Pranav Mahajan

Pranav is a postdoctoral researcher at University of Oxford. As a scientist and an engineer, he tries to understand the adaptive and maladaptive aspects of human and artificial minds, in order to help develop AI systems that work for us, humans (rather than the other way round!).  

To a first approximation, this involves treating minds as computational systems - agents that learn, adapt, act purposefully in uncertain, open-ended environments and interact with other minds - broadly termed computational cognitive neuroscience. Bridging it with AI helps us build the next generation of safer AI systems, which are grounded in a more rigorous science of intelligence, as well as digital health technologies driven by the precise mechanisms of dysfunction. 

Pranav earned his DPhil (PhD) from University of Oxford, under the guidance of Prof. Ben Seymour and Prof. Ioannis Havoutis, and his Bachelors in Electronics and Communications Engineering from BITS Pilani Goa, India prior to starting this DPhil here. He has previously worked with Dr Boris Gutkin on algorithmic modelling of drug-seeking behaviours and with Dr Veeky Baths on early detection of Alzheimer's dementia detection from speech.  He has developed a toolbox for quantifying higher-order interactions with Dr Daniele Marinazzo and Dr Fernando Rosas at INCF and a toolbox for quantifying synchronisation in neural time-series with Dr Basabdatta Sen Bhattacharya. He has industry RnD experience in scalable deep learning (MLperf) at Nvidia.