All Years Seminars
[LINGI2399] 2026-04-16 (10:45) : Quantum Computing
At BARB94
Speaker :
Eric Michiels (IBM)
Abstract : Quantum Computing is rapidly moving onto the strategic agenda of organizations worldwide. It is designed to tackle complex problems and serves as a complement, not a replacement, to Classical Computing. What truly sets Quantum Computing apart? What are the key characteristics of its hardware, software, and applications? Which hardware architectures exist, and how are Quantum Algorithms developed? And what skills will professionals need in the new "Quantum Era"?
The speaker will explore short-, mid-, and long-term use cases, look at early adopters, and examine the synergy between Quantum Computing and AI. You will also discover how both junior and senior professionals can begin their Quantum Journey.
[INGI] 2026-04-16 (13:00) : No evaluation without fair representation: Impact of label and selection bias on the evaluation, performance and mitigation of classification models
At BARB 94 (Hall Sainte-Barbe)
Speaker :
Magali Legast (ICTEAM)
Abstract : Bias can be introduced in diverse ways in machine learning datasets, for example via selection or label bias. Although these bias types in themselves have an influence on important aspects of fair machine learning, their different impact has been understudied. In our work, we empirically analyze the effect of label bias and several subtypes of selection bias on the evaluation of classification models, on their performance, and on the effectiveness of bias mitigation methods. We also introduce a biasing and evaluation framework that allows to model fair worlds and their biased counterparts through the introduction of controlled bias in real-life datasets with low discrimination. Using our framework, we empirically analyze the impact of each bias type independently, while obtaining a more representative evaluation of models and mitigation methods than with the traditional use of a subset of biased data as test set. Our results highlight different factors that influence how impactful bias is on model performance. They also show an absence of trade-off between fairness and accuracy, and between individual and group fairness, when models are evaluated on a test set that does not exhibit unwanted bias. They furthermore indicate that the performance of bias mitigation methods is influenced by the type of bias present in the data. Our findings call for future work to develop more accurate evaluations of prediction models and fairness interventions, but also to better understand other types of bias, more complex scenarios involving the combination of different bias types, and other factors that impact the efficiency of the mitigation methods, such as dataset characteristics.
[INMA] 2026-04-14 (14:00) : High order deterministic and stochastic optimization without evaluating the objective function
At Euler building (room A.002)
Speaker :
Philippe Toint (Université de Namur)
Abstract : We first motivate OFFO methods, that is methods for optimization without computing the objective function's value. We then show that such methods are applicable for unconstrained minimization of nonconvex functions (both in the deterministic and stochastic frameworks) and give a few examples from deep learning applications. We then move on to the case where the problem has general equality and inequality constraints, propose an OFFO algorithm for this case and analyze its global convergence rate in the deterministic case. We conclude by presenting some numerical illustration of the proposed method. This is a Joint work with S. Gratton, S. Bellavia and B. Morini.
[LINGI2399] 2026-04-09 (10:45) : How LLMs will change IT jobs
At BARB94
Speaker :
Tim Paridaens (Deloitte)
Abstract : The rise of Large Language Models (LLMs) is poised to revolutionize the IT job landscape. In domains such as automated coding assistance, automated testing, customer support automation or cybersecurity advancements, LLMs already provide today advanced capabilities that efficiently support IT staff in their daily operations. The speaker will share Deloitte’s experience using LLMs to support IT functions and highlight measured gains and identified limitations.
[ELEN] 2026-04-08 (09:00) : From Beyond-Diagonal Reconfigurable Intelligent Surfaces to Analog Computing for Communications and Signal Processing
At Shannon Room
Speaker :
Bruno Clerckx (Department of Electrical and Electronic Engineering - Imperial College London, South Kensington Campus)
Abstract : Modern systems rely on digital circuits, computing, and signal processors that operate on binary values, offering advantages such as precision, versatility, robustness. Yet, digital processors face major limitations as high power consumption and limited speed. Despite digital signal processing being widely adopted today, analog computing is attracting a renewed interest thanks to its ability to perform energy-efficient and massively parallelized computations.
The talk shows two promising avenues to devise new, faster, and more sustainable communication and signal processing architectures that marry the communication theoretic principles of modern digital communications with analog domain processing and computing paradigms such that information transmission, processing and computing are conducted faster with much lower computational complexity.
First, we introduce Beyond-Diagonal Reconfigurable Intelligent Surfaces (BD-RIS), a general framework of reconfigurable intelligent surfaces where elements are inter-connected via tunable impedances. This enables engineered coupling, allowing waves to propagate between elements, enhancing RIS-aided communications with greater signal manipulation flexibility.
Next, we introduce the concept of Microwave Linear Analog Computer (MiLAC) as a very general model of a computer exploiting the propagation of analog signals in a microwave network, offering exceptionally low computational complexity - unimaginable with conventional digital computers. We show that MiLAC can perform computation, e.g. matrix inversion and linear minimum mean square error estimation, with low complexity directly in the analog domain and enable new future MIMO communications with 10⁴× lower computational complexity than digital processing.
The increasing research interest in those areas is reflected by the Special Interest Groups on BD-RIS https://sites.google.com/view/ieee-comsoc-rcc-sig-bdris and on Analog Computing https://sites.google.com/view/sig-analog-computing in the IEEE Communications Society.
Bio:
Bruno Clerckx is a Full Professor and the Head of the Communications and Signal Processing Group at Imperial College London, London, U.K. He received the MSc and Ph.D. degrees in Electrical Engineering from Université Catholique de Louvain, Belgium, and the Doctor of Science (DSc) degree from Imperial College London, U.K. He spent many years in industry with Silicon Austria Labs (SAL), Austria, where he was the Chief Technology Officer (CTO) responsible for all research areas of Austria's top research center for electronic based systems and with Samsung Electronics, South Korea, where he actively contributed to 4G (3GPP LTE/LTE-A and IEEE 802.16m). He has authored two books on “MIMO Wireless Communications” and “MIMO Wireless Networks”, over 350 peer-reviewed international research papers, and 150 standards contributions, and is the inventor of over 80 issued patents among which several have been adopted in the specifications of 4G and 5G standards and are used by billions of devices worldwide. His research spans the general area of wireless communications and signal processing for wireless networks. He received the Blondel Medal 2021 from France for exceptional work contributing to the progress of Science and Electrical and Electronic Industries, the 2022 Adolphe Wetrems Prize in mathematical and physical sciences and the 2025 Georges Vanderlinden Prize in Electromagnetism and Telecommunications from Royal Academy of Belgium, multiple awards from Samsung, IEEE best student paper award, IEEE Globecom 2025 best paper award, and the EURASIP (European Association for Signal Processing) best paper award 2022. He is a Fellow of the IEEE and the IET. He is the vice-chair of ETSI Industry Specification Group (ISG) on Multiple Access Techniques (MAT).
The talk shows two promising avenues to devise new, faster, and more sustainable communication and signal processing architectures that marry the communication theoretic principles of modern digital communications with analog domain processing and computing paradigms such that information transmission, processing and computing are conducted faster with much lower computational complexity.
First, we introduce Beyond-Diagonal Reconfigurable Intelligent Surfaces (BD-RIS), a general framework of reconfigurable intelligent surfaces where elements are inter-connected via tunable impedances. This enables engineered coupling, allowing waves to propagate between elements, enhancing RIS-aided communications with greater signal manipulation flexibility.
Next, we introduce the concept of Microwave Linear Analog Computer (MiLAC) as a very general model of a computer exploiting the propagation of analog signals in a microwave network, offering exceptionally low computational complexity - unimaginable with conventional digital computers. We show that MiLAC can perform computation, e.g. matrix inversion and linear minimum mean square error estimation, with low complexity directly in the analog domain and enable new future MIMO communications with 10⁴× lower computational complexity than digital processing.
The increasing research interest in those areas is reflected by the Special Interest Groups on BD-RIS https://sites.google.com/view/ieee-comsoc-rcc-sig-bdris and on Analog Computing https://sites.google.com/view/sig-analog-computing in the IEEE Communications Society.
Bio:
Bruno Clerckx is a Full Professor and the Head of the Communications and Signal Processing Group at Imperial College London, London, U.K. He received the MSc and Ph.D. degrees in Electrical Engineering from Université Catholique de Louvain, Belgium, and the Doctor of Science (DSc) degree from Imperial College London, U.K. He spent many years in industry with Silicon Austria Labs (SAL), Austria, where he was the Chief Technology Officer (CTO) responsible for all research areas of Austria's top research center for electronic based systems and with Samsung Electronics, South Korea, where he actively contributed to 4G (3GPP LTE/LTE-A and IEEE 802.16m). He has authored two books on “MIMO Wireless Communications” and “MIMO Wireless Networks”, over 350 peer-reviewed international research papers, and 150 standards contributions, and is the inventor of over 80 issued patents among which several have been adopted in the specifications of 4G and 5G standards and are used by billions of devices worldwide. His research spans the general area of wireless communications and signal processing for wireless networks. He received the Blondel Medal 2021 from France for exceptional work contributing to the progress of Science and Electrical and Electronic Industries, the 2022 Adolphe Wetrems Prize in mathematical and physical sciences and the 2025 Georges Vanderlinden Prize in Electromagnetism and Telecommunications from Royal Academy of Belgium, multiple awards from Samsung, IEEE best student paper award, IEEE Globecom 2025 best paper award, and the EURASIP (European Association for Signal Processing) best paper award 2022. He is a Fellow of the IEEE and the IET. He is the vice-chair of ETSI Industry Specification Group (ISG) on Multiple Access Techniques (MAT).
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