This series of six weekly webinars is held on Tuesday evenings, 5:00 - 6:00 pm, from 20 January - 24 February 2026 for students in Year 12 (S5 in Scotland/Year 13 in Northern Ireland).
These sessions are completely free and open to prospective students who would like to learn more about different topics in Computer Science. They are led by female and non-binary members of the Department and explore a topic of the presenter’s choice.
The sessions are run as a Zoom webinar and designed to be interactive. Throughout the seminars, you are asked to answer questions, complete quick quizzes and have the opportunity to ask questions.
Before signing up, please read our Code of Conduct for online events.
To sign up for the seminar series, please fill in this form. You will receive an email containing the link to the webinar a few days before it is due to take place.
If you’d like to be considered for the Women in Computer Science programme, for female and non-binary students in Year 12, please see this page.
You can find the topics of the seminars below:
If you'd like to watch the recordings of seminars from previous years, please see this page.
20 January - Computational complexity
What makes some problems easy to solve and others seemingly impossible even for the fastest computers? In this talk, we’ll explore how mathematics and computer science meet in the study of computational complexity, a field that asks what can (and cannot) be efficiently computed. We’ll see how simple mathematical ideas like counting, combinatorics, and logic help us classify problems according to their intrinsic difficulty. From the elegant theory of algorithms to the famous P vs NP question, complexity theory reveals a hidden geometry of problems, connecting proofs, puzzles, and computation in surprising ways. Along the way, we’ll discuss how questions about efficiency of algorithms lead to some of the most profound open problems in modern mathematics.
27 January - The Quantum Computing Bottleneck: The mathematics of fault tolerance
While quantum algorithms offer exponential speedups for specific computational problems, current quantum computers are impractical due to noise and decoherence. This seminar bridges the gap between abstract theory and practical engineering. We will explore the linear algebra governing qubit state transformations and mathematically model "noise" , focussing on using these tools to see how Quantum Error Correction achieves lower error rates in quantum computers.
3 February - Building blocks of Computer Science
A whistle-stop tour through the different layers of abstraction that make up a computer.
10 February - How do machines learn? An introduction to neural networks and LLMs
How does a machine learn to recognize your face, translate a sentence, or chat like a human?
In this talk, we’ll talk about how machines learn, beginning with the building blocks of neural networks: artificial neurons, layers, and learning from errors. We’ll briefly introduce the mathematical engines behind them, gradient descent and backpropagation, and see how simple ideas scale into powerful systems. We’ll finally look at large language models and how they turn massive amounts of text into convincing conversations, revealing what’s really behind chatbots like ChatGPT.
This is an invitation to look under the hood of AI and see that it’s not magic: it’s something you can understand, question, and maybe even build yourself.
17 February - Behind the scenes of video streaming: How is video quality measured
Have you ever wondered how Netflix or YouTube decides what video quality you see when your internet connection changes? This talk takes you behind the scenes of video streaming to explore how “video quality” is measured and used to deliver the best possible viewing experience. We’ll examine how streaming services automatically switch between different video qualities, why this matters, and how engineers determine what looks “good enough.” You’ll also discover how human vision plays a key role in judging video quality, and how algorithms are designed to predict which quality degradations human observers will be able to notice and which will disrupt their viewing experience.
24 February - Hardware-software interface: How it contributes to better computer security
Modern computer security relies heavily on software-based defences, including analysis tools that look for bugs and patches that fix reported vulnerabilities. Although safer programming languages and improved system designs have significantly reduced many risks, memory safety problems still remain as a major security concern, accounting for over 70% of serious vulnerabilities in Microsoft and Chromium codebases. In this talk, we explore how rethinking the boundary between hardware and software opens up exciting new opportunities for stronger security guarantees. We show how this interface represents a design space full of trade-offs, and how the design approach requires piecing together multiple layers of the computer to build a secure and practical system.
