Workshop

Illinois Institute of Technology, US

Workshop Chair: Prof. Marwan Omar, Associate Professor in Illinois Institute of Technology

The Adversarial Machine Learning workshop is a specialized event that focuses on exploring the challenges and latest developments in the field of adversarial attacks and defenses in machine learning systems. The workshop brings together experts from different disciplines, including machine learning, computer security, and cryptography, to discuss the latest research and advancements in this rapidly evolving field.

The workshop covers a range of topics related to adversarial attacks and defenses, including the latest attack techniques, their impact on machine learning systems, and the development of effective defense mechanisms. Participants will have the opportunity to learn about state-of-the-art techniques for defending against adversarial attacks and explore the latest research and advancements in the field.

The workshop will also include interactive sessions and discussions where participants can exchange ideas and share their experiences in dealing with adversarial attacks. These sessions will provide a forum for participants to collaborate and network with other researchers in the field, helping to build a community of experts dedicated to developing robust machine learning systems.

Overall, the Adversarial Machine Learning workshop is an essential event for researchers and practitioners who want to stay up-to-date with the latest developments and best practices in defending against adversarial attacks in machine learning systems. The workshop will provide a platform for participants to gain new insights, share their experiences, and collaborate with other experts in the field, helping to advance the state-of-the-art in Adversarial Machine Learning.

University of Surrey, UK

Workshop Chair: Prof. Roman Bauer, Lecturer in University of Surrey

On June the 23rd 2023 the workshop "Computational Modeling of Complex System Dynamics" was held in Guildford at the University of Surrey (UK). The workshop was hosted by the COMBYNE lab (www.combynelab.com) and held as a hybrid meeting, to facilitate involvement of participants from many different countries such as UK, Germany, Italy and Spain. This international workshop comprised an eclectic selection of presentations and interactive talks on Computational Biology topics from leading academics and well-established domain experts. Over 20 participants were present, mostly academics and PhD students from institutions such as the University of Surrey, Cambridge University (UK), CERN (Switzerland), the SCImPULSE Foundation (Netherlands), the University of Cyprus and others. Members of the international BioDynaMo collaboration (www.biodynamo.org) also contributed to the workshop.

The workshop started off with an introductory seminar talk that touched on the challenges and prospects of computational modelling in biomedicine. Afterwards, a discussion among the participants elaborated on the relevant issues such as the curse of dimensionality with regards to model parameters, and the need for diversity in computational models. Other talks focussed on topics comprising various complex systems and their dynamics, such as for instance cancer growth, cancer therapy and the visual (neural) system. More information on the workshop including a programme can be found here: CBM23 (google.com).

University of Auckland, New Zealand

Workshop Chair: Prof. Alan Wang, Associate Professor in University of Auckland

The Workshop on Intelligent Computing for Medical Data Analysis is an informative and interactive event dedicated to exploring the utilization of intelligent computing techniques in the analysis of medical data. This workshop, scheduled for Thursday, 13th July 2023, from 14:00 to 16:00, will take place at The University of Auckland's Grafton Campus, specifically in Room 505-212 and will be accessible remotely via Zoom.

The workshop aims to bring together researchers, practitioners, and experts from the fields of intelligent computing, medical research, and healthcare. The primary objective is to foster knowledge sharing, collaboration, and innovation in the application of intelligent computing to analyze medical data, with a particular focus on its potential impact on enhancing healthcare outcomes. Throughout the workshop, attendees will have the opportunity to delve into the latest advancements and trends in intelligent computing techniques tailored to medical data analysis. The agenda features speakers who will present their insights and research findings. Topics include deciphering the intricate structure-function relationship of gut pacemaker cell networks, fMRI data analysis for predicting post-stroke recovery outcomes, connectivity analysis to aid stroke recovery prediction, and multiband fMRI data analysis for ADHD. Each presentation promises to shed light on the application of intelligent computing in the respective medical domains.

The workshop agenda also includes dedicated time for discussions, providing a platform for participants to exchange ideas, share their experiences, and engage in meaningful conversations. The interactive nature of the workshop encourages collaboration and the exploration of innovative approaches to medical data analysis. By the end of the workshop, participants will have gained a deeper understanding of how intelligent computing can be harnessed to analyze medical data. They will be equipped with knowledge about the potential applications and benefits of intelligent computing in enhancing healthcare outcomes, diagnosis, and personalized medicine. Moreover, the workshop offers a unique opportunity for networking and fostering collaborations, driving progress in the field of intelligent computing for medical data analysis.