Peter's Undergrad/Masters Student Project Ideas

 

I help lead UCL's research on evolutionary computation. I am happy to supervise any project that involves evolution (genetic algorithms, genetic programming, evolutionary strategies, evolutionary programming) or related subjects (artificial immune systems, swarm intelligence, robotics). If you are a final year undergrad or Masters student and interested in any of the following projects, or have some evolutionary ideas yourself, e-mail me at:

If you’d like to do a Ph.D. here at UCL and would like to discuss your project with me, then you’ll need to think of your own idea and then email me.

If you'd like to know more about the things I get up to, click here. Otherwise, here are some ideas for projects that might be good fun to try:

Parallel Systemic Computation

In recent years I have created my own model of computation and a corresponding architecture, based on natural processes. Right now we are simulating this highly parallel machine on a conventional computer and have plans to build a multi-processor version in the near future. However, another way of implementing the computer is simply to run it over a network (LAN or Internet). This project would extend the current systemic computer design and create a parallel networked version akin to grid computing. The result would be a fault-tolerant computer capable of supporting algorithms such as GAs or neural networks at high speed.

 

Evolutionary Sculptures

Evolutionary design - that's using evolution to evolve designs - is a rapidly growing area of research. One application is art, and in particular, sculpture. Using VRML (or OpenGL) to display the 3D shapes, an evolutionary algorithm can be used to explore 'sculpture-space', helping us to find some aesthetically pleasing forms. These could even be built, resulting in novel physical sculptures. Evolution has already been used by some artists and architects and the results are surprising - many quite beautiful pieces have been created using this approach. Take a peek in my book Evolutionary Design by Computers for more details.

 

Evolving 3D Printed "bug" robots

UCL now has a suite of 3D printers, allowing us to print 3D designs to sub-millimetre precisions. This project would use an off-the-shelf physics engine such as PhyX to evaluate miniature robot designs evolved by a genetic algorithm. A tiny magnet inserted into the body and placed near an oscillating electromagnet could provide a quick and easy actuator without needing to worry about power. The result could be a prototype of one of the smallest robots ever made - smaller than the size of a ladybird!

 

Machine Learning of Heart Sounds

My iStethoscope app has generated one of the world's largest databases of heart sounds, which we now have partly annotated by cardiologists, and released in a PASCAL Challenge. In this project you would attempt to classify or cluster the data into different categories that correspond to symptoms used by doctors for diagnosis.

 

Evolving Ferrofluid Patterns

Ferrofluid is a magnetic fluid - its shape can be pulled and distorted by magnetism. It works because it has nano-sized magnetic particies held in suspension of an oil-like substance. This practical project would involve linking several electromagnetics to a computer, and then using a genetic algorithm to evolve patterns of activation of the electromagnets. These would then be placed around a pool of ferrofluid, causing it to be pulled into different patterns and shapes. The result would be a physical evolutionary art system - you would be able to evolve attractive "liquid sculptures" that dance to the direction of the magnets.

 

Evolving Aerodynamic Shapes

The wings of birds, bats and insects have all evolved to be highly efficient for flight. This project would involve the use of a genetic algorithm to evolve an aerodynamic shape for unpowered flight. Using a mixture of software simulation and real-world testing, a shape designed to increase the time spent airborne could be evolved. This might use the spiraling flight of a sycamore seed, the drifting flight of a dandelion seed, or the gliding flight of a bird. Because real-world testing is so time-consuming, methods to interpolate fitness scores and perform simple simulation will be essential.