Aanya Malaviya

I am a Research Assistant in the Computational Psychiatry Lab, led by Professor Michael Browning. The lab uses computational models of behaviour to understand anxiety and depression better and to inform the development of novel treatments. Currently working on the Wellcome Trust-funded RELMED project, a clinical trial investigating how different antidepressants influence reinforcement learning. This work integrates behavioural paradigms with neuroimaging methods to identify computational predictors of treatment response in depression.

My academic background is in brain imaging, cognitive neuroscience, and psychosis research, with a strong focus on the biological mechanisms underlying severe mental illness. I hold an undergraduate degree in Psychology and a Master’s degree in Brain Imaging and Cognitive Neuroscience. I am a trained MRI operator with hands-on experience in functional MRI (fMRI), structural MRI (sMRI), magnetic resonance spectroscopy (MRS), and diffusion tensor imaging (DTI). I am well-versed in MRI data analysis, MRI safety procedures, and participant screening.

My research includes work with large-scale datasets, where I have developed machine learning models to classify psychiatric phenotypes using neuroimaging and inflammatory biomarkers. I am particularly interested in developing computational tools to identify biologically informed biomarkers that can support personalised treatment approaches in psychiatry.

Alongside my computational research, I have extensive experience working directly with individuals experiencing mental health difficulties, including participant recruitment, informed consent, and clinical assessments. I also bring wet-lab expertise, enabling me to bridge basic neuroscience and clinical research. By integrating biochemical, neuroimaging, and computational approaches, I aim to develop data-driven models of severe mental illness that ultimately improve treatment outcomes.