WAALIS 2026

Lecturer and Senior Research Scientist - Newcastle University

Harold Fellermann is a committed and creative computational scientist working at the intersection of academia and industry. He is a Lecturer in Molecular Computing and Nanoscience in the Interdisciplinary Computing and Complex Biosystems Research Group at Newcastle University. He has more than ten years of experience in developing and applying computational design, modelling, and analysis techniques to problems in molecular biology, synthetic biology, and DNA nanotechnology. More broadly, he brings over 18 years of experience applying mathematics and computer science to chemistry and nanotechnology.

He received his PhD in Applied Systems Science in 2009 from the University of Osnabrück, Germany, and subsequently worked as a Postdoctoral Research Associate at Los Alamos National Laboratory (NM, USA) and the University of Southern Denmark (Odense), before joining Newcastle University in 2014. He is a Fellow of the European Center for Living Technology in Venice, Italy, and a member of the Board of Directors of the International Society of Artificial Life. His research focuses on molecular computing and the design and analysis of in vitro and in vivo DNA-based computing systems, including the modelling and evaluation of nanoscale information-processing systems.

ML Research Engineer - Bandai Namco Studios Inc., Japan

Christoph Senn is a machine learning research engineer working at the intersection of applied machine learning and artificial life. He is currently based in Tokyo, where he develops neural simulation and rendering systems for game production at Bandai Namco Studios. He received his Doctor of Engineering from Tokyo Institute of Technology, where his research focused on nonlinear dynamical systems and reservoir computing. This background continues to shape how he approaches machine learning problems involving temporal structure, learned dynamics, and simulation.

His work combines applied machine learning with ideas from artificial life, including neural Lindenmayer systems, differentiable simulation, and learned world models. In this setting, models are treated as dynamical systems that evolve over time, enabling both prediction and interaction within simulated environments. He is particularly interested in how structured generative processes can be integrated with data-driven learning to produce coherent temporal behaviour. Across both academia and industry, he focuses on building practical systems that translate these ideas into usable tools. His current work includes neural rendering and simulation-driven models for interactive environments, with an emphasis on supporting creative workflows in game development.