We come from different backgrounds and bring different skillsets, but we are interested in solving similar problems.

Principal Investigator

Dr. Andreea Diaconescu

Dr Andreea Diaconescu is an Independent Scientist at the Krembil Centre for Neuroinformatics at CAMH and Assistant Professor in the Department of Psychiatry at the University of Toronto with cross-appointments with the Institute of Medical Science and the Department of Psychology at the University of Toronto and member of the Max Planck-University of Toronto Centre for Neural Science and Technology.

Before this, she was a Swiss National Foundation Ambizione fellow and Junior Group Leader at the University in Basel, Department of Psychiatry leading a project on early detection and treatment of psychosis using mathematical modelling. After completing her PhD in cognitive neuroscience at the Rotman Research Institute, University of Toronto, Dr. Diaconescu held a postdoctoral position at the Translational Neuromodeling Unit, University of Zurich and ETH Zurich. There, she developed and applied computational models of learning and decision-making to understand the emergence and persistence of delusions in psychoaffective disorders such as schizophrenia.

Areas of Research:
Dr. Diaconescu has developed and validated mathematical models that infer subject-specific disturbances of information processing in neuronal circuits from neuroimaging, electrophysiological, and behaviour measures. She also has expertise in whole-brain, multimodal neuroimaging analysis methods. Dr. Diaconescu’s research is centered on the clinical validation of (neuro)computational models of learning and decision-making for predicting psychosocial functioning and treatment response in individuals at clinical high risk for psychosis. Moreover, Dr. Diaconescu is engaged in the identification of cognition- and neuroimaging-based transdiagnostic predictors of suicidality.

Postdoctoral Fellow

Dr. Povilas Karvelis

Dr. Povilas Karvelis is a Postdoctoral Research Fellow at the Krembil Centre for Neuroinformatics at CAMH. He completed his PhD at the Institute of Adaptive and Neural Computation at the University of Edinburgh. Prior to his doctoral studies, Povilas obtained an MSc in Computational Cognitive Science at the University of Edinburgh and an MSci in Physics and Astrophysics at the University of Birmingham. His current work centers on the development, validation, and clinical translation of computational assays for mental disorders. Computational assays, which combine cognitive tasks with computational models of cognition, enable inferring on latent brain computations and could become a new basis for personalized psychiatry. However, for the assays to be sufficiently informative at the level of individual, they must exhibit excellent psychometric properties: reliability and construct validity. In other words, they must provide precise, accurate, interpretable, and actionable measures – these are the challenges that Povilas aims to highlight and address in his work. When it comes to clinical conditions, his recent work includes developing a model of vulnerability to suicidality grounded in Active Inference (a normative framework characterizing Bayes-optimal cognition and behavior in living organisms). This work spans behavioral, cognitive, and neural levels of analysis and formalizes vulnerability to suicidality in computational terms. Importantly, the model generates testable hypotheses and offers insights into anti-suicidal and anti-depressant effects of psychedelic-assisted therapies.

PhD Student

Pamina Laessing

Pamina Laessing received her B.Eng. and M.Sc. in Engineering Physics with a focus on Machine Learning and Optimization from the University of Oldenburg in Germany in 2018 and 2021, respectively. Now, she is a doctoral student at the Max Planck – University of Toronto Centre (MPUTC) for Neural Science and Technology under the joint supervision of Dr. Andreea Diaconescu in the CogNeMo group at the Krembil Centre for Neuroinformatics and CAMH and Dr. Peter Dayan at the Max Planck Institute for Biological Cybernetics. Pamina is broadly interested in employing Machine Learning concepts to understand human behaviour and decision making. In the CogNemo group, Pamina works on formulating and validating biologically informed computational models of suicidality. Integrating Active Inference and Reinforcement Learning frameworks with fMRI data, the research aims to advance our theories about pathological behaviours observed in individuals with suicidal tendencies as well as the involvement of underlying neuromodulatory systems. The larger goal of the project is to develop a refined mechanistic understanding of suicidal thoughts and behaviours with the potential to improve early detection in individuals at risk through the identification of biomarkers and develop customized interventions.

PhD Student

Milad Soltanzadeh

Milad Soltanzadeh earned his bachelor’s and master’s degrees in electrical engineering from the University of Tehran and Concordia University, respectively. His research background includes development of biophysical models for brain metabolism and application of machine learning algorithms on EEG signal’s features in patients with epilepsy. Currently pursuing a Ph.D. at the University of Toronto’s Institute of Medical Science under the supervision of Dr. Andreea Diaconescu, Milad is engaged in developing large-scale neurocomputational models that incorporate conductance-based and Jansen-Rit models to study brain activity and connectivity in the context of psychosis and the antidepressant effects of psychedelics. The final goal of the project is to provide a computational framework to advance our understanding of underlying mechanisms and to predict treatment response in treatment-resistant depression and schizophrenia.

Master's Student

Gabrielle Allohverdi

Gabrielle Allohverdi obtained a BSc, with a major in biology and a minor in psychology in 2020 from the Western University in London Ontario. During her undergraduate years, Gabrielle completed coursework in neuroscience, neuroimaging data analysis and the psychology of altered states of consciousness. She spent time as a research assistant under Dr. Elizabeth Hayden studying the effect of maternal psychiatric diagnosis on child affect, and Dr. Graham Reid whose lab focuses on access and use of services for youth with mental health diagnoses. Currently, Gabrielle is enrolled in a MSc program in the Institute for Medical Science at the University of Toronto. Gabrielle is working on a project that investigates the effect of psychedelics on sensory learning in the brain. She is interested in the application of generative models of learning to non-invasive neuroimaging data to understand the antidepressant effect of ketamine and psilocybin. Additionally, she is interested in ketamine as a model of prodromal psychosis, looking for patterns between the symptomatology of psychosis and the dissociative state under ketamine.

Master's Student

Jason Yang

Jason Yang earned his BSc in Neuroscience and Physiology from the University of Toronto in 2020. He is now pursuing a MSc from the Institute of Medical Science, also at the University of Toronto. Jason’s research focuses on the negative symptoms of schizophrenia. Currently, his project looks at amotivation in schizophrenia, where he employs Bayesian inference models of exploratory behavioral data to derive insight into the underlying mechanism of amotivation. Beyond academia, Jason manages a non-profit organization (Saturday Program – St. George Campus) that pairs university students with high school students from marginalized communities for academic and mentorship support. Likewise, in his leisure time, he enjoys competing in the sport of dragon boat at the university level.

Research Methods Specialist

Dr. Zheng Wang

Zheng Wang is a Research Method Specialist working with both Dr. Andreea Diaconescu and Dr. John Griffiths. Following the completion of his Ph.D. in Control Theory from the Department of Mechanical Engineering at the University of Calgary, Dr. Wang undertook several postdoctoral positions at the University of Toronto and the Stevens Institute of Technology. His research at these institutions was primarily focused on consensus mechanisms in large network systems and bifurcation phenomena in power networks. Introduced to the field of brain network modeling by Dr. Randy McIntosh, Dr. Wang transitioned into this field after assuming a role as a research technician at Baycrest Hospital. His current research interests are centered on identifying neuro-behavioral biomarkers through the integration of neural and behavioral computational models. This multidisciplinary approach seeks to elucidate the underlying mechanisms responsible for brain disorders, thereby aiding in both diagnosis and the identification of potential intervention targets.

PhD Student

Yi-An Chen

Yi-An Chen is a PhD student in the Department of Psychology of the University of Toronto. She received her M.D. from the National Yang-Ming University in Taiwan and became a licensed physician in 2014. In addition to clinical training, Yi-An was also a trainee of the Physician Scientist Program and had participated in pre-clinical research of cellular electrophysiology during her undergraduate years. She chose the academic path afterwards, first working as a research assistant at the Department of Psychology of the National Taiwan University where she focused on building neural biophysical models and applying machine learning to psychiatric prescription data-base, then joining the Institute of Medical Device and Imaging where she completed her master’s research integrating MR physics and biophysical modeling under the supervision of Professor Wen-Yih Isaac Tseng. Yi-An’s research interest encompasses MRI, neural electrophysiology, and psychiatry. Currently she works in the field of suicidology where she develops novel tasks to probe cognitive processes potentially relevant to suicide and optimizes MRI techniques to better characterize the underlying neuromodulatory processes.”