Updated for 2020 semester 2
A number of projects are possible in all areas, I
list the ones I could think of, please also make
up your own ideas, and talk me into them. Most of
these can be extended to a PhD or reduced for a 3rd
year single semester project or a Summer Research Scholarship,
or something in between. Also, most of them could range from
an AI investigation, to SE construction of a
platform, to HCI/IS analysis, and so on.
If you are interested in any of the following
(or similar) topics and would like to see if
you might want to do a project in this area,
please e-mail me
or come and see me in N332.
I suggest you consider my "high priority" projects first. During the COVID lockdown, some of the projects below which mention physiological signals could be done using webcams and computer vision approaches to extract e.g. heart rate. Also, we have lots of data for many of these which has not yet been analysed ...
Please select the topic and type of project and
click the display button.
Human responses in complex interaction projects
interested in combining advanced bio-inspired computing techniques
and eye gaze and physiological observation of users to model their
conscious and non-conscious behaviour during interaction tasks. This area
is a meld of my eye gaze / physiological signals / generating art projects
and my neural nets and deep learning / evolutionary algorithms projects.
With major funding starting in 2016 and again in 2019, this will be a priority for at least 3 years.
*** Detecting empathy:
We have access to a large dataset of videos classified by degree
of empathy shown in the interaction. The project would firstly involve
human experiments showing the videos to subjects, and detecting the
degree of empathy from their responses and training a neural/deep
AI for prediction and recognition.
*** Bio-inspired computing and implicit preferences:
Can we infer what a user likes by observing their eye gaze and
physiological signals? A number of projects are possible here,
ranging from bio-inspired computing approaches to analyse data, to
design and running an experiment to collect data.
*** Passive and active stress/fatigue monitoring
Our previous results show we can detect stress in from physiological/biometric signals from people, can we also detect fatigue? Does dynamic presentation of information improve or hinder recognition?
I am interested in a few specific
NLP topics partly related to teaching.
The use of the Piazza
becoming commonplace. In large courses, many of the same questions
are asked each year, so an automated question answering tool would
be very valuable, and would require innovative research.
Mobile and Wearable Device projects
I am interested in
topics such as interactive interfaces for mobile phones or tablets, in
the use of novel mobile devices and wearable or unobtrusive devices, and in eReaders.
I am interested in the control of virtual and physical
objects via smart phone platforms. Previous work has used iOS devices
for generating Art, and for 3D control of virtual objects. The next
steps would be either
moving to the control of real world objects - a robot arm,
interfacing with a heart rate sensor for HCI experiments, or
enhancing the evolutionary component for generating Art.
*** Mind altering wearables:
We have some biofeedback brain sensor devices such as Muse,
Thync, foc.us. A number of projects are possible to collect
data in experiments.
We have some new (pre-release) Myo
gesture control armbands. This project
will be to extend some programs which use its capabilities, most
likely in recognitions of fatigue.
The use of eInk technology is likely to replace the
use of paper books in not too many years. There are few if any
scientific comparisons of eReaders. Our current work has produced
surprising results, its not always the big companies with the best
interfaces. Our next steps would be either
- to examine large screen eInk devices, and the newer devices
with integrated LED lights for reading in the dark; or
- to modify the software and hardware to obscure or contradict
the branding to quantify brand recognition effects.
Face Recognition projects
I am interested in
topics such as image processing for face recognition, HCI research tool
to collect facial images, biologically plausible architectures for face recognition,
building and modifying computer models of real faces. No previous work on face
recognition is necessary.
Caricature: Comparing a specific face to an averaged face allows
us to determine how this face differs from the average. If this difference
was increased (an inverse of morphing), we can generate a caricature of the
face. (See also 3D face model project, a tool is almost ready.)
Eye gaze: Use of an eye gaze detector and (optionally) an EEG
'hat' allows learning when a user is looking at a face they
recognise versus one they do not recognise. If we can tell from eye
gaze we have a simple specialised lie detector for the question "do
you know this person"! Overall, this use of eye gaze has a number of
applications, primarily in the security domain.
View morphing: View morphing between two images of an object taken
from two different viewpoints produces the illusion of physically moving a
virtual camera. We generate compelling 2D transitions between images. Initially
we will use the same face with small rotations and produce intermediate images
to produce a realistic QuickTimeVR head.
Deep fake face transfer: Use/extend the recent deep fake tool and
similar face transfer tools. Projects could involve extension of such
deep learning models, to human experiments to see how well people can
detect such fakes.
3-D Face model: An average face 3D model can be constructed from
a single face image and animated via rotation, a simple face
expression model, or illumination. This can then be used to recognise
faces in multiple poses, expressions or lighting. (A tool was
built, which can be extended or used for caricature etc.)
Physiological Signals projects
We have a Mind Attention
Interface lab, which now also has physiological signal devices such as Galvanic
Skin Response, and ElectroCardiogram equipent as well as the Eye Gaze and EEG.
Please see the Eye Gaze section also as many of those projects could use the
physiological signals to augment or replace Eye Gaze and/or EEG.
*** Revocable biometrics:
Most signals recorded from people could be
used as biometric signals for identification or authentication.
Like passwords, these should be under our control and revocable
at will. Possible solutions include crypotgraphic, blind source
separation or machine learning approaches.
Previous projects have built an infrastructure for collecting
data in various driving scenarios, and collected data. Our next steps would be either
to analyse the data and demostrate that the hypotheses are upheld, or
collect and analyse data from a small targeted experiment using this infrastructure.
Driving simulator: we have a driving simulator setup with a force
feedback steering wheel with which we have recorded physiological
reactions in simulated accidents. Projects in this area could include
extending the setup to use eye gaze / EEG or other sensors, or to
improve the analysis or ...
Eye Gaze projects
We have a Mind Attention
Interface lab, which has Eye Gaze and brain monitoru equipment, and is run in the
Interaction lab room. I am particularly interested in
interesting uses of the eye gaze equipment, as well as validation
using the fNIRS/EEG equipment.
*** Mac OS Eye gaze tool:
Eye gaze trackers are becoming commodity hardware. This project will be to
use one of the new eye gaze trackers we have to develop a Mac OS program using eye gaze.
Face recognition: see the Eye Gaze project in Face Recognition section
Generating art: see below
record EEG/fNIRS and eye gaze while users look at particular kinds
of images/scenes. This project could involve:
- software engineering construction of a platform for such work
- reliably extract EEG/fNIRS signals known to occur for certain types of
images using AI techniques
- unsupervised AI techniques for finding new EEG/fNIRS signals
- correlating known/unknown EEG/fNIRS signals with eye gaze path
- unsupervised AI techniques for characterising eye gaze paths
Attention: what do people see in images? What is it about some images
that attract our attention and presumably interest where other
seemingly similar images are less interesting?
Some previous work has been
done generating Mondrian-like images (see under Evolutionary algorithms).
Various projects are possible in this area. These range from the design or
implementation of a simulator, to further development of the Mondrian work,
to computerised analysis of artistic esthetic, and to generation of
other kinds of artistic images.
3D simulator: to show images generated in a 3D visualisation
which is either technically interesting or of
: a number of further developments are possible here
(some initial work done, involved creation of a new drawing tool,
which also incorporates some support for a 3D mouse, and initial
support for wiimote)
- further develop Mondrian image generation process
- extend interactive interface
- extend to new mobile devices
: Converting live-action film or images to an animated form
is called rotoscoping
This project would use existing line detection and optical flow software to
automate the conversion of a film to an animated form.
Generate more art: using some other kind(s) of artistic
Faces: modify faces in an identi-kit fashion and present
them to users for selection of likeness
Eye gaze: use eye gaze monitor to substitute for manual
selection of likes and dislikes (see Eye Gaze section)
Analyse esthetics: can a neural network learn what I find
esthetic? (Initial work indicates that this
is possible to some extent - this would be interesting to
Reaction: what 3D effects are more powerful? This lends
itself best (I think) to an IS/HCI project.
Smart disk cataloguer and synchroniser
I have many files on
multiple computers organised in different ways, and
would like to be able to keep track of them, etc. I
suspect this is common, especially if we include files on google docs
or facebook etc. None of the software I have seen solves my problem. A
good solution would be very useful for me and many others.
I am interested in bio-inspired computing techniques, and have most
expertise in neural networks, fuzzy logic and evolutionary algorithms.
I am willing to discuss possible topics using Swarm Intelligence, Ant
Trail Optimisation, Immune Networks and so on as well.
MATLAB and hadoop
This project is to continue the use of our
bio-inspired computing techniques (mostly fuzzy signatures) via hadoop
on clusters of commodity hardware. The cluster has been setup over the summer 2014/2015 so its ready for some experiments!
I am interested in topics such as
extracting rules from neural networks,
information retrieval using neural networks, data mining and feature
selection, cascade neural network structures, hierarchical neural
network structures, and neural network applications. I have published
papers in all of these areas with former students so there is plenty of
earlier work to build on.
Most projects will use the very popular backpropagation
neural network training algorithm, and sometime the self-organising
Cascade neural network stuctures can be built automatically without
making decisions as to the number of neurons required to solve a
problem by adding single neurons. This project would investigate the
use of larger chunks such as feature maps as cascade components,
which would be useful for recognising images (including faces, or
generated art). (Some progress made using shared weight feature-map
'chunks', which can be extended.)
Rule extraction: Neural networks can learn complex tasks but face
the problem that human beings do not trust them as they can not
understand _why_ a particular decision is made. This project
focuses on rule extraction for explanation.
*** Deep learning for handwriting recognition:
This project involves personalisation of deep learning tools for
automated handwriting recognition, starting with existing tools
and benchmark datasets and extending to a practical tool.
Various deep learning architectures such
as deep neural networks, convolutional deep neural networks,
generative adversarial networks, deep belief networks and recurrent
neural networks have been applied to fields like computer vision,
automatic speech recognition, natural language processing, audio
recognition and bioinformatics where they have been shown to
produce state-of-the-art results on various tasks. This project
is to extend previous work using neural networks for deep learning
using eye gaze and physiological data.
Cognitive modeling: The recommendation architecture model is based
on a system theoretical approach to understanding higher cognition in
terms of physiology. The model has some similarities to conventional
neural networks but remains true to biological information flow constraints
and does not suffer from the forgetting problem. This project could extend
previous work in applications of this model in information filtering and
face recognition, or extension of the model to demonstrate some of the
properties observed in human consciousness.
I am interested in topics
such as automated construction of fuzzy rule bases
from data, hierarchical fuzzy systems, fuzzy interpolation, information
retrieval using fuzzy logic, universal approximators, and fuzzy
logic applications. I have published papers in all of these areas with
former students so there is plenty of earlier work to build on.
*** Interval Likert scales and fuzzy intervals:
Likert scales are commonly used in HCI to capture qualitative
information from users, but can not capture the uncertainty in
the mind of the subject. By selecting intervals, this can be
captured, and analysed using non-singleton fuzzy systems.
Fuzzy document filtering: Web search engines return many documents
which are not relevant to queries. Fuzzy techniques to enhance the
results from search engines will be very useful. This project will
investigate a number of fuzzy techniques for this purpose.
Combining uncertainty: Fuzzy logic is a technique which deals with
uncertainty well. Sometimes data contains multiple kinds or sources
of uncertainty. For example, a pedestrian could report that he saw
someone he was quite sure was stealing something. He was not certain,
and his own reliability is another (different) kind of uncertainty.
This project is to develop some methods to combine different kinds
of uncertainty in intelligence led investigation. (Data from a
company specialising in this area will be available.)
A pattern tree is a tree which represents the pattern for
an output class. The output class is located at the top as the
root of this tree. The fuzzy terms of input variables are on
different levels of the tree. They use fuzzy aggregations to aggregate
from the bottom level to the top (root). For a classification
application which involves several output classes, the worked model
should have as many pattern trees as the number of the output classes,
with each pattern tree representing one class. This project will
extend our initial work as published in IEEE Transactions on Fuzzy
Fuzzy Signature Neural Networks:
A neural network model using fuzzy signatures as hidden neurons
has shown good results. This project would extend that by
finding a quicker automatic way to generate the signatures, to
add filtering, and so on.
There are several
optimisation methods inspired by natural processes,
It has been shown that evolutionary algorithms are efficient tools for
solving non-linear, multi-objective and constrained optimizations.
The principle is a search for a population of solutions, where tuning
is done using mechanisms similar to biological recombination.
If artificial 'organisms' encode the components of an abstract
computer generated picture, an individual could identify nice and
not nice images repeatedly to generate some 'art' which is tuned
for their esthetic sense. Software built here is available to be
be extended and improved. This project is ideal if you would like
to create Art but do not believe you are artistic (but can recognise
something you like).
Scheduling: A previous student has worked on a GA for University
exam scheduling. An extension of this work or comparison with
bacterial algorithms would be an interesting project. The ANU
exam schedule data for last year are available, and the ANU
timetabling section is happy to assist.
Web Teaching projects
I am interested in
topics related to the way I teach my Web Development and Design course as well as
innovative ways of teaching via the web.
With the 3D MaxWhere
for example, a 3D layout of teaching materials would allow a much better
understanding of content in context for students. This project would involve
development of layouts and conversion of existing materials, to gain insights
for the development of a tool to do this automatically.
I am interested in tools which would assist me in automating tasks which would
be impossible for a single or few course staff to do, in settings like a MOOC
delivery of the course, possible next steps would be to continue one of:
a tool to automate distribution and anonymisation of reports for peer marking,
a tool to communicate between Wattle (an ANU Moodle imlementation) and the free
Piazza course forum tool, so allow social networks peer approval, and
a tool to implement badges for achievements in a course.