Teaching

🎓 Current Teaching

Quest Lecture for the Machine Learning Systems Course

Topic: LLM 101 and Model Compression

• 📊 Slides
• 🎥 Video Recording

👨‍🏫 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

• Staff Award for MLP TA Service - View Award Letter

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