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Our lab provides a space to learn and to grow as a brain scientist! We welcome people from different academic backgrounds (e.g., psychology, neuroscience, computer science, data science, mathematics/statistics, physics, biology, economics etc.). We believe that psychology will benefit a great deal from being more interdisciplinary.
Our lab provides a space to learn and to grow as a brain scientist! We welcome people from different academic backgrounds (e.g., psychology, neuroscience, computer science, data science, mathematics/statistics, physics, biology, economics etc.). We believe that psychology will benefit a great deal from being more interdisciplinary.
The current lab members are familiar with tools in data science (R, Python, Matlab, shell), signal processing, statistical modelling, machine learning and/or neuroimaging. They have picked up and trained each other these tools while studying humans' brain and behaviours. We have had people from New Zealand (both Māori and tauiwi), Russia, Iran, Thailand, China, the Netherlands, Taiwan, Brazil and Malaysia!
The current lab members are familiar with tools in data science (R, Python, Matlab, shell), signal processing, statistical modelling, machine learning and/or neuroimaging. They have picked up and trained each other these tools while studying humans' brain and behaviours. We have had people from New Zealand (both Māori and tauiwi), Russia, Iran, Thailand, China, the Netherlands, Taiwan, Brazil and Malaysia!
Postdoc : Alina Tetereva, PhD
Postdoc : Alina Tetereva, PhD
Alina has a strong background in neuroimaging with several papers published in this area. Co-supervised by John Dalrymple-Alford and Tracy Melzer at NZBRI and University of Catervury, Alina is now working on predictive models using multimodal MRI and EEG in Parkinson's.
Alina has a strong background in neuroimaging with several papers published in this area. Co-supervised by John Dalrymple-Alford and Tracy Melzer at NZBRI and University of Catervury, Alina is now working on predictive models using multimodal MRI and EEG in Parkinson's.
Postdoc: Chen Zheng, PhD
Postdoc: Chen Zheng, PhD
Chen is a computer scientist. Co-supervised by Jeremiah Deng, he is now working on various deep learning methods to transfer information across different neuroimaging datasets.
Chen is a computer scientist. Co-supervised by Jeremiah Deng, he is now working on various deep learning methods to transfer information across different neuroimaging datasets.
Assist. Research Fellow: Jack Scott, PhD
Assist. Research Fellow: Jack Scott, PhD
Jack has a background in animal neuroscience and machine learning. Jack is now working on longtitudinal predictive models from multimodal MRI and EEG in ADHD children.
Jack has a background in animal neuroscience and machine learning. Jack is now working on longtitudinal predictive models from multimodal MRI and EEG in ADHD children.
PhD Student: Yue Wang, MS
PhD Student: Yue Wang, MS
Yue is a statistician with Master's and Honours degrees in statistics. Yue has been a go-to person for statistical modelling. Co-supervised by A/Prof Matthew Parry in Stats and A/Prof Jeremiah Deng in School of Computing, Yue is now working on predictive inference for neuroimaging big data and statistical genetics with twins.
Yue is a statistician with Master's and Honours degrees in statistics. Yue has been a go-to person for statistical modelling. Co-supervised by A/Prof Matthew Parry in Stats and A/Prof Jeremiah Deng in School of Computing, Yue is now working on predictive inference for neuroimaging big data and statistical genetics with twins.
PhD Student: Irina Buianova, MS
PhD Student: Irina Buianova, MS
Irina has a strong background in biology and diffusion imaging. Co-supevised by A/Prof Jeremiah Deng in School of Computing, Irina is now working on big data in cognition, mental health and brain.
Irina has a strong background in biology and diffusion imaging. Co-supevised by A/Prof Jeremiah Deng in School of Computing, Irina is now working on big data in cognition, mental health and brain.
PhD Student: Farzane Lal Khakpoor, MS
PhD Student: Farzane Lal Khakpoor, MS
Farzane is interested in computational modelling in psychology. Co-supervised by Prof Neil McNaughton, Farzane is working on creating neuroimaging analysis pipelines in Python.
Farzane is interested in computational modelling in psychology. Co-supervised by Prof Neil McNaughton, Farzane is working on creating neuroimaging analysis pipelines in Python.
Research Assistant Superhero:
William van der Vliet
Research Assistant Superhero:
William van der Vliet
William is a Unix guru and has done tremendous work, running jobs over the national-wide cluster: New Zealand eScience Infrastructure (NeSI). He is also completing a year-long project on applying 3D-Convolutional Neural Network on fMRI data, cosupervised by Lech Szymanski in computer science.
William is a Unix guru and has done tremendous work, running jobs over the national-wide cluster: New Zealand eScience Infrastructure (NeSI). He is also completing a year-long project on applying 3D-Convolutional Neural Network on fMRI data, cosupervised by Lech Szymanski in computer science.
PhD Student: Elena Gorina, MS
PhD Student: Elena Gorina, MS
Elena is a cognitive neuroscientist with a strong background in data science. Co-supervised by A/Prof Jeremiah Deng in the School of Computing, Elena is working on incorporating multimodal neuroimaging data (s/f/dMRI and EEG) into the predictive models of cognition and mental health.
Elena is a cognitive neuroscientist with a strong background in data science. Co-supervised by A/Prof Jeremiah Deng in the School of Computing, Elena is working on incorporating multimodal neuroimaging data (s/f/dMRI and EEG) into the predictive models of cognition and mental health.
PhD student: Kseniia Konopkina, MS
PhD student: Kseniia Konopkina, MS
Kseniia is a cognitive neuroscientist with a background in psychology, neuroscience and sociology. Co-supervised by Prof Bruce Russell in the School of Pharmacy, Kseniia will be working on longitudinal predictive modelling for cognitive functioning across the life span.
Kseniia is a cognitive neuroscientist with a background in psychology, neuroscience and sociology. Co-supervised by Prof Bruce Russell in the School of Pharmacy, Kseniia will be working on longitudinal predictive modelling for cognitive functioning across the life span.
Exchange PhD student:
Nattapat Simarangsarit
Exchange PhD student:
Nattapat Simarangsarit
Nattapat is a PhD student from Chulalongkorn University in Thailand. He obtained a scholarship to spend a year here with us. Nattapat is working on longitudinal modelling of the changes in mental health and cognitive abilities in kids.
Nattapat is a PhD student from Chulalongkorn University in Thailand. He obtained a scholarship to spend a year here with us. Nattapat is working on longitudinal modelling of the changes in mental health and cognitive abilities in kids.
Visiting Postdoc: Leony Morgana Galliano, PhD
Visiting Postdoc: Leony Morgana Galliano, PhD
Leony has a strong background in physical activity and health, with a PhD in Physical Education. Leony is now working on predictive models for falls based on movement behavior data, including physical activity, sedentary time, and sleep.
Leony has a strong background in physical activity and health, with a PhD in Physical Education. Leony is now working on predictive models for falls based on movement behavior data, including physical activity, sedentary time, and sleep.
Visiting PhD student:
Raissa de Melo, MS
Visiting PhD student:
Raissa de Melo, MS
Raissa is bachelor's in nutrition and physical education, master's in physical education and PhD student in Health Sciences at the Federal University of Rio Grande do Norte - Brazil, with a background in movement behavior patterns in 24-hours cycles and their associations with cardiovascular diseases in older adults. She is currently developing cardiovascular risk prediction models based on AI. Supervised by Professor Eduardo Caldas and co-supervised by professors Narun Pat and Debra Waters.
Raissa is bachelor's in nutrition and physical education, master's in physical education and PhD student in Health Sciences at the Federal University of Rio Grande do Norte - Brazil, with a background in movement behavior patterns in 24-hours cycles and their associations with cardiovascular diseases in older adults. She is currently developing cardiovascular risk prediction models based on AI. Supervised by Professor Eduardo Caldas and co-supervised by professors Narun Pat and Debra Waters.
Master's student: Oscar Chen
Master's student: Oscar Chen
Oscar has a background in both psychology and economics. He is now working on a meta-analysis of neuroimaging-based prediction model for cognitive abilities.
Oscar has a background in both psychology and economics. He is now working on a meta-analysis of neuroimaging-based prediction model for cognitive abilities.
Visiting PhD student: Jessica Gu
Visiting PhD student: Jessica Gu
Jess is a senior counselling psychologist, specialising in mTBI, psychological trauma and AI use in psychology practice. Currently she is a PhD candidate in Department of Anatomy and Medical Imaging, Faculty of Medical and Health Science and Centre for Brain Research at University of Auckland and Mātai Medical Research Institute.
Jess is a senior counselling psychologist, specialising in mTBI, psychological trauma and AI use in psychology practice. Currently she is a PhD candidate in Department of Anatomy and Medical Imaging, Faculty of Medical and Health Science and Centre for Brain Research at University of Auckland and Mātai Medical Research Institute.
Lab Alumni
Research Assistant: Will Johnstone
Research Assistant: Will Johnstone
Will has a degree in computer science from University of Otago and University of Colorado - Boulder. Before joining our lab, he worked on robotics. Will helped us with developing deep learning architecture from neuronal time series.
Will has a degree in computer science from University of Otago and University of Colorado - Boulder. Before joining our lab, he worked on robotics. Will helped us with developing deep learning architecture from neuronal time series.
Research Assistant: Bryn Gibson
Research Assistant: Bryn Gibson
Bryn was our programmer, having skills in Python, Git, Bash, C#, JavaScript among others. He helped us build a pipeline to communicate with New Zealand eScience Infrastructure (NeSI)
Bryn was our programmer, having skills in Python, Git, Bash, C#, JavaScript among others. He helped us build a pipeline to communicate with New Zealand eScience Infrastructure (NeSI)
Research Assistant: Rhys Hobbs, MS
Research Assistant: Rhys Hobbs, MS
Rhys is a physicist with a Master's degree in physics. Rhys has been a go-to person for signal processing and has been building a Python toolbox for decoding EEG signals. Rhys is now working remotely from Wellington where he is working as a Medical Physics trainee.
Rhys is a physicist with a Master's degree in physics. Rhys has been a go-to person for signal processing and has been building a Python toolbox for decoding EEG signals. Rhys is now working remotely from Wellington where he is working as a Medical Physics trainee.
Research Fellow: Calvin Young, PhD
Research Fellow: Calvin Young, PhD
Calvin was our research fellow, jointly working with Neil McNaughton. Calvin is interested in Brain-behaviour interactions in health and disease, neurophysiology, optogenetics, EEG, signal processing/data analysis, mood disorders, Parkinson's disease and neurocognition.
Calvin was our research fellow, jointly working with Neil McNaughton. Calvin is interested in Brain-behaviour interactions in health and disease, neurophysiology, optogenetics, EEG, signal processing/data analysis, mood disorders, Parkinson's disease and neurocognition.
Vicky He
Vicky He
Vicky was our summer student in 2021-22, funded by the Otago Medical Research Foundation -Wilkinson summer scholarship. During the summer, Vicky worked on classifying MDD from MRI data using machine learning. Vicky is currently a PhD student at University of Melbourne.
Vicky was our summer student in 2021-22, funded by the Otago Medical Research Foundation -Wilkinson summer scholarship. During the summer, Vicky worked on classifying MDD from MRI data using machine learning. Vicky is currently a PhD student at University of Melbourne.
Wei Xiang Tan
Wei Xiang Tan
Wei Xiang was an Honours student in psychology. Wei Xiang worked on genetics X environments that might explain cognitive abilities using big data.
Wei Xiang was an Honours student in psychology. Wei Xiang worked on genetics X environments that might explain cognitive abilities using big data.
Ellie Logan
Ellie Logan
Ellie was an Honours student in neuroscience. Ellie worked on alterations in reinforcement-related EEG signals in depression.
Ellie was an Honours student in neuroscience. Ellie worked on alterations in reinforcement-related EEG signals in depression.
Emma Duffy
Emma Duffy
Emma was a Master's student in psychology. Emma worked closely with Calvin on rodents' electrophysiology model of depression.
Emma was a Master's student in psychology. Emma worked closely with Calvin on rodents' electrophysiology model of depression.
Jean Li, MS
Jean Li, MS
Jean was a PhD student in information science. She has helped us with machine learning related pipelines in the lab.
Jean was a PhD student in information science. She has helped us with machine learning related pipelines in the lab.
Danielle Rutter
Danielle Rutter
Danielle was a psychology 310 student who is working with Alina on structural MRI and depression.
Danielle was a psychology 310 student who is working with Alina on structural MRI and depression.
Hannah Burlison
Hannah Burlison
Hannah was an undergraduate student. Hannah worked on well-beings in NZ during the Covid-19 lockdown.
Hannah was an undergraduate student. Hannah worked on well-beings in NZ during the Covid-19 lockdown.
Meghan Goodman
Meghan Goodman
Meghan was an undergrad student who continued the work started by Hannah on well beings in NZ during the Covid-19 lockdown.
Meghan was an undergrad student who continued the work started by Hannah on well beings in NZ during the Covid-19 lockdown.
Issac Jamieson
Issac Jamieson
Issac was a clinical psychology student in the lab, working on predictive models of Covid related behaviours using machine learning and big data.
Issac was a clinical psychology student in the lab, working on predictive models of Covid related behaviours using machine learning and big data.
Mary-Joy Williams
Mary-Joy Williams
Marry-Joy was a psychology honours student who worked on the predictive modelling of the psychopathology factor.
Marry-Joy was a psychology honours student who worked on the predictive modelling of the psychopathology factor.
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