Woo-Young (Young) Ahn is a Professor in the Department of Psychology at Seoul National University (September 2024 - Present; Associate Professor from September 2019 to August 2024; Assistant Professor from September 2017 to August 2019). He was previously an Assistant Professor in the Department of Psychology and an affiliated faculty at Translational Data Analytics at The Ohio State University (August 2015 - August 2017). He earned his B.S. in materials science & engineering in 2002 from Seoul National University and then went to Harvard University as a doctoral candidate for applied physics and received his S.M. in applied physics in 2003. Due to his interests in the human mind, he decided to change his major to clinical psychology so that he could study the human mind from multiple perspectives. He continued on to receive his M.A. in clinical psychology from Seoul National University in 2006, and his Ph.D. in clinical psychology from Indiana University, Bloomington in August 2012 co-advised by Jerome Busemeyer and Brian O'Donnell. He completed his (APA accredited) clinical psychology internship at the University of Illinois at Chicago (UIC) in June 2012. He worked then as a postdoc with Read Montague and Peter Dayan for two years at Virginia Tech Carilion Research Institute (VTCRI) and for a year at Virginia Commonwealth University Institute for Drug and Alcohol Studies.

When he is outside of the lab, he enjoys playing tennis 🎾 and hitting the gym.

Simon Eickhoff is a full professor and chair of the Institute for Systems Neuroscience at the Heinrich-Heine University in Düsseldorf and the director of the Institute of Neuroscience and Medicine (INM-7, Brain and Behavior) at the Forschungszentrum Jülich. He is furthermore a visiting professor at the Chinese Academy of Science Institute of Automation. Workig at the interface between neuroanatomy, data-science and brain medicine, the he aims to obtain a more detailed characterization of the organization of the human brain and its inter-individual variability in order to better understand its changes in advanced age as well as neurological and psychiatric disorders. This goal is pursued by the development and application of novel analysis tools and approaches for large-scale, multi-modal analysis of brain structure, function and connectivity as well as by machine-learning for single subject prediction of cognitive and socio-affective traits and ultimately precision medicine.

Réka Enz studied Cognitive Science at the University of Osnabrück. She moved to Zürich in 2020 to pursue a Masters Degree in Neural Systems and Computations. Since 2021 Réka has worked in close collaboration with the Translational Modeling Unit, starting as a Research Assisstant, working on her thesis project, and later as a Research Coordinator at UZH and the Schulthess Clinic. She recently started as a doctoral student at the Schulthess Clinic and ETH Zurich focusing on digital medicine for chronic pain patients.

Charlotte Fraza earned her Bachelor's in theoretical physics at Utrecht University followed by a European Master's in Image processing, color science, and computer vision in France (UDL), Spain (UGR), Finland (UEF) and Japan (TUT). Subsequently, she followed with a Master's in Neuroscience, specializing in Natural Computing and Neurotechnology, at Radboud University. Here she is now a PhD candidate under the supervision of Andre Marquand and Christian Beckmann, working on improving the models for individualized predictions of neurological and mental disorders, using machine learning techniques such as normative modeling and autoencoders. Furthermore, she has her own Blog and YouTube channel, discussing several topics in neuroscience and machine learning.

Herman is currently pursuing a PhD at the Translational Neuromodeling Unit. He is interested in the predictive modeling of mental states, especially using large biomedical databases. He hopes to contribute novel developments to the machine learning tools that underly such analyses, as well as demonstrate how they could be useful in clinical practice. Besides research, Herman enjoys bouldering, entrepreneurship, and socializing over (good) food.

Mona is an Assistant Professor of Neuroscience at Julius-Maximilians-University Würzburg, Germany. Her research combines computational modeling, neuroimaging, and neuromodulation to explore how the brain constructs internal models of the world to guide decision-making—and how these processes break down in psychopathology. She earned her PhD from University College London (UCL), followed by a postdoctoral position at the University of Oxford and a senior research position at the Max Planck Institute for Human Cognitive and Brain Sciences. Beyond academia, she spent a year leading the Science Team at Alena, a computational psychiatry start-up, gaining firsthand experience in translating research into real-world applications.

Claire is Professor in Psychology at Trinity College Dublin. She runs a lab that focuses on large-scale clinical and cognitive phenotyping using online methods including the smartphone app her lab developed, Neureka. Her current areas of research focus are compulsivity, model-based planning and habit learning, psychiatric nosology, treatment prediction and metacognition. She has developed methods to advance these areas, including new ways to leverage passively generated data to study cognition and for defining novel transdiagnostic clinical phenotypes. She is Editor in Chief of Current Opinion in Behavioural Sciences, has grant funding from many sources including an ERC Starting Grant, and was Ireland's Early Career Research of the Year in 2022.

Jakob studied Physics at the Swiss Federal Institute of Technology (ETH) in Zürich. During his PhD with Kevan A.C. Martin at the Institute for Neuroinformatics (ETH, Zürich, Switzerland) he developed a layered cortical microcircuit model of the frontal eye fields, a brain region important for the control of eye movement in primates. Jakob then moved to Berlin where he worked with John-Dylan Haynes and developed and applied novel methods to study multivariate and information theoretical aspects of brain connectivity with fMRI. Since 2012, Jakob is a Senior Researcher and Head of Laboratories at the Translational Neuromodeling Unit.

Alex Hess received his Bachelor's and Master's Degrees from ETH where he studied Health Science and Technology and is currently a PhD candidate at the TNU. In his research, Alex investigates the role of brain-body interactions for mental health using computational models of respiratory interoception. Also, he has a general interest in Bayesian Statistics and Causal Inference. In his free-time he enjoys good food in good company and he is a passionate floorball player.

I obtained my Bachlor of Science in Psychology with a minor in General Linguistics from the University of Zurich in 2019. I then completed the prestigious Research Master of Cognitive and Clinical Neuroscience with distinction at Maastricht University in 2022. In my master's thesis, I applied Hidden Semi-Markov modeling to explore EEG brain states associated with auditory verbal hallucinations, which sparked my interest in computational psychiatry. Since 2023, I have been a full-time research assistant at the Tranlational Neuromodeling Unit. In this role, I actively contribute to various projects while continuing to learn about computational psychiatry as well as the administrative aspects of research. Finally, I was one of the main organizers of the Computational Psychiatry Course Zurich 2023.

Imre Kertesz received his Bachelor's and Master's Degree in Information Technology and Electrical Engineering from ETH Zurich and is currently a doctoral student at the Translational Neuromodeling Unit. In his research he is developing generative models of whole-brain connectivity. In his free time he enjoys 3D printing or playing the violin.

Miriam Klein-Flügge is an Associate Professor, Wellcome Trust Sir Henry Dale and UKRI-ERC fellow at the Departments of Experimental Psychology and Psychiatry and the Wellcome Centre for Integrative Neuroimaging at the University of Oxford. Her research group studies human cognitive processes, with a particular focus on motivation and decision making. She has extensive experience with neuroimaging and neuromodulation approaches. Her long-term vision is to conduct fundamental research that provides a platform for translation to psychiatric disease.

I am an assistant professor at Aarhus University working under the supervision of Chris Mathys where I use nonparametric predictive coding to study the formation of delusions. From 2019 to 2022, I was a postdoctoral fellow in the Embodied Computation Group at Aarhus University, where I developed novel tasks to measure cardiac interoception using Bayesian psychophysics. I am the creator and maintainer of several Python packages for physiological signal analysis, psychophysics, predictive coding neural networks and computational models of learning and metacognition.

Andre Marquand is a computational neuroscientist interested in the development of novel statistical techniques for neuroimaging data, aiming to further the understanding of human brain function. He has a particular focus on machine learning techniques that aim to learn to detect patterns of statistical regularity in empirical data. These methods hold significant promise for decoding cognitive states and predicting clinically relevant variables in health and disease.

Chris Mathys is Professor of Cognitive Science at Aarhus University in Denmark and a TNU alumnus. His group's research is focused on the creation of computational models of behaviour and brain function, with a recent emphasis on the modelling of delusions. As a graduate student, Chris developed hierarchical Gaussian filtering (HGF), a modelling approach that allows for the automatic, principled, and agent-specific adjustment of learning rates in rapidly changing environments. This enables the quantification of individual differences in learning, inference, and decision-making. In addition to his original background in physics and information technology, Chris has a degree in Psychology and Psychopathology and has completed post-graduate training as a clinical psychologist.

Adeel Razi is a Professor of Computational Neuroscience at Monash University, Australia. He leads a cross-disciplinary lab integrating engineering, physics, and machine learning to address neurobiological questions. His research focuses on statistical methods for neuroimaging data, particularly state-space modelling, Bayesian statistics, and dynamical systems. He has advanced Dynamic Causal Modelling for resting-state fMRI. His work is published in top journals like Nature Human Behaviour, Nature Reviews Neuroscience and Neuron, and featured in media such as The Guardian, BBC, and The Age. He joined Monash after a postdoc at UCL's Wellcome Centre for Human Neuroimaging and holds degrees (BE, MSc and PhD) in Electrical Engineering from NED University (Pakistan), RWTH Aachen (Germany), and UNSW (Australia).

I am currently a postdoctoral researcher at the Donders Institute, where I focus on harmonizing cognitive scales across databases to improve prediction of schizophrenia outcomes. My work draws on my background in artificial intelligence, statistics, and computational biology. I completed my Ph.D. at the Czech Technical University in Prague, where I developed methods for multi-modal neuroimaging data analysis. Throughout my career, I've contributed to national health initiatives in the Czech Republic and have been grateful for support from grants such as the Fulbright Fellowship at the University of Pennsylvania.

I received my bachelor's degree in engineering sciences from the Technical University of Munich (TUM) in 2018 and passed the elite master's degree in neuroengineering (TUM) with honours in 2022. Between 2018 and 2021 I was employed at the Institute for Cognitive Systems (TUM) where I worked on adaptive machine learning algorithms for the decoding of neuronal signals in brain-computer interfaces. In my master thesis I worked on interpretable machine learning methods in hearing diagnostics using Bayesian Inference in a joint project between the University of Tübingen, the Harvard Medical School and the TUM. Since 2022 I am part of the Translational Neuromodeling Unit where I focus on the development of mechanistic models of the insular cortex as well as EEG and MEG data analysis.

Dr. Smith holds master's degrees in Neuroscience and Philosophy, as well as a Ph.D. in Psychology, each completed at the University of Arizona (UA). He did postdoctoral work with Drs. Scott Killgore and Richard Lane at the UA Psychiatry Department and with Dr. Karl Friston at University College London. In 2019, he accepted a faculty position at the Laureate Institute for Brain Research (LIBR). He is currently a Principal Investigator at LIBR and Research Associate Professor at the University of Tulsa. Dr. Smith's work focuses on computational mechanisms of interoception, emotion, and decision-making in individuals with anxiety, depression, and substance use disorders. His specific interests relate to how brain-body interactions during emotional responses influence information-seeking and multi-step planning, and how these mechanisms may be altered within affective disorders.

Klaas Enno Stephan is a computational neuroscientist and medical doctor. He is Full Professor for Translational Neuromodeling & Computational Psychiatry at the University of Zurich and ETH Zurich. His scientific work covers the entire translational pipeline, from the development of disease theories via the creation of computational methods to their application in clinical studies. A central goal is the development of clinically useful “computational assays” for psychiatry and psychosomatics. Based on generative models of brain activity and behaviour, the hope is that such assays will support more precise diagnostics and individualized treatment recommendations, leading to a transformation of clinical practice and redefinition of mental diseases. Current research foci include psychosis and brain-body interactions in fatigue and depression. In order to enable the clinical validation of his work, Klaas founded the Translational Neuromodeling Unit (TNU) at Zurich, an interdisciplinary institution with the mission to translate advances in computational neuroscience into tools for clinical practice. The TNU assembles computational scientists and clinicians under one roof and operates a dedicated research clinic for evaluating the diagnostic and prognostic utility of computational assays in prospective patient studies.

Peter Thestrup Waade is a PhD candidate in Cognitive Science at Aarhus University. He works with computational modeling, especially within predictive processing, and applies it to social coordination. He has developed the Julia software for the Hierarchical Gaussian Filter and works continuously on its development. He also works within active inference and computational psychiatry, as well as motion capture and movement synchrony, applied to partner dancing.

Ashley is a postdoctoral researcher in the Embodied Computation Group (ECG) at Aarhus University, Denmark. Her research interests focus on the effects of noradrenaline on uncertainty and decision-making, and how these may be compromised in neurodevelopmental disorders such as ADHD. She recently completed a large-scale within-subject MEG study investigating the effects of central versus peripheral noradrenergic perturbation on predictive processing, interoception, and metacognition.

Before moving to Denmark, Ashley completed her PhD as part of the Wellcome Trust Neural Dynamics PhD Programme at the University of Bristol, UK, with Prof Rosalyn Moran, during which she applied both Dynamic Causal Modelling of EEG and fMRI data, and Active Inference modelling of behavioural data.

Lilian is a postdoctoral researcher in the Motivation, Decision and NeuroStimulation (MoDeS) lab at the University of Oxford. She studies how we form and update beliefs about the world and ourselves in changing environments, how belief updating and decision making depends on neurochemistry, and how it changes across mental health conditions. To that end, she combines computational models with measures of behaviour and brain function and non-invasive brain stimulation (focussed ultrasound).

Prior to coming to Oxford, she completed her PhD in Translational Neuromodeling with Klaas Enno Stephan and Frederike Petzschner at the ETH Zurich in Switzerland. There, she used hierarchical Bayesian models, pharmacology, and EEG to understand how we process sensory signals in the auditory and in the interoceptive domain. Lilian holds a German diploma (MSc) in psychology and a BSc in physics, both from the Philipps University Marburg in Germany.