computer sciences lab
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Computer Sciences Lab & NICTA
Opportunities for Honours projects 2009
Marcus Hutter (adapted from and thanks to Sylvie Thiebaux)
College of Engineering & Computer Science (& Friends)
DCS
DEng
CSL
InfoEng
NICTA
Research Groups
• Research focuses on:– Artificial Intelligence– Machine Learning– Logic & Automated Reasoning– Computer Vision
• 40 researchers in 4 groups:– Diagnosis, Planning, & Optimisation (DPO, aka KRR)– Statistical Machine Learning (SML)– Logic & Computation (LC)– Vision Science, Technology & Applications (VISTA)
Diagnosis, Planning & Optimisation Group
• Diagnosis– Explain abnormal situations from observations– Circuits, power networks, web services, humans
• Planning– Decide & schedule the tasks to be undertaken
to meet given objectives
– Project planning, military operations planning, robot control, solving puzzles & games
• Optimisation– Find the best possible solution to a problem– How can we predict the hardness of optimisation problems?
Contact: [email protected]
Model-Based Supervision of Composite Systems
Composite systems: feature simple components organised into ahighly reconfigurable architecture
Examples: web & grid services, power and water systemstelecom networks, traffic control systems
Supervision tools: confer the ability to– self-diagnose to detect faults in
the system and explain their causes
– self-reconfigure to restore or improve service
Project goals: develop theories, algorithms & tools for the supervision of composite systemsApproach: draws on artificial intelligence(model-based diagnosis, planning), discrete-event systems, and model-checking
Contact: [email protected]
Statistical Machine Learning Group
• Machine Learning automates the input-output mapping.
• Lots of fun projects for analysing data.Let us do both theory and application
input(data)DocumentsVideoMoleculesMicroarraysSensor NetworksMission Plans
output(analysis)Authors, scriptPeople, scenesBiological functionCancer diagnosisNovelty, alarmOptimal strategy
Magic happens …
Contact: [email protected]
Document Analysis
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b
c$c$abc$ abc$
+.
• Build document similarity measure• Build fast discriminative optimiser (SVM style)• Integrate into mail filtering system (e.g. DSPAM)
= Spam filter
Suffix tree
Contact: [email protected]
Logic and Computation Group
• Logical analysis of systems– Assure correctness, safety, robustness– Software systems (are votes counted okay?)
– Physical systems (will the robot arm break?)
– Trust and Security (can I trust this eBay seller?)
• Tools for reasoning by computers– Logical deduction: “Does it follow?”– Constraint satisfaction: “How might it be?”
• Theory behind all this– New kinds of logic for new tasks
Contact: [email protected]
Constraint Satisfaction Platform (G12)
• Constraint Satisfaction Problem– “Hard” constraints - e.g. every
team plays every other at home and away
– “Soft” constraints - e.g. fairness conditions (may be complex)
– Additional requirements from TV stations, etc. complicate further
• Difficult computational problem Contact:
L4 Verified
L4 Micro-kernel
L4 operating system used in embedded systems
e.g. sensor networks, mobile phones
“Small” trusted kernel (guarantees separation properties)
NICTA project: formally verify the kernel
Project runs until 2008
One of the most ambitious formal verification projects ever undertaken anywhere
Commercial potential if successful
Contact: [email protected]
Vision Science, Tech. & Applications Group
• Major projects:– Spectral imaging– Smart cars– Medical image analysis– Surveillance
Contact: [email protected]
Smart Cars
Pedestrian detection & tracking
Speed sign detection & recognition
Car detection & tracking
A complete driver assistance system, focusing on driver safety
Contact: [email protected]
Automatic Anatomical Structure Extraction
Topology repair Parametrisation
Detection of Alzheimer’s disease
- changes to hyppocampus implicated- doctors hand-trace each scan slice- obtain a math. representation for analysis- need to repair and parametrise the 3D data
Contact: [email protected]
Artificial Intelligence
Universal Artificial Intelligence = =Decision Theory = Probability + Utility Theory + +Universal Induction = Ockham + Bayes + Turing
• Information-theoretic,• Statistical, and• Philosophical,• Foundations of• Artificial Intelligence
Contact: [email protected]
Finally …
• These slides are at: http://www.hutter1.net/rsise/honours.ppt
• Many other projects, for exmple in:
• Traffic control [email protected]
• Game playing [email protected]
• Agent architectures [email protected]
• Artificial AI, Trust [email protected]
• Automated deduction [email protected], [email protected], [email protected]
• Satisfiability [email protected], [email protected], [email protected]
• Security protocol verification [email protected]
• If you like theory [email protected]
Apply for a summer scholarship with us !