Steven Kleinegesse

PhD Student in Data Science

University of Edinburgh

Biography

I am a PhD student at the Centre of Doctoral Training (CDT) in Data Science at the University of Edinburgh. My research interests include Bayesian experimental design, likelihood-free inference and Bayesian optimisation. Prior to being a PhD student, I graduated with a Master of Science in Physics from Imperial College London, where I specialised in Astrophysics and Particle Physics.

Interests

Data Science
Probabilistic Modelling
Approximate Inference
Bayesian Experimental Design

Education

MScR in Data Science, 2018

University of Edinburgh
MSci in Physics, 2017

Imperial College London

Skills

Python

100%

R

70%

Statistics

100%

Machine-Learning

90%

Git

80%

Linux

70%

Featured Publications

Sequential Bayesian Experimental Design for Implicit Models via Mutual Information

Bayesian experimental design (BED) is a framework that uses statistical models and decision making under uncertainty to optimise the …

Steven Kleinegesse, Christopher Drovandi, Michael U. Gutmann

PDF Source

Bayesian Experimental Design for Implicit Models by Mutual Information

Implicit stochastic models, where the data-generation distribution is intractable but sampling is possible, are ubiquitous in the …

Steven Kleinegesse, Michael U. Gutmann

PDF Source

Efficient Bayesian Experimental Design for Implicit Models

Bayesian experimental design involves the optimal allocation of resources in an experiment, with the aim of optimising cost and …

Steven Kleinegesse, Michael U. Gutmann

PDF Code Source

Pulse Shape Discrimination and Exploration of Scintillation Signals Using Convolutional Neural Networks

We demonstrate the use of a convolutional neural network to perform neutron-gamma pulse shape discrimination, where the only inputs to …

J. Griffiths, S. Kleinegesse, D. Saunders, R. Taylor, A. Vacheret

PDF Source

Recognizing Emotions in Video Using Multimodal DNN Feature Fusion

We present our system description of input-level multimodal fusion of audio, video, and text for recognition of emotions and their …

Jennifer Williams, Steven Kleinegesse, Ramona Comanescu, Oana Radu

PDF Source

Steven Kleinegesse

PhD Student in Data Science

University of Edinburgh

Biography

Interests

Education

Skills

Python

R

Statistics

Machine-Learning

Git

Linux

Featured Publications

Sequential Bayesian Experimental Design for Implicit Models via Mutual Information

Bayesian Experimental Design for Implicit Models by Mutual Information

Efficient Bayesian Experimental Design for Implicit Models

Pulse Shape Discrimination and Exploration of Scintillation Signals Using Convolutional Neural Networks

Recognizing Emotions in Video Using Multimodal DNN Feature Fusion

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