I am a translational neuroscientist focused on using machine learning (ML) and artifical intelligence (AI) tools to better understand the brain and develop clinically viable neurotechnologies aimed at improving the clinical diagnosis/treatment of neurological and psychological disorders (such as PTSD and concussion), and enabling better quality-of-life for vulnerable populations (e.g. Indigenous communities, youth, etc.). To accelerate the conception and development of such novel translational neurotechnologies, I co-founded NeurotechHA, the Hamilton chapter of the global NeurotechX organization, with the objective of unifying interdisciplinary researchers, industry partners and clinicians with a common interest in applying neurotechnologies to improve health outcomes.

I am currently an Adjunct Research Professor at the Departments of Psychiatry and Neuroscience at Western University, where I further my quest into AI-powered neuroscience and Brain-Computer Interfaces (BCIs) for improved quality-of-life and better mental health. Most recently, I held the position of Senior Data Scientist at Cognixion Inc., where my work focused on developing a viable communicative BCI in Augmented Reality (AR) for those with Amyotrophic Lateral Sclerosis (ALS), running a host of research studies to understand the dynamics of selective attention and factors affecting BCI performance, and finally customizing the AI models to account for these factors.

I completed a MITACS Industrial post-doctoral fellowship at the Homewood Research Institute (HRI), and the Department of Psychiatry at Western University, under the supervision of Dr. Ruth Lanius, where I applied my machine learning (ML) and artifical intelligence (AI) expertise to translate research-findings into clinical neuromarkers of post-traumatic stress disorder (PTSD), to improve diagnosis and treatment of such psychological disorders. I also was a postgraduate affiliate of the Vector Institute for Artificial Intelligence (AI), Toronto. I acquired my PhD under the supervision of Dr. Sue Becker at McMaster University, where my work focused on identifying signatures of brain networks using a cheaper and more clinically feasible imaging modality (EEG), compared to the current norm (fMRI), for better diagnosis of patients with complex mental health disorders (e.g. PTSD). I also completed my Bachelor's and Master's degree in Electrical and Biomedical Engineering from McMaster University, while developing better treatment tracking tools for concussion, and applying machine learning to improveme medical imaging of muscle.