Posts by Collection

portfolio

publications

Generative Adversarial Network-Based Semi-supervised Learning for Pathological Speech Classification

Published in International Conference on Statistical Language and Speech Processing, 2021

This paper is about applying generative adversarial networks in a semi-supervised learning approach

Recommended citation: Trinh N.H., O’Brien D. (2020) Generative Adversarial Network-Based Semi-supervised Learning for Pathological Speech Classification. In: Espinosa-Anke L., Martín-Vide C., Spasić I. (eds) Statistical Language and Speech Processing. SLSP 2020. Lecture Notes in Computer Science, vol 12379. Springer, Cham. https://doi.org/10.1007/978-3-030-59430-5_14 http://doras.dcu.ie/25067/1/SLSP2020_Nam_DOB.pdf

Task-Related and Resting-State EEG Classification of Adult Patients with ADHD Using Machine Learning

Published in 2023 IEEE 19th International Conference on Body Sensor Networks (BSN), 2023

This paper is about applying machine learning with electroencephalogram (EEG) to classify ADHD people from healthy controls

Recommended citation: N. Trinh, R. Whelan, T. Ward and G. Derosiere, Task-Related and Resting-State EEG Classification of Adult Patients with ADHD Using Machine Learning, 2023 IEEE 19th International Conference on Body Sensor Networks (BSN), Boston, MA, USA, 2023, pp. 1-4, doi: 10.1109/BSN58485.2023.10331185. https://psyarxiv.com/zec2x/download?format=pdf

talks

teaching

Teaching Assistant

Undergraduate course, School of Computing, Dublin City University, 2020

  • Assisted Dr. John McKenna for the course “Advanced Programming in Python” on managing lab sessions for class of 40 students
  • Answered questions from students and assisted them to debug the code

Teaching Assistant

Undergraduate course, School of Computing, Dublin City University, 2023

  • Assisted Prof. Tomas Ward to teach the course CA4015 - “Advanced Data Science”
  • Answered questions from students and assisted them to debug the code
  • Built notebooks to introduce basic data science steps from data cleaning, visualisation to modelling with machine learning models.