University of Antwerp

Internet Data Lab (IDLab)
Artificial Intelligence in general and deep learning specifically has experienced major breakthroughs in the last decade showing above human intelligence for complex tasks. Current deep learning technologies are however very power hungry and therefore require the use of large Graphical Processing Units (GPUs) farms in large-scale datacenters. With the recent advances in neural network hardware (neuromorphic computing design such as Neural ...

Artificial Intelligence Data Analysis KU Leuven

Giovanni Lapenta
Plasma-astrophysics

AIDA brings a transformational innovation to the analysis of heliophysics data in four steps.
First, AIDA will develop a new open source software called AIDApp written in Python (a free language) and capable of
collecting, combining and correlating data from different space missions. AIDApp wants to replace mission-specific tools
written for costly languages (such as IDL) that exclude many scientists, students and amateur space ...

A Methodology for Analysis and Optimization of Distributed Artificial Intelligence. University of Antwerp

Peter Hellinckx
Internet Data Lab (IDLab)
Although the foundations of Artificial Intelligence (AI) have been around for a long time, advances in computational performance and research in novel AI techniques have led to a revival of this research domain. With the advent of the Internet of Things (IoT), numerous "smart" applications driven by AI, have found their way into our everyday lives. Due to the computational complexity of these techniques, currently a common approach is to ...

Geometry in the mix: geometric methods for non-linear spectral unmixing (GEOMIX). University of Antwerp

Paul Scheunders
Vision lab
The main objective of the project is the creation of a powerful yet flexible hyperspectral unmixing methodology, based upon sound physical and mathematica! principles, validated on extensive artificial and real data sets, and made publicly available through publication and sharing of program code. The unmixing methodology is based upon the recently developed multilinear mixing model, and will extend this state-of-the-art method with several ...