With the main goal of broadening the participation of researchers in sibling communities, such as physics, computer science, economics, and neuroscience, facilitating the exchange of ideas between other fields and information theory and enriching the experience of regular attendees, ISIT2024 will host satellite workshops.
The five workshops are:
Coding Theory and Algorithms for DNA-based Data Storage
Organizers: Rawad Bitar, Dave Landsman, Antonia Wachter-Zeh, Eitan Yaakobi
This workshop will focus on coding theory and algorithms for DNA-based data storage. It will consist of invited and contributed talks, as well as poster presentations from researchers and experts.
Information-Theoretic Methods for Trustworthy Machine Learning (IT-TML)
Organizers: Shahab Asoodeh, Flavio Calmon, Oliver Kosut, Lalitha Sankar
The ISIT 2024 Workshop on Information-Theoretic Methods for Trustworthy Machine Learning (IT-TML) aims to establish a platform where researchers and engineers can come together to address the challenges and propose solutions pertaining to the responsible deployment of ML in applications of social consequence, with a particular focus on privacy and fairness.
Learn to Compress
Organizers: Elza Erkip, Ezgi Ozyilkan, Aaron Wagner
This workshop is inspired by the belief that data compression, foundations of which are rooted in information theory, is on the brink of a significant transformation. The emergence of deep generative models, like variational autoencoders, generative adversarial networks (GANs), normalizing flows, and diffusion models, has opened up a fresh path for data compression, one that fully taps into the power of machine learning. These methods demonstrate impressive capabilities, particularly with image and video data, yet challenges remain for practical applications.
NeurIT: Information Theory in Neuroscience and Neuroengineering
Organizers: Zoran Cvetkovic, Pulkit Grover, Amanda Merkley
Neuroscience and neuroengineering are at a cusp today, poised to have a deep impact on our society. The goal of the workshop is to be a catalyst in broadening and deepening information theory’s role in answering key questions in clinical and fundamental neuroscience and neuroengineering. This will in turn contribute to continued growth of information theory by both formulating new fundamental questions as well as broadening its application domain.
Quantum Information Knowledge (QuIK)
Organizers: Priya Nadkarni, Narayanan Rengaswamy, Bane Vasic
The goal of this first edition of the workshop is to provide foundational knowledge in quantum error correction (QEC) for fault-tolerant quantum computing (FTQC), complement that with exciting talks by invited speakers working in this area, foster discussions on key open problems, both foundational and practical ones, and discuss some of the latest results in the field.