Prof. Mandic received the Ph.D. degree in nonlinear adaptive signal processing in 1999 from Imperial College, London, U.K., where he is now a Professor. He specializes in Statistical Learning Theory, Machine Intelligence, and Statistical Signal Processing, and their applications, especially in Biomedicine and Finance.

He is a pioneer of Hearables (in-ear sensing of neural function and vital signs), an unobtrusive, discreet, and long-term wearable solution for physiological monitoring based on miniaturized sensors embedded in an earplug, an area where he holds several patents. He also specializes in Machine Intelligence for Finance and is a Director of the AIDA Lab at Imperial.

He has written over 600 journal and conference articles and research monographs on Recurrent Neural Networks (Wiley, 2001), Complex-valued Adaptive Filters and Neural Networks (Wiley, 2009), Tensor Networks for Dimensionality Reduction and Large Scale Optimization (Now Publishers, 2017), and Data Analytics on Graphs (Now Publishers, 2021).

Prof. Mandic is a Fellow of the IEEE, the 2019 recipient of the Dennis Gabor Award for "Outstanding Achievements in Neural Engineering," given by the International Neural Networks Society (INNS). He is also a 2018 winner of the Best Paper Award in IEEE Signal Processing Magazine for his article on Tensor Decompositions for Signal Processing Applications and the 2021 winner of the Outstanding Paper Award at the IEEE ICASSP conference. He is also a winner of the 2023 IEEE Engineering in Medicine and Biology Prize Paper Awards and has coauthored six more award-winning articles. He is a Core Member of the Machine Learning Initiative at Imperial.

Danilo served as the President of the International Neural Networks Society and a past Technical Chair of ICASSP 2019, held in Brighton, U.K. He also received the President's Award for Excellence in Research Supervision at Imperial College in 2014. Danilo is passionate about cross-disciplinary aspects of his work and about bringing research into the curriculum. His current research interests are Adaptive Learning Theory, Big Data, Machine Learning on Graphs, Neural Networks, and Complexity Science, and their applications in Biomedicine and Financial Engineering.

Anthony G. CONSTANTINIDES FREng FIET is a Professor of Signal Processing and the creator of the Communications and Signal Processing Group of the Department of Electrical and Electronic Engineering at Imperial College London. He has been actively involved with research in various aspects of digital filter design, digital signal processing, and communications for more than 45 years. Professor Constantinides' research spans a wide range of digital signal processing and communications, both from the theoretical as well as the practical points of view. His recent work has been directed toward the demanding problems arising in financial signal processing.

Professor Constantinides has published several books and over 400 papers in learned journals in the area of digital signal processing and its applications. He has served as the first President of the European Association for Signal Processing (EURASIP) and has contributed in this capacity to the establishment of the European Journal for Signal Processing. He has been on, and is currently serving as, a member of many technical program committees of the IEEE, the IEE, and other international conferences. He has organized the first-ever international series of meetings on digital signal processing, in London initially in 1967, and in Florence (with Vito Cappellini) since 1972.

In 1985 he was awarded the Honour of Chevalier, Palmes Academiques, by the French government, and in 1996, the promotion to Officier, Palmes Academiques. He holds honorary doctorates from European and Far Eastern universities, several visiting professorships, distinguished lectureships, fellowships, and other honours around the world.

Professor Constantinides has acted as an advisor to many organizations and governments on modern technology and development. He has served on professorial selection committees around the world (15 during the last five years), as a member of IEE/IEEE awards committees, EU university appraising panels, and chair (or co-chair) of international conferences.

He is a Fellow of the Royal Academy of Engineering, a Life Fellow of the Institute of Electrical and Electronics Engineers (USA), and of the Institution of Electrical Engineers (UK).

Arta holds an MSc degree in Communication and Signal Processing and a PhD degree, both from the Department of Electrical and Electronic Engineering at Imperial College London. The focus of his PhD thesis was on the optimization of distributed algorithms.

Currently, he is a Partner at Accrete, an alternative investment platform that works with trusted, tenured sponsors to unlock private markets for the many. Accrete uses its own investing power, relationships, and technology to provide access to opportunities that were previously only available to institutional investors and family offices.

He is also a co-founder of Stable, a global consulting enterprise across London and New York that specializes in Operations, Finance, and Online Growth, finding pockets of inefficiencies in organizations and refocusing them for growth. Clients include private equity growth investment firms and their portfolio companies.

Arta serves as the special advisor to the director at the Simons Laufer Mathematical Sciences Institute (SLMath), formerly known as the Mathematical Sciences Research Institute (MSRI), one of the world’s preeminent centers for collaborative research in mathematics.

Previously, he co-founded the AIDA Finance Lab, formerly known as the Financial Signal Processing Lab, in the EEE Department, where he conducted research in quantitative finance using engineering techniques such as signal processing, machine learning, optimization, and network science. He was also one of the directors of the Algorithmic Trading Group, a student-led group within the Imperial College Finance Society, which focused on research in quantitative finance and organizing seminars for academics and professionals both at Imperial College London and in the City.

Giorgos holds an MEng in Electrical and Electronic Engineering from Imperial College London with a year abroad at MIT, where he graduated with First Class Honours and was ranked 2nd overall in his cohort. He is currently a PhD student at AIDA Lab under the supervision of Prof. Mandic, where his research focuses on developing computationally efficient, explainable, and domain-specific LLMs, specifically for finance and healthcare.

Wuyang is a PhD student at AIDA Lab, supervised by Prof. Mandic. He received his MEng in Electrical and Electronic Engineering from Imperial College London with First Class Honours and Dean’s List award, where he also served as the academic representative for two consecutive years. His research focuses on creating computationally efficient and interpretable multi-linear tensor frameworks and neural network models for financial and healthcare applications.