“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)
Tripat Kaur followed the Masters in Applied Computer Science in 2020. His interest in Computer Science goes back to his school days. Not only the theory classes were very interesting, he also enjoyed the practical assignments to the fullest. His first-ever programming language C++. was a thrill. He made his first program on the blue screen of Turbo to get a ‘Hello Tripat’ output on the black screen. Ever since programming has been his passion.
The MACS program started teaching from a very basic level. Even if one had no computer science background, it was not a problem because everything is taught from scratch, but the study load in the first year was very high. Tripat enjoyed Advanced Programming Concepts the most by far. It helped him improve his programming skills a lot. Tripat studied during the corona year and his first year was through remote teaching. It was very different from what he had imagined. Even though being in different countries, his fellow students made sure that he did not have to worry about the time differences. They always adjusted with him making it fun to work on team projects. Tripat is now a more confident person as his horizons have widened. Not only technically but even his soft skills have improved thanks to this program. Tripat says: Never be afraid to dream. Word hard and believe in yourself, things will fall into place. His ideal future is to be completely independent and settled not only in terms of finances but in terms of happiness and confidence. Also, being able to support his family the way they have till now.
It is possible to perform the preparatory program in parallel with the master program and does not add study duration to the 2-year master program if you choose to do so.
ETRO’s Peter Schelkens has put his shoulders under the new Spin-off Swave Photonics, an innovator in Holographic eXtended Reality (HXR) technology. It is a Spin-off of IMEC and VUB.
“Our vision is to help build the fundamental holographic technology to bring the metaverse to life and work,” said Theodore Marescaux, CEO and founder, Swave Photonics. “Swave’s HXR gigapixel technology will forever change the way we see and experience displayed still images, videos and live imaging. True, lifelike and immersive metaverse experiences powered by Swave technology are poised to replace every AR/VR display and headset to the point where virtual, augmented or eXtended reality is practically indistinguishable from the real world.”
“We are convinced that Swave can bring to the market a fundamental technology we have been developing for more than five years through substantial R&D programs and imec investments,” said Luc Van den hove, president and CEO of imec. “Imec has a strong track record of innovation and productization that can scale across a wide range of applications. We are committed to make Swave a success and have great confidence that with their extensive patent portfolio and continued support of our teams and ecosystem, Swave can become one of the biggest disruptors for immersive 3D displays and a key accelerator for applications like the metaverse.”
Johan Stiens, the ETRO representative in the working group of “Digital for Climate” of the Alliance for IoT and Edge Computing Innovation, https://aioti.eu/
is co-author with a group of 20 people of a final report (+ 80 pages) on “IoT and Edge Computing Carbon Footprint Measurement Methodology”  (Release 1.1)
https://aioti.eu/wp-content/uploads/2022/11/AIOTI-Carbon-Footprint-Methodology-Report-Final-R1.1.pdf
The goals of this report are multifold:
• To help users of IoT and Edge Computing technologies and services, to understand and make informed choices on how to assess the carbon footprint of solutions and services they use, and to as well to measure how these methodologies support carbon footprint reduction of their use
• To present initiatives and standards, existing methodologies of measuring ICT carbon footprint and how they can be applied to IoT and Edge Computing
• To present selection methodology criteria and how to measure benefits of using them in reducing carbon footprint when using IoT and Edge Computing technologies and services for several industrial domains
• To propose a method of calculating the carbon avoided emissions in an industrial sector/domain, when ICT is used as an enabling technology
The I Love Science Festival at Tour & Taxis in Brussels on October 13-15 was a great success, drawing over 150000 science and technology enthusiasts of all ages. ETRO.RDI enchanted attendees with interactive exhibits, including light-based physiological readings, acoustic camera art, a crypto escape room challenge, and an AI-driven urban climate model.
For those who missed out on this year’s event, mark your calendars for the next I Love Science Festival, and be sure to check out ETRO.RDI’s booths.
Exciting news for the start of this academic year in the team of Prof. Nikos Deligiannis: a prestigious FWO grant has been awarded to 2nd year PhD candidate Brent de Weerdt. Brent will start a new research project with a goal in mind: merging optimization algorithms and deep learning algorithms, to create more efficient models for image, video processing and computer vision. Additionally, PhD candidates Esther Rodrigo and Boris Joukovsky successfully passed the 2 years evaluation mark for their FWO grants. Their respective research on explainable graph deep learning on video deep learning have been consequently extended.