Sanjay Manohar

Clinical Fellow, Nuffield Department of Clinical Neurosciences, University of Oxford


I am a cognitive neuroscientist and a clinical neurologist. I study the mechanisms of motivation, and how these can be used to treat clinical disorders. My research bridges psychology, neuroscience and neurology, using mathematical modeling and neuroimaging. 

My work

Although primarily an experimental scientist, my work involves designing software tools for colleagues, aiming to provide a robust and futureproof environment for reproducible and open data analysis. 

I have been programming all my life, and creating software has featured at every stage in my career. I am passionate about bringing programming to all domains including my hobbies, clinical work and research. I program in diverse languages, having completed full research projects in C++, Pascal, Forth, Java, Python and Matlab. I am an active member of Oxford University Research Software Developers’ Network (RSDN), a peer group of individuals who support research through the coding.

I pride my role as an educator, advocating best coding practices.  Training neuroscientists require much assistance and close supervision with methods and rapid prototyping of analysis scripts. Coding is often the slowest and most challenging area for a number of scientists.  A minimal training and educational framework is in place to give scientists the confidence they need to present their own code as a piece of work.  However the symptoms of bad practice are everywhere in neuroscience. Reproducibility of results has been hampered by coding errors and non-peer-reviewed code. 

I plan to present good-coding principles relevant to scientists in general, in a language-agnostic way. I will aim to produce a series of video seminars for scientists that demonstrate the principles of good programming practice. It would provide accessible, simple and targeted information on techniques for writing scientific scripts. It will be based a course I designed at UCL and Oxford, which uses modern teaching tools like problem-based learning, facilitation of discussion, and multimodal demonstrations, aiming to impassion students about well-written code

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