Teaching

Lead Teaching Assistant for the Machine Learning Practical course - Edinburgh University - 2017-2019

• Heavily involved in creating all weekly teaching materials, usually in the form of Jupyter notebooks, in which the students were required to build their own deep neural networks from scratch in numpy in Term 1. Further, in Term 2, I am the main contributor of tutorials on Pytorch/Tensorflow as well as cloud computing guides and GPU cluster debugging tutorials.
• One of main teaching staff involved in designing/structuring the coursework. Furthermore, the main contributor that implements any and all coursework boilerplate code/tutorial notes/guides.
• Supervision of student groups on their deep learning projects in term 2, where students can choose any deep learning related topic and work on a research project, to be implemented in Pytorch/Tensorflow. The main output is a report in ICML paper format. This component requires supporting students in writing a concise, readable and compelling paper.
• Maintenance and development of the MLP github repo
• Marker for term 2 research projects.
• Support for technical issues with GPU Clusters and Compute Cloud providers.
• Running the GPU MLP Cluster Usage Tutorial:
  • Videos:
    • Tutorial 01/04: GPU Clusters Lecture
    • Tutorial 02/04: MLP Cluster Lecture
    • Tutorial 03/04: Live Demo of Training/Evaluating multiple models on the MLP cluster
    • Tutorial 04/04: Live Demo Continued and Q/A Session
• Running the Google Cloud Platform for Deep Learning MLP Projects Tutorial:
  • Videos:
    • Tutorial 01/02: Live Demo - Local machine setup + navigating the GCP web interface
    • Tutorial 02/02: Live Demo - Setting up a GPU VM and running an experiment + rsyncing to and from a VM/local machine
• Running the Advanced Neural Network Concepts Tutorial Series:
  • Videos
    • Tutorial 01: Relational Networks
    • Tutorial 02: Relational Networks Continued + HyperNetworks
    • Tutorial 03: Neural Attention + Transformers Intro
    • Tutorial 04: Transformers Continued
    • Tutorial 05: Transformers Continued + Intro Meta-Learning
    • Tutorial 06: Meta-Learning Contined

Teaching Assistant for the Digital Innovation Course - Lancaster University - 2014-2015:

• Supporting the learning of students in the lab sessions via instruction and guidance
• Evaluating students coursework via marking and discussions with other teaching staff
• Course relating to integration of digital electronics and low-level programming in C++/Arduino

Teaching Award Nominations

• 2020-21 Staff Award for my service as the MLP TA - Read Award Letter
• 2019 5 Teaching Award Nominations on Best Practice in Inclusive Learning Award, Best Support Staff Award, 2 x Best Student Who Tutors Award and Best UK jPhD Tutor Award - Read Nomination Letters
• 2018 Nominated for the Best Student Who Tutors Award