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.

I am a Professor of Neuroscience and Psychiatry at the University of Newcastle, Group Leader of the Systems Neuroscience Group at the Hunter Medical Research Institute and consultant psychiatrist at the Awabakal Aboriginal Medical Service, Newcastle. I lead a multi-disciplinary program that models large-scale systems of the brain, bridging from mathematical foundations to clinical translation. In most organ systems, scientific understanding of molecular and cellular processes has led to better treatments. However, this has not held true for the brain and psychiatric disease. Despite our substantial understanding of the neuron, we do not understand the systems-level rules of the brain and how they breakdown in brain disorders. Drawing on mathematics, psychiatry and neuroscience, I study systems-level models of brain disorders, using these to shed light on disease mechanisms and provide new diagnostic and prognostic tools.

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.

Carter Goldman is an incoming Neuroscience PhD student at the University of Sussex. His research focuses on how humans and machines form generative models of the world. For humans, he is particularly interested in whether neural activity supports inference through message-passing or sampling algorithms. For machines, he aims to improve the efficiency of machine learning systems by incorporating principles from brain-inspired frameworks, such as predictive coding.

Carter earned his B.A. in Computer Science from the University of North Carolina at Chapel Hill, graduating with highest distinction. Following graduation, he joined Dr. Ryan Smith's Computational Psychiatry Lab at the Laureate Institute for Brain Research, working full-time as a research specialist. His work centered on developing computational models of decision-making to investigate how affective states and traits influence cognition. He has applied a variety of modeling approaches—including reinforcement learning, active inference, and stochastic evidence accumulation—to help uncover the computational mechanisms underlying psychiatric disorders such as anxiety and depression.

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.

Jooyeon Jamie Im is a Ph.D. student in the CCS lab at Seoul National University (Sep 2022 - Present). She received her B.A. in psychology from Boston University and M.S. & Ph.D. in neuroscience from Seoul National University. She worked as a postdoctoral fellow from Feb 2021 to Aug 2022 in the CCS Lab and decided to pursue her second Ph.D. in clinical psychology. Previously, her research focused on investigating the neurobiological mechanisms of mental disorders using neuroimaging and noninvasive brain stimulation methods. More recently, she became interested in the role of interoception in mental disorders. Currently, she is exploring how interoception and beliefs about interoception influence addiction using behavioral, psychophysical, and computational modeling approaches. Through this work, she aims to deepen the understanding of interoceptive processes to inform more effective interventions for addiction and related mental disorders.

Alexandra earned her Bachelor of Science in Psychology from the University of Zurich in 2019, followed by a Research Master in Cognitive and Clinical Neuroscience at Maastricht University, which she completed in 2022. In her master's thesis, she used Hidden Semi-Markov Models to investigate EEG brain states linked to auditory verbal hallucinations, which sparked her interest for computational psychiatry. This led her to the Translational Neuromodeling Unit (TNU), where she joined as a Research Assistant and became a core organizer of the Computational Psychiatry Course. After nearly two years at the TNU, Alexandra recently began her PhD there, focusing on digital health solutions for patients experiencing chronic fatigue. In parallel, she is pursuing the MAS ETH in Digital Clinical Research.

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.

Prof Nikolaos Koutsouleris is the Coordinator of the EU-FP7 funded project PRONIA ("Personalised Prognostic Tools for Early Psychosis Management"). He serves as consultant and Head of the Centre for Adolecent Psychiatry and Transitional Youth Mental Health and the Section for Precision Psychiatry, Ludwig-Maximilian-University, Munich (LMU). He also leads the group for Artificial Intelligence in Mental Health at the Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London. Dr. Koutsouleris studied medicine at LMU between 1996 and 2003 as scholar of the German National Academic Foundation. He took his first medical & academic appointment in 2004 at the Department of Psychiatry and Psychotherapy, where he finished his doctorate thesis in 2005. Since 2008, Prof Koutsouleris has advanced the use of multivariate pattern recognition methods for the identification and validation of diagnostic and prognostic prediction models in at-risk and early stages of affective and non-affective psychoses. His work was awarded with several national and international prizes and led so far to 205 peer-reviewed, highly cited papers. In addition, he strived to make robust machine-learning methods available to researchers in the clinical neurosciences in order to improve the methodological rigour of this new research direction based on the proper use of validation and model sharing approaches. These efforts have the lead to the publication of the open-source NeuroMiner machine learning platform available at http://www.proniapredictors.eu/neurominer/index.html.

Jeung-Hyun is a graduate student in the CCS Lab (March 2020-Present). She recently completed her MA at CCS Lab (Feb 2022). She received a Bachelor's degree in Psychology and Public Governance & Leadership from Korea University (Feb 2020). Jeung-Hyun is interested in computational psychiatry and decision neuroscience. In particular, her research investigates how humans make maladaptive decisions under stress and how they are implicated in certain psychiatric conditions. To this end, she aims to bridge clinical science with neuroscience and computational approaches.

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.

Matthew Nassar is an Assistant Professor in the Department of Neuroscience at Brown University. He received his BA at Colgate University and his Doctorate from the University of Pennsylvania. He completed post-doctoral training at the University of Pennsylvania and Brown University before joining faculty at Brown. His research focuses on understanding how the brain flexibly processes information to achieve complex and adaptive behaviors.

Inês Pereira studied Medicine at the NOVA Medical School of Lisbon and at the Charité Universitätsmedizin Berlin. She continued working in Berlin as a Neurology resident. She further obtained her MSc Degree in Neural Systems and Computation in 2020 at UZH and ETH Zurich and is currently a doctoral student at the TNU.

Inês works on mathematical models of brain connectivity using mostly fMRI data. Her projects at the TNU involve both model development as well as model application on specific patient populations. She is interested in particular in furthering our understanding of the pathophysiology of fatigue, and has been working with people affected by multiple sclerosis.

Apart from research, Inês also thoroughly enjoys the outdoors, including splitboarding, biking and sailing.

Dr. Frederike Petzschner is an Assistant Professor at the Carney Institute for Brain Science at Brown University. She is also a director of the Carney Brainstorm Program that accelerates the translation of computational brain science to clinical applications and commercialization. Prior to this, Frederike worked at the Translational Neuromodeling Unit at the University of Zurich and ETH Zurich with Prof. Klaas Enno Stephan. Her research focus is human perception and mental health: She uses mathematical models in combination with behavior and brain imaging to understand brain-body and brain-world interactions in the healthy population and in patients suffering from psychosomatic symptoms, Disordered Gambling, Obsessive-Compulsive Disorder and Chronic Pain.Before coming to Zurich, Frederike received a Master with Honors degree in Physics at the University of Würzburg and a PhD with Stefan Glasauer in systemic Neuroscience at the LMU Munich. She graduated both programs of the Bavarian Elite Network with the highest possible distinction.Besides her academic interest, Frederike is a member of the national council for digital ecology in Germany (Rat für digitale Ökologie), an alumni of the WEF Global Shapers.

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.

Clara is a 3rd year PhD candidate in the Precision Psychiatry working group at Ludwig-Maximilians-Universität München and a junior member of the Munich Center for Machine Learning (MCML). She specializes in multimodal machine learning in psychiatry, integrating neuroimaging, genetics, childhood trauma, and behavioral data to identify transdiagnostic signatures of risk and resilience in psychiatric disorders. Her research focuses on improving early diagnosis and individual outcome prediction in early-stage mental illness, with an emphasis on model interpretability and clinical translation. She also contributes to the development of the NeuroMiner toolbox and helps organize the NeuroMiner summer school.

Clara holds an MSc Research in Psychology & Behavioral Data Science from the University of Amsterdam and previously studied Psychology and Computer Science at the University of Freiburg. She has been involved in international research collaborations, including a research stay at the University of Hong Kong, and brings experience from working in IT start-ups. Next to her academic work, she is actively engaged in making AI accessible to younger audiences and contributes to educational initiatives for high school students at the MCML.

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.

Roland von Känel, MD, is Chair of Consultation-Liaison Psychiatry and Psychosomatic Medicine at the University of Zurich and Director of the Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine at the University Hospital Zurich. He is an internist, psychiatrist and psychotherapist, specialized in psychosomatic medicine. His research interests include biobehavioral pathways linking psychological stress with cardiovascular disease and persistent somatic symptoms.