2024 list
Complete list of design briefs to be advertised to students for 2024 group design projects.
(text transcluded from individual project descriptions - click on project title to edit original page)
Acoustic Land Management
Client: Adham Ashton-Butt, BTO <adham.ashton-butt@bto.org>
Land managers are often responsible for restoration projects, in which they make changes expected to benefit wildlife over time. One very useful source of evidence is acoustic data recordings. This project is intended to create an interactive application that can be used by land managers to visualise, make decisions, monitor, and evaluate their interventions, based on bioacoustic survey data processed through the BTO acoustic pipeline and enhanced with machine learning methods.
Braille Predictive Text
Client: Gregory Hargraves, Paige Braille <greg@paigebraille.com>
David MacKay’s Dasher was a radical predictive text system where a machine learning language model helped users with disabilities by guiding them to zoom in to more likely possible texts. That’s no use for people with a vision impairment, who can’t see the guidance or easily operate animated graphical interfaces. This is an opportunity to work with a team who have recently augmented the classic mechanical Braille typewriter with internet connectivity. Your prediction model will help users to learn and master Braille, by offering appropriate spoken suggestions on what word they might be typing and (if needed) remind them which keys they might need to press next. All this will have to be designed in a way that is helpful, motivational and accessible, not an additional obstacle to learning Braille!
Climate Foresight
Client: William Jones, Embecosm <william.jones@embecosm.com>
Dynamic Causal Modeling is a Bayesian statistical technique for reverse engineering time series data. One of the ongoing challenges in applying such statistical models is how to visualise the multiverse of possible outcomes that the algorithm derives. Your goal is to create an evidence-based visualisation of possible climate futures that allows users to interrogate and compare projections from a complete simplified carbon-climate model within the Dynamic Causal Modeling framework.
Component Quest
Client: Stephen Devlin, Sensors CDT <sd2030@cam.ac.uk>
The electronics industry faces chip shortages, rising costs, and increasing e-waste. This creates demand for secondhand components, but it can be difficult to identify and value them. Develop a smartphone app that uses AI to identify and value electronic components (usually still mounted on PCBs) using the phone camera. The app should handle a wide range of components, provide current market value, and link users to a marketplace to buy and sell them.
Copilot for Business
Client: Jason Mashinchi, Cambridge Kinetics <jason.mash@cambridgekinetics.com>
We’re all familiar with the code generation capabilities of ChatGPT and GitHub Copilot. That’s fine for experienced programmers, but how could an AI coding tool support people who have never written a line of code? Your goal is to create a user friendly natural language interface that not only generates code for extracting and visualising data from an arbitrary business database, but helps non-programmer users to understand how that code works, recognising and correcting bugs or hallucinations in the generated code.
Creative Writing Coach
Client: Rachel Thorley, Inkli <rachelthorley@gmail.com>
Will human authors be replaced by AI? Language models can convincingly generate human-sounding text and automate many writing tasks, even contributing to novels! Instead, could they be harnessed to make us all more creative? The goal of this project is to create an app in the style of Duolingo. This app will use bite-sized, gamified lessons to help students write more creatively, with poetic imagery, dramatic tension, and vivid characterisation. Experiments show that a standard LLM (with carefully designed prompts) can provide useful feedback. Your app needs to engage and motivate students to become more fluent and confident creative writers.
Disability Bias Explorer
Client: Cecily Morrison, Microsoft Research Cambridge <cecilym@microsoft.com>
Recent work led by a team at ethical AI initiative Hugging Face (arXiv:2303.11408) demonstrated a tool that could be used to interactively investigate some of the race and gender biases that have become encoded in major text to image generation systems. Your task is to create a similar tool that could be used to demonstrate image generation biases relevant to visual disabilities. You may also need to consider how this tool can be made accessible to users who have visual disabilities themselves.
DoS D-Stress
Client: Simon Fothergill, Cam AI <simon@cam-ai.co.uk>
The very first AI chatbot was the psychotherapist Eliza. For young people today, mental health is more challenging than ever, but we aren’t using LLM technology in ways that reduce stress. Your goal is to create a de-stressing experience, potentially including responsive sound and imagery alongside short generated text exchanges that respond to what is stressing you. A fully automated chain should direct stressful content (e.g. an email from your DoS) directly into the system so that you can be properly de-stressed before you even read it.
Envisioning Nairobi
Client: Nkatha Gichuyia, Urban Re-engineering Taskforce <lindankatha@gmail.com>
Large cities around the world are grappling with plans to accommodate environmental, social and climate change. But there is a huge gulf between the technical software of geographical information systems and infrastructure planning on one hand, and the retail and entertainment data that is promoted in consumer products like Google Maps. The city of Nairobi is thinking ahead through visionary planned cities as Nairobi Railway City, Tatu City, and the Konza Technopolis, that aim to present models of how an environmentally sustainable and climate-resilient urban area developments in a carbon-constrained environment can be delivered. Your role is to prototype a new social mapping tool that could engage members of the local population in these discussions, visualising data, plans, priorities, and their personal implications.
Future Health and Fitness
The Terra API unlocks health and fitness data from diverse sources, including popular wearables and fitness apps like Fitbit, Apple Watch, Oura, and 70+ others. Your challenge is to leverage the Terra API to develop an innovative and creative product that enhances the way people engage with health and fitness data. We're looking for an application that does more than track metrics. Your project needs to inspire, motivate, and transform users' health and fitness journey.
