Evdoxia Taka

Office: Sir Alwyn Williams Building, Room F161
E-Mail: evdoxia.taka.1@research.gla.ac.uk
Personal Site:  http://www.dcs.gla.ac.uk/~evdoxia/

ORCID iDhttps://orcid.org/0000-0001-7011-3367

Research title: Interactive Animated Visualizations of Probabilistic Models

Research Summary

Research Group

My research lab is situated within the Inference, Dynamics and Interaction research group.

Current Research

My research focuses on the creation of novel representations of probabilistic models that incorporate animated and interactive visualizations for the communication of the uncertainty about the true value of the model's variables. The research question that I will try to answer in the contexts of this research will be whether these novel representations of probabilistic models help people better understand and interpret models and make explainable and rational decisions.

Import outcome of my research so far is the Interactive Probabilistic Models Explorer (IPME) tool - available here.

Research Interests

  • Bayesian Probabilistic Models
  • Probabilistic Programming Languages (PyMC3, Stan)
  • Interactive visualizations
  • Decision-making under uncertainty


  • EPSRC Scholarship 2018: My PhD studies are funded by the "Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics, EPSRC Project: EP/R018634/1".


 Graduate Teaching Assistant

 2019 - 2020

  • Information Retrieval (H/M) - COMPSCI5011 (only marking support)

 2020 - 2021

  • Data Fundamentals (H) - COMPSCI4073
  • Systems Programming (H) - COMPSCI4081
  • Introduction to Data Science and Systems (M) - COMPSCI5089
  • Deep Learning (M) - COMPSCI5085
  • Object-Oriented Software Engineering 2 - COMPSCI2008

 2021 - 2022

  • Data Fundamentals (H) - COMPSCI4073
  • Human-Computer Interaction (H) - COMPSCI4023
  • Machine Learning and Artificial Intelligence for Data Scientists (M) - COMPSCI5100

Research datasets

Jump to: 2022
Number of items: 1.


Taka, E., Stein, S. and Williamson, J. (2022) Does Interacting Help Users Better Understand the Structure of Probabilistic Models? [Data Collection]

This list was generated on Thu Mar 23 18:44:33 2023 GMT.

Additional Information

  • Presentation of the IPME tool at the PyMCon2020 - talk available here
  • Our contribution to WP1 of the Closed-Loop in Data Science project could be found here