Worked in collaboration with Medic Mobile and Dimagi, to use ML & AI tools to generate, assess synthetic patient data and provide recommendations for its development & use so that partners can create health tools that work for everyone.
Daily Challenge of solving atleast one Competitive Programming question.
Course project for 'Railway Engineering' (Autumn Semester, 2020)
Pytorch codebase for DEAP Cache.
Created an OpenAI gym environment for Policy Optimisation in the drug/vaccine disribution problem using Reinforcement Learning. Codebase for VacSIM.
Deep Learning Framework developed for automatic and semi-automatic data annotation in connectomics. Contributed during internship at Lichtman Lab, Harvard University.
A detailed engineering survey involving on-field data collection and off-field data processing, with solutions recommended for the identified problems based on statistical inference.
Classification of EEG Signals into focal and non-focal epileptic type using Machine Learning and Deep Learning architectures. Manuscript in preparation stage.
Summaries of the papers that are discussed by VLG(Vision and Language Group) IIT Roorkee.