Fareed  Sheriff

Fareed Sheriff

Scholar Title

Eric and Wendy Schmidt Center Funded Research and Innovation Scholar

Research Title

Causal Inference and Reinforcement Learning

Cohort

2023–2024

Department

Electrical Engineering and Computer Science

Research Areas
  • Artificial Intelligence & Machine Learning
Supervisor

Caroline Uhler

Abstract

In many applications the end goal of causal inference is not necessarily to learn the underlying causal system but to infer the best interventions in order to push the underlying system towards a desired state. This is the case for example when studying reprogramming, where the goal is to determine the best interventions (e.g. over-expression of particular transcription factors) to push a differentiated cell towards the stem cell state. In this project, the goal is to build on methods in active learning, RL and causal inference to obtain methods for selecting the best interventions in order to push the system towards a desired state.

Quote

I’m participating in this SuperUROP because I am interested in statistics and inference research. I would like to obtain more experience with inference while learning about causal inference, which is applicable to many fields including economics, the social sciences, and biology. I hope to learn relevant background on existing problems and solutions in causal inference and hopefully produce work worth publishing.

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