Our Team

Our Team

Dr. Aristotle Voineskos, M.D., Ph.D

Dr. Aristotle Voineskos is the Koerner New Scientist, and Head of the Kimel-Family Translational Imaging-Genetics Laboratory at CAMH. He is Assistant Professor in the Department of Psychiatry, Faculty of Medicine at the University of Toronto.

Dr. Voineskos’s work combines multi-modal neuroimaging and genetics approaches to map gene effects in the brain with a view to discovering vulnerability pathways for severe mental illness. This will aid in early identification of at-risk individuals and disease prevention. Currently, his neuroimaging approaches include MRI techniques known as diffusion tensor imaging and cortical thickness mapping. Disease populations currently under study include schizophrenia, bipolar disorder and Alzheimer’s disease, as well as studying healthy individuals and healthy aging.

Another area of Dr. Voineskos’s work includes understanding genetic and structural brain determinants of brain function by combining the approaches described above with transcranial magnetic stimulation (TMS). He is also using brain imaging to understand the effects of existing and novel treatments on brain structure and function.

Dr. Colin Hawco, Ph.D

Dr. Hawco (PhD, Neuroscience, McGill University) is a project scientist. He develops new approaches to uncover meaningful patterns of individual variability in complex neuroimaging data. He hopes this work will lead to better understanding of biological variability in patient samples, and inform personalized medicine approaches in psychiatry. In 2018, Dr. Hawco was appointed to the Department of Psychiatry as an Assistant Professor, published six papers (four as first author) and four conference poster presentations. Dr. Hawco has also submitted his first large project grants as senior investigator to CIHR and the National Institute of Mental Health, developing neuroimaging markers to predict response to brain stimulation therapies.

ResearchGate

Dr. Erin W. Dickie, Ph.D

Dr. Erin Dickie (PhD, Neurological Sciences, McGill University) is a Project Scientist. Dr. Dickie’s research focus is personalized connectomics, or the ability to map brain organization at the level of the individual. She recently published a paper in Biological Psychiatry, finding that personalized brain mapping might facilitate biomarker discovery. In this paper, she introduced a novel tool for mapping neurodiversity (PINT), and showed that the brains of those affected by autism are more variable in their organization than those of typically developing controls. Dr. Dickie was recently awarded a NARSAD Young Investigator Award to investigate how individual mapping of brain function may be a critical first step for the design of targets for neurostimulation therapy. Dr. Dickie also founded the “ciftify” open software framework for surface-based analyses of MR data, with collaboration from the developers of the Human Connectome Project. She serves as an invited instructor and member in international initiatives for education and best scientific practices, including the International Neuroinformatics Coordinating Facility (INCF) working group for Reproducibility and Best Practices in Human Brain Imaging.

Dr. Lindsay Oliver, Ph.D

Dr. Lindsay Oliver (PhD, Neuroscience, University of Western Ontario) is a postdoctoral fellow. Oliver’s work focuses on the neural circuitry and behavioural correlates of social cognition across psychiatric and neurologic disorders. Oliver is currently using behavioural modeling to examine the structure of social cognition in individuals with schizophrenia and healthy controls from the SPINS dataset. Her recently published work used structural equation modeling to identify lower-level (e.g., emotion recognition) and higher-level (e.g., inferring others’ intentions) social abilities. Oliver revealed an association between these higher-level abilities and everyday functioning in schizophrenia spectrum disorder and healthy control groups. Now, Dr. Oliver is incorporating brain imaging data to understand neural networks underlying social cognitive deficits. The overall goal is to identify biomarkers of social cognitive impairment to inform targeted treatment options for these symptoms.

Hajer Nakua, BSc.

Hajer Nakua (BSc. Psychology, Neuroscience, & Behaviour, McMaster University) joined the lab as a Master’s student in September. She hopes to explore the connections between the cerebral cortex and amygdala in children and adolescents with neurodevelopmental disorders; specifically, obsessive-compulsive disorder (OCD), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). By comparing these connections with their behavioural correlates, we can better understand the mechanisms of disease and create more effective treatment plans.

Dr. Christin Schifani, Ph.D

Dr. Schifani (PhD, Neuroscience, Ruprecht-Karls University of Heidelberg) joined the lab in September 2018. She will be using advanced MRI techniques to work with data from the rTMS-WM study. Schifani’s work will first explore the impact of rTMS on the structure of the cortex, using a cutting-edge method called Neuritic Orientation Dispersion and Density Imaging (NODDI). Next, Schifani intends to explore how rTMS changes the functional brain networks underlying working memory function. With this, we aim to improve understanding of the therapeutic mechanisms of rTMS. Data collection for rTMS-WM is almost completed, and analyses will begin shortly.

Michael Joseph, M.Sc

Joseph (BSc, Biology & Psychology, McMaster University; MSc, Physiology, University of Toronto) is a Research Analyst. He assists with improving the lab’s MRI data management and quality control software. Michael previously performed a similar role at the Ontario Brain Institute, where he specialized in neuroimaging and clinical data collection databases. To this end, Michael teaches a monthly introductory course to train the hospital’s research staff and scientists in using databases for their research projects. Michael is also involved in managing SPINS-ASD: a new study comparing autism-spectrum and schizophrenia-spectrum disorders led by lab collaborator Dr. Stephanie Ameis. Michael’s primary interests lie in developing new software to automate MRI data analysis and understanding the statistical techniques involved.

Dr. Natalie Forde, Ph.D

Dr. Forde (BSc Chemistry, University College Cork, Ireland; MSc Neuropharmacology, National University of Ireland, Galway; PhD Psychiatry, University of Groningen, the Netherlands) joined the lab in January 2018 as a post-doctoral research fellow. Dr. Forde is interested in symptoms that appear across different neurodevelopmental disorders and investigates their neural correlates by integrating imaging data from multiple modalities. She uses this multi-modal approach to better understand brain connectivity, the relationship between brain structure and function, and the way this all relates to symptoms of neurodevelopmental disorders. Forde uses the uniquely large Province of Ontario Neurodevelopmental Disorders (POND) Network dataset of children and adolescents with various neurodevelopmental disorders to identify biomarkers that relate to symptoms across disorders. In the future, this may help design targeted interventions like transcranial magnetic stimulation to improve cross disorder symptoms and long-term outcomes for those with neurodevelopmental disorders. Dr. Forde was awarded a CAMH Discovery Fund award for this proposal.

Gabrielle Herman, B.Sc

Herman (BSc Psychology, Neuroscience, & Behaviour, McMaster University, 2018) joined the lab in May as a research analyst. She assists with data management and quality control for several studies in the lab. She has been especially involved in the OPTIMUM study on late-life depression, and has created a number of tools to track study recruitment. She also manages twice-yearly uploads of imaging and clinical data for the lab’s two NIH R01-funded studies (OPTIMUM and SPINS). Herman has also contributed code to various analysis and data management pipelines. She is interested in neurocognitive predictors of brain activity, and hopes to investigate brain networks and network flexibility.

Jerrold Jeyachandra, M.Sc

Jeyachandra (M.Sc, Science, Queens University) joined the lab as a Research Analyst. He is responsible for maintaining and expanding upon the lab’s computational pipelines for processing imaging data. In addition, he manages the analysis of phantom data, which provides critical insight into scanner performance across the many research centres involved in the lab’s studies. Jeyachandra is also interested in utilizing computational techniques to improve precision in therapeutic neurostimulation. To create personalized treatment, he is working to bringing together techniques for modeling rTMS-induced electrical fields with characterizing individualized resting state activity.

Kevin Witczak

Witczak joined the lab in June and works to improve the lab’s compute cluster and general data processing resources. His specific focus in the lab has been on the development of reproducible software systems and high performance computing. He maintains and develops programming scripts, troubleshoots computing issues, and is involved with tracking inventory and maintaining the lab’s computers.

Dr. Neda Rashidi-Ranjbar, M.D., M.Sc

Dr. Rashidi (MSc, Cognitive Science, Trento University; MD, University of Tehran) is a doctoral student. She studies brain structure and function among older adults with varying levels of risk for dementia, and examines their connections with cognitive scores. Rashidi-Ranjbar is primarily working with PACt-MD, a multi-center clinical trial that aims to identify stepwise patterns of disease progression in older participants with depression, mild cognitive impairment, and Alzheimer’s Disease. Specifically, Rashidi-Ranjbar will use the three neuroimaging scans provided by each participant over a span of six months to identify structural and functional brain measures associated with the observed delay or prevention of dementia, as well as investigate the effect of cognitive training and brain stimulation on brain structure and function. In the coming year, Dr. Rashidi will use similarity network fusion (SNF), a modeling approach developed by lab collaborator Dr. Anna Goldenberg (SickKids), to identify similarity networks that integrate demographic, cognitive and imaging data. Rashidi anticipates that SNF will identify informative clusters of participants with similar profiles irrespective of diagnosis. This year, Rashidi has been awarded the Alzheimer Society Research Program Doctoral Award and the Faculty of Medicine GSEF Merit Scholarship.

Mathuvanthi (Mathu) Manogaran

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Manogaran (BSc Computer Science, University of Toronto Scarborough, expected 2021) joined the lab as a co-op student for the January - May term, and enjoyed it so much she stayed for an additional co-op term until August 2018. In collaboration with Dawn Smith and Dr. Erin Dickie, she supported many aspects of the lab’s computational infrastructure and contributed to software development. She is responsible for creating a program that can convert the lab’s native directory structure to a new reproducible data format (BIDS), and created several portable Docker images for Dr. Dickie’s Ciftify program. Manogaran also upgraded DTI processing pipelines and made several contributions to the lab’s quality control interface.

Dr. Nick Neufeld, M.D., M.Sc

Dr. Nicholas Neufeld (MSc, University College London; MD, University of Toronto) is a former Commonwealth Scholar and current research fellow. Dr. Neufeld’s primary project involves the analysis of brain imaging data from STOP-PD. In 2017, Dr. Neufeld received a Norris Scholar Award as well as a Resident Research Grant from the Physician Services Incorporated Foundation that will fund a pilot project on brain imaging biomarkers of antipsychotic (clozapine) response in an early intervention population. Ultimately, Dr. Neufeld’s goal is to harness the power of neuroimaging and other biomarkers to get patients with psychiatric disorders better, faster.

ResearchGate - Academia.edu - Frontiers

Dawn Smith, B.Sc

Dawn Smith (BSc Psychology, York University; BSc Computer Science, York University) is a Research Methods Specialist, responsible for improving existing and creating new software to manage MRI data and perform quality control. Smith also works to keep the lab’s technical systems running smoothly in the face of heavy demand and constant change. Smith’s primary interest is in developing and deploying new tools to automate common preprocessing and quality control tasks, and make the computational aspects of imaging analysis easier for the lab’s scientists. Recently, her focus has been on updating the quality control dashboard and its underlying code, and she presented on this facilitated review process at INCF.

Grace Jacobs, B.Sc

Grace Jacobs (BSc, Biomedical Science, University of Ottawa) is a third year PhD candidate in the Institute of Medical Science under Dr. Voineskos’ supervision. Her work focuses on youth with psychosis spectrum symptoms, and aims to understand the neural mechanisms underlying symptom development, as well as sex-specific differences. Jacobs uses structural and functional MRI data to characterize connectivity of a circuit involving the striatum, thalamus and cortical areas. She asks if activity alterations known to occur in adult chronic schizophrenia can also be seen during critical neurodevelopmental periods. The hope is that, if this circuit is an early biomarker for schizophrenia, identifying it and understanding its underlying mechanisms can improve illness risk detection and allow personalized intervention in youth.

Sonja Stojanovski, B.Sc.

Sonja Stojanovski (BSc Neuroscience, Psychology, & Physiology, University of Toronto) is a second-year Doctoral Candidate in the Department of Physiology working with lab alumnus Dr. Anne Wheeler. Over the past year, Stojanovski collaborated with current lab members and lab alumnus Dr. Arash Nazeri’s to apply his Superficial White Matter methods to identify how TBI affects these structures in youth and the elderly. Recently, Stojanovski collaborated with the lab to explore how traumatic brain injuries (TBI) affects the etiology of ADHD. The paper reporting her findings features many Kimel Lab members as coauthors, and was recently published at Biological Psychiatry. Stojanovski recently won the Margaret & Howard GAMBLE Research Grant for three consecutive terms starting this fall, and holds Sickkids Restracomp scholarship for the rest of her degree. Stojanovski looks forward to continued collaboration with the lab.

Calarco (BA Philosophy, University of Toronto; BA Cognitive Science, York University) is starting an MSc. in the Institute of Medical Science program, under the direction of Dr. Voineskos, after spending three years in the lab as an RA. Her thesis work will support the central aims of Dr. Voineskos’ OMHF-funded longitudinal study examining the neurobiology of persistent negative symptoms (PNS) in first-episode psychosis. Specifically, Navona will describe disruptions in white matter network circuitry, and test if these disruptions can be used by a machine learning classifier to accurately predict which individuals will go on to develop PNS. If successful, this work will advance early identification and inform intervention efforts. This project was funded by CIHR CGS-M and CAMH’s Discovery Fund award. Navona will also work as an RA for lab alumnus and collaborator Dr. Yuliya Nikolova, on a project aiming to test the “accelerated aging” hypothesis of depression.

Judy Kwan, B.Sc.

Judy Kwan (BSc., Animal Physiology, University of Toronto) is a Research Analyst working on both SPINS and STOP-PD. For both studies, she takes the lead collecting neuropsychological and social cognitive assessments from research participants, and coordinating shared visits for the sample collection lab and MRI. Kwan is also responsible for providing training to new study staff.

Dielle Miranda, MA (Clin Psy)

Alumni

Sinead Ramsaroop

Sinead Ramsaroop (BA, Psychology, York University, expected 2017) spends two days each week with the lab to provide administrative support to its students, staff, and Dr. Voineskos. She appreciates that her role affords her an inside view of hospital bureaucracy, academic administration, and the scientific process. Ramsaroop is also very committed to community advocacy, and outside of the lab, runs her own charity called Project Reset, which helps facilitate a psycho-education treatment program for women accessing city shelters.

Rutwik Bangali

Rutwik Bangali (BEng Electrical Engineering, University of Toronto, expected 2019) returned as a summer student for the second year. Bangali analyzed metabolite concentrations in the dorsolateral prefrontal cortex (dlPFC) and the subgenual anterior cingulate cortex (sgACC) using magnetic resonance spectroscopy (MRS) data from the STOPPD dataset. Bangali worked closely with Dr. Nick Neufeld, Dr. Sofia Chavez, and Joseph Viviano to ensure his data analysis and processing scripts could be applied to the study’s multiple data-collection sites, and also worked to automate the entire pipeline to ensure ease of future use.

Lauren Liu

Lauren Liu (BEng Electrical and Biomedical Engineering, McMaster University, expected 2019) joined the lab as a summer student. In collaboration with Joseph Viviano, Liu analyzed the relationships between structural topology and brain dynamics at rest, among participants with schizophrenia and healthy control populations. She tested various diffusion tractography algorithms and parameters in order to tackle the challenge of quantifying structural connectivity strength between brain regions. Liu subsequently developed a processing pipeline to produce ROI-to-ROI connectivity matrices for various structural metrics to use in conjunction with functional MRI correlation matrices, which will soon be adopted into the lab’s larger processing pipelines system. Combining multimodal neuroimaging techniques - in this case structural and functional - allows for a more comprehensive characterization of global brain networks, an essential first step to future interventions.

Dayton Miranda

Dayton Miranda (BSc Life Sciences, Western University, expected 2020) returned as a summer student for the second year. In collaboration with Dr. Erin Dickie and Saba Sahab, Miranda analyzed structural and functional MRI data from patients with schizophrenia and healthy controls in an effort to identify between-group structural differences in the cortex, which in turn might contribute to an explanation of the functional disconnectivity observed in schizophrenia. Further understanding of the structural features and markers of schizophrenia might allow the illness to be identified and perhaps predicted using structural as opposed to functional scans, which are quicker and therefore cheaper to collect. Miranda is continuing to analyze incoming data for this project, and looks forward to reporting his results in an upcoming paper.

Laagi Yoganathan

Laagi Yoganathan (BSc Psychology, Neuroscience & Behaviour, McMaster University) returned as a summer student for the second year. Under the supervision of Drs. Stephanie Ameis and Colin Hawco, he worked on a project investigating the efficacy of rTMS treatment in individuals who have high functioning autism and comorbid executive functioning (EF) deficits. Yoganathan analyzed cognitive assessment and task-based fMRI data to determine if there are any changes on EF performance or in the brain networks involved with EF following rTMS treatment. He is now pursuing an MSc in Psychology at McMaster University.

Erika Ziraldo

Erika Ziraldo (BEng AREA, University of Guelph, expected 2018) joined the lab as a summer student. With support from Dr. Dickie and Joseph Viviano, Ziraldo developed a cleaning pipeline to remove artifacts from spiral resting state functional MRI scans. Thorough testing and application of the pipeline to multiple datasets has demonstrated improved brain connectivity in expected regions. The pipeline has been made publicly available for other researchers at CAMH. Ziraldo will be returning to the Kimel lab for another student term this fall.

Dr. Yuliya Nikolova, Ph.D

Dr. Yuliya Nikolova (BA, Psychology, Harvard University; PhD, Psychology & Neuroscience, Duke University) completed her training as a Banting Postdoctoral Fellow in Dr. Etienne Sibille’s Neurobiology of Depression and Aging lab. Throughout her postdoctoral work she collaborated with Dr. Voineskos on projects aiming to accelerate the translation of basic preclinical research to human neuroimaging and clinical applications. In her most recent project, Dr. Nikolova developed a novel transcriptome-based polygenic risk score for depression, which maps onto cognitive brain function and performance, as well as stress-related depressive symptoms. Over the past year, Dr. Nikolova received two prestigious conference travel awards to present her work at the annual meetings of the American College of Neuropsychopharmacology and the Society of Biological Psychiatry. She was recently appointed the next Koerner New Scientist at CAMH and will continue her collaborative work with Dr. Voineskos.

Laura Stefanik, M.Sc

Laura Stefanik (BA, Psychology, Queen’s University; MSc, Institute of Medical Science, University of Toronto) recently graduated under the supervision of Dr. Voineskos. Stefanik’s work focuses on the application of novel data aggregation algorithms for social cognitive, neurocognitive, and neuroimaging data in an effort to identify impairment-specific markers of illness across adolescents and young adults with autism spectrum, schizophrenia spectrum and bipolar disorder. The goal of this work is to enhance disease subtyping and to identify treatment targets to improve social functioning. During her graduate studies, Stefanik had authorship on five peer reviewed scientific publications and her work was presented at a number of local and international academic conferences. Stefanik recently accepted a Research Analyst position with the Slaight Family Centre for Youth in Transition and Child, Youth and Emerging Adult Programs.

Saba Shahab, M.Sc

Saba Shahab (BSc, Neuroscience, University of Toronto) completed her MSc under the supervision of Dr. Voineskos. Over the past year, she collaborated with Dr. Dickie to apply a tool developed in-lab to a replication dataset in an effort understand how the brains of individuals with schizophrenia differ in their functional organization from those of neurotypical adults. Identifying abnormalities in functional organization in the brains of schizophrenia patients may lead to a better understanding of the disease process, and illuminate new targets for future treatment interventions. Shahab also conducted a systematic review and meta analysis examining sex-based differences in white matter microstructure in schizophrenia, which was recently published in Schizophrenia Bulletin. Shahab completed her degree in June 2017, and is now a first-year medical student at Western University.

Dr. Tom Wright, Ph.D

Dr. Tom Wright (PhD Neurophysiology, Gothenborg University, Sweden) is a Research Methods Specialist, who works mainly on the lab’s MRI quality control metrics. Most notably, Dr. Wright developed an in-house interactive ‘dashboard’ interface that allows staff to easily examine individual participant data, seamlessly observe and track longitudinal trends across participants, sites, and scan types, and communicate issues with relevant parties. Additionally, Dr. Wright regularly consulted with the lab’s students and scientists to support the computational requirements of their projects, and worked with the lab’s staff to strengthen its general computational infrastructure. Dr. Wright recently accepted a position as a Senior Research Associate (Electrophysiology) at the Kensington Vision & Research Centre.

Dawson Overton, M.Sc

Dawson Overton (BSc, Computer Science, University of Toronto, MSc, Cognitive Neuroscience, University of Toronto) is interested in the characterization and identification of psychosis spectrum disorders using the BOLD signal and ASL neuroimaging data, especially using predictive computational techniques, such as support vector machines, neural networks, and other machine learning models. He recently left the lab to attend medical school at the Schulich School of Medicine.

Daniel Felsky, Ph.D

Dr. Daniel Felsky (PhD, Institute of Medical Science, University of Toronto) completed his doctoral training under Dr. Voineskos in 2016, and has since completed a productive first year of his postdoctoral fellowship at Brigham and Women’s Hospital and Harvard Medical School, and recently transitioned to a postdoctoral scientist position in the newly founded Center for Translational and Computational Neuroimmunology at Columbia University Medical Center. In addition, Dr. Felsky is continuing his investigations into the complex genomic foundations of aging and Alzheimer’s disease as an associate scientist at the Broad Institute of MIT and Harvard. Since starting his fellowship, Dr. Felsky has published four peer-reviewed articles, been invited to speak at three national and international conferences, and, in 2016, was awarded the CIHR Institute of Aging Fellowship Prize of Excellence in Research on Aging.

Julie Winterburn, M.Sc

Julie is a student in the second year of her Master’s degree with the Institute of Biomaterials and Biomedical Engineering at the University of Toronto. Her thesis focuses on comparing machine learning techniques reported in the magnetic resonance imaging literature for schizophrenia/control classification. Her previous work includes atlasing the hippocampus on high-resolution magnetic resonance images. Julie has been with the Kimel Family lab group since 2012. In her spare time, she can be found baking delicious treats, eating said baking, or out rowing on Lake Ontario.

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Dr. Mallar Chakravarty, Ph.D

Magnetic resonance imaging (MRI) is one of the tools of choice for the analysis of the brain in normally functioning and diseased states. Different MRI acquisition protocols provide excellent contrast and resolution and can be analyzed using automated techniques. The goal of Dr. Chakravarty’s work is to develop and use computational neuroanatomical techniques to understand how the structure of the brain is altered in psychiatric disorders. These techniques include the automated identification of structures and computational metrics that quantify their shape. He is currently working on adding information from diffusion tensor imaging in order to describe inter-structural connectivity. Many of these techniques can be used to elucidate phenotypes that can help describe how known risk genes may be affecting brain anatomy and ultimately increasing susceptibility to psychiatric illness. This work will aid in the early identification and treatment of those at high-risk of developing severe forms of mental illness.

Dr. Chakravarty now heads the CoBrA Lab at the Douglas Institute, Montreal.

Dr. Tristram Lett, Ph.D

Dr. Anne Wheeler, Ph.D

Anne is a new Catalyst Scholar in traumatic brain injury (TBI) at SickKids Hospital.

ResearchGate

David Rotenberg, M.Sc

David is now the Manager of Scientific Computing at CAMH.

Mikko Mason, B.Sc

As a relatively new member of the Kimel Lab, I am excited to work with so many bright, engaged individuals. My role as a study RA challenges me to apply my psychometric experience to a research setting, and I am constantly amazed by the resilience with which our patients meet mental health challenges. I plan to further my education and combine research, clinical work, and teaching in the future.

On a more personal level, I feel like a Finn when in Canada and a Canadian when in Finland. I have a soft spot for old novels and the CBC. I believe in free time the way I believe in unicorns, but find sanctuary in wild places. I am happiest in woods or water or on a bike.

Tina Behdinan, MSc

Tina is now persuing her MD at the Schulich School of Medicine & Dentistry.

Robert S.C. Amaral, B.Sc

Robert is pursuing graduate studies at the CoBrA Lab at the Douglas Institute, Montreal.

Matt Park, B.Sc

Matt is now pursuing his MD at the Schulich School of Medicine & Dentistry.

Jon Pipitone, M.Sc

Jon is now pursuing his MD at the Queen’s School of Medicine.

Dr. Mélissa Lévesque, Ph.D

Melissa did a BSc in Psychology at McGill University, followed by an MSc in Neuroscience, also at McGill. During her Master’s degree she studied the function of the serotonin 1A receptor following acute administration of fluoxetine, using positron emission tomography (PET) with [18F]MPPF in healthy populations of both rats and humans. Then, during her PhD in Biomedical Sciences in the Department of Psychiatry at the University of Montreal, she studied the long-term impacts of prenatal and early postnatal adversity on brain development using MRI and fMRI, and epigenetic mechanisms, specifically DNA methylation, in a cohort of adolescent monozygotic twins followed since birth.

At CAMH, she is now working on testing the accelerated aging hypothesis of schizophrenia using both DTI and peripheral markers in young and old schizophrenia patients and controls. Her interests lie in uncovering the biomarkers of vulnerability for mental illness using a combination of neuroimaging and molecular strategies.

Dr. Arash Nazeri, M.D.

Dr. Arash Nazeri (MD, Tehran University of Medical Sciences) completed a postdoctoral fellowship under the mentorship of Dr. Voineskos in 2016, and has since started his residency in Diagnostic Radiology at Washington University in St. Louis. Dr. Nazeri has maintained his collaboration with the lab from long distance and continues his research on gray matter tissue microstructure in brain health and disease using diffusion-weighted MRI. He has also recently joined Chen Ultrasound Laboratory in St. Louis as where he works on applications of focused ultrasound on the brain. His primary goal is to developing novel neuro-therapeutic and neuro-diagnostic approaches using focused ultrasound.

GithubORCiD

Dr. Tina Roostaei, M.D., M.P.H.

Dr. Tina Roostaei (MD, Tehran University of Medical Sciences) completed a postdoctoral fellowship in imaging-genetics in neurodegenerative disorders under the mentorship of Dr. Voineskos in 2016. She has now joined the Center for Translational and Computational Neuroimmunology, Columbia University, New York, as a postdoctoral research scientist. Tina is continuing her studies on the genetic basis of susceptibility and progression of brain neurodegenerative disorders, with focus on the functional genomics of Multiple Sclerosis and Alzheimer’s disease. Her goal is to contribute to the advancement of understanding of the pathophysiology of these brain disorders and to find targets for their treatment and prevention.

Nikhil Bhagwat, M.Sc

Currently I am working on developing novel biomakers and diagnostic applications for neurodegenerative disorders using machine-learning techniques. My research interest include, computational neuroscience, machine-learning, signal processing and related areas.

Amy Miles, MA

Amy Miles (BA, Psychology & French Language and Literature, University of Maryland; MA Developmental Psychology, Columbia) is a fifth year PhD candidate under the supervision of Drs. Allan Kaplan and Aristotle Voineskos. She is interested in the neurobiological underpinnings and developmental trajectories of eating disorders and has designed a structural MRI study to explore the neuroanatomical correlates of risk for and manifestation of Anorexia Nervosa (AN). Ultimately, Amy hopes to use this information to identify novel therapeutic targets for AN, the most fatal psychiatric disorder and one for which there are currently no evidence-based treatments.

Vincent Man, BSc

Joseph Viviano, M.Sc

Joseph Viviano (BA, Psychology, Queens University; MSc, Biology, York University) is responsible for the design and implementation of a data management platform used by researchers in the lab and beyond, as well as the lab’s general computational infrastructure. Viviano’s role also involves the design and implementation of analytic code used by the lab’s scientists, and the development of novel prognostics tools utilizing MRI scans to guide patient-specific treatment. Over the past year, Viviano has worked to develop a fully-automated method for identifying patients with schizophrenia and comorbid severe cognitive impairment, as well as a method for predicting Alzheimer’s onset.

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