“Signal Processing in the AI era” was the tagline of this year’s IEEE International Conference on Acoustics, Speech and Signal Processing, taking place in Rhodes, Greece.
In this context, Brent de Weerdt, Xiangyu Yang, Boris Joukovsky, Alex Stergiou and Nikos Deligiannis presented ETRO’s research during poster sessions and oral presentations, with novel ways to process and understand graph, video, and audio data. Nikos Deligiannis chaired a session on Graph Deep Learning, attended the IEEE T-IP Editorial Board Meeting, and had the opportunity to meet with collaborators from the VUB-Duke-Ugent-UCL joint lab.
Featured articles:
- De Weerdt, B. et al., “Designing Transformer Networks for Sparse Recovery of Sequential Data Using Deep Unfolding” (https://ieeexplore.ieee.org/abstract/document/10094712)
- Yang X. et al., “Relevance Propagation through Deep Conditional Random Fields” (https://ieeexplore.ieee.org/abstract/document/10095075)
- Stergiou A. et al., “Play it back: Iterative attention for audio recognition” (https://ieeexplore.ieee.org/abstract/document/10096532, developed at the University of Bristol)
Two of ETRO’s postdocs, Angel for the project Equitable Oxymetry and Abel for the I-Healthy path project, have been selected for the MedTech accelerator: https://lifetech.brussels/en/medtech-accelerator-en/.
More info and pictures in these links:
On March 12 2021 at 16.00 Evgenia Papavasileiou will defend her PhD entitled “Towards more Efficient NeuroEvolution: Application on Feature Selection and Classification Problems”.
NeuroEvolution (NE) is a sub-field of Artificial Intelligence whose purpose is to optimize Artificial Neural Networks (ANNs) by modeling the biological evolutionary process. NeuroEvolution of Augmenting Topologies (NEAT) that evolves the topology and the connectivity weights of the ANNs, is one of the most influential algorithms in the field. This PhD performs different studies on NEAT extensions, namely FD-NEAT, FS-NEAT and HA-NEAT and proposes new extensions so that the resulting methods could require fewer generations, evolve smaller and less complex networks and scale on complex problems.
After the publication of NEAT in 2002 many methods have appeared that extend its functionality in various ways. In this PhD, a systematic review is performed to identify and categorize the NEAT’s successors. The proposed clustering scheme can support researchers 1) understanding the current state of the art that will enable them 2) exploring new research directions or 3) benchmarking their proposed method to the state of the art, if they are interested in comparing, and 4) positioning themselves in the domain or 5) selecting a method that is most appropriate for their problem. In addition, different studies are conducted to achieve important intermediate stepping stones. The first set of investigations concern design choices in the initial topologies of two NEAT extensions, namely FD-NEAT and FS-NEAT. These include the introduction of a hidden layer in the initial topologies, the initialization of the topologies with a different connectivity setting and the employment of different activation functions in the output layer. Additionally, BS-HA-NEAT and BS-NEAT are proposed as new extensions of HA-NEAT and NEAT, that perform speciation in the behavioral rather than in the genotypic space. It is found that BS-HA-NEAT and BS-NEAT outperform HA-NEAT and NEAT solving previously unsolvable problems or improving the accuracy and reducing the complexity of the evolved networks. Furthermore, HA-FD-NEAT, extending both HA-NEAT and FD-NEAT is proposed. This is able to evolve the topology, the connectivity weights and the activation functions of ANNs while identifying the relevant features. HA-FD-NEAT outperforms HA-NEAT and performs as good as FD-NEAT. Also, BS-HA-FD-NEAT is proposed as an extension to HA-FD-NEAT by performing speciation in the behavioral space. BS-HA-FD-NEAT outperforms its ancestor by evolving significantly smaller networks. In overall, the resulting algorithm outperforms its ancestors, NEAT, FD-NEAT, and HA-NEAT achieving better accuracy, in fewer generations and evolving smaller and less complex networks. Finally, BS-HA-FD-NEAT is tested on a complex, real world application of reducing the false positives outputed from a detector of abnormal COVID-19 related findings from lung Computer Tomography (CT) images.
You van visit the LEGO urban planner again and design your climate-resilient city at “Dag van de Wetenschap” (Science Day) on Sunday 26 November at Muntpunt.
Dear colleagues,
We’re pleased to announce that the AI4WCM research team will be hosting a presentation in the Marconi meeting room at PL9.2 on the 16th of October from 13:30 to 14:30. During this one-hour session, each team member will share their latest research and findings in a relaxed and informative manner. It’s a great opportunity to stay updated on the work happening within our group.
Please mark your calendars and keep an eye out for more details. We look forward to sharing our research progress with you!
ETRO’s Senior Business Development Manager Bugra Ersu was invited by Istanbul Project Management Institute to give a webinar on problems encountered in technology transfer projects.
A very productive event was held with the participation of more than 100 project professionals from different sectors.
https://www.linkedin.com/feed/update/urn:li:activity:6760177146632691712/
Johan Stiens gave a lecture @ the atheneum Geel in the framework of PACT
“Technology, Humanity, and the Climate Imperative: Engineering a Sustainable Future”
Climate change is no longer a distant threat—it is a defining reality shaping our planet, economies, and societies. This keynote invites participants to take a bird’s-eye view of the interconnected forces driving this transformation and to explore how technology, data, and global citizenship can converge to create a sustainable future. We begin with critical observations on climate change and its cascading impact on population dynamics and economic resilience. From there, we examine the evolving energy mix, where renewable sources are not just alternatives but imperatives, demanding innovation in materials, transistors, and processors that power both ICT and solar technologies.
As we enter the data era, ICT systems and smart IoT solutions are unlocking unprecedented sectorial benefits—from MedTech and HealthTech to agri-food and construction—while enabling biodiversity and sustainability at scale. These advances are not merely technical; they represent a societal shift toward intelligent, resource-efficient ecosystems. Drawing on decades of experience in sensor technology development and active engagement with global organizations, this talk will challenge academia, industry, and policymakers to embrace technology uptake as a catalyst for systemic change. Ultimately, the question is not only how we innovate, but how we become true global citizens—responsible stewards of the planet we share, and architects of a future where digital intelligence and clean energy work hand in hand to safeguard life on Earth.