🎓 Current Teaching

Quest Lecture for the Machine Learning Systems Course

Topic: LLM 101 and Model Compression

👨‍🏫 Past Teaching Experience

Lead Teaching Assistant - Machine Learning Practical

University of Edinburgh (2017-2019)
Course Website

Key Responsibilities

  • Created comprehensive weekly teaching materials using Jupyter notebooks
  • Developed deep learning tutorials from scratch using NumPy (Term 1)
  • Led PyTorch/TensorFlow tutorials and cloud computing guides (Term 2)
  • Designed and structured coursework materials
  • Implemented coursework boilerplate code and tutorial documentation
  • Supervised student groups on deep learning research projects
  • Maintained the MLP GitHub repository

Tutorial Series

🖥️ GPU MLP Cluster Usage
  1. GPU Clusters Lecture
  2. MLP Cluster Lecture
  3. Live Demo: Training/Evaluating Multiple Models
  4. Live Demo Continued and Q/A Session
☁️ Google Cloud Platform for Deep Learning
  1. Local Setup & GCP Interface
  2. GPU VM Setup & Experimentation
🧠 Advanced Neural Network Concepts
  1. Relational Networks
  2. Relational Networks & HyperNetworks
  3. Neural Attention & Transformers Intro
  4. Transformers Deep Dive
  5. Transformers & Meta-Learning Intro
  6. Meta-Learning Advanced

Teaching Assistant - Digital Innovation

Lancaster University (2014-2015)

  • Led lab sessions focusing on digital electronics and C++/Arduino programming
  • Evaluated student coursework and collaborated with teaching staff

🏆 Teaching Awards & Recognition

2020-21

2019

  • 5 Teaching Award Nominations:
    • Best Practice in Inclusive Learning Award
    • Best Support Staff Award
    • 2x Best Student Who Tutors Award
    • Best UK PhD Tutor Award
    • View Nomination Letters

2018

  • Nominated for Best Student Who Tutors Award