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  • For your info, the picture is one of SyDRe, a supply restoration system which locates faults in power distribution systems and reconfigure them appropriately.
    An example of this is show in the little "Restore" window, where SyDRe says there is a fault on line l6 and suggest a reconfiguration plan opening and closing some switches.
  • there

    1. 1. Computer Sciences Lab & NICTA Opportunities for Honours projects 2007 Sylvie Thiebaux
    2. 2. College of Engineering & Computer Science (& Friends) DCS DEng CSL InfoEng NICTA
    3. 3. Research Groups • Research focuses on: – Artificial Intelligence – 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)
    4. 4. 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: Sylvie.Thiebaux@anu.edu.au
    5. 5. Planning with time, resources, and uncertainty • Uncertainty about task duration and resource consumption – Model uncertainty – Handle continuous time/res. – Design efficient algorithms – Build robust plans – Build better GUIs • Build a better Microsoft Project! Contact: Doug.Aberdeen@nicta.com.au
    6. 6. Model-Based Supervision of Composite Systems Composite systems: feature simple components organised into a highly reconfigurable architecture Examples: web & grid services, power and water systems telecom 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 systems Approach: draws on artificial intelligence (model-based diagnosis, planning), discrete- event systems, and model-checking Contact: Sylvie.Thiebaux@anu.edu.au
    7. 7. 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) Documents Video Molecules Microarrays Sensor Networks Mission Plans output(analysis) Authors, script People, scenes Biological function Cancer diagnosis Novelty, alarm Optimal strategy Magic happens … Contact: Alex.Smola@nicta.com.au
    8. 8. Bioniformatics • Build feature selector for genes • Integrate sequencing information (similarity ..) • Integrate automatic analysis of abstract + = Cancer diagnosis Contact: Adam.Kowalczyk@nicta.com.au
    9. 9. Document Analysis ab c$ 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: SVN.Vishwanathan@nicta.com.au
    10. 10. 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?) – Systems of agents (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: John.Slaney@anu.edu.au
    11. 11. 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: John.Slaney@anu.edu.au
    12. 12. 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: Michael.Norrish@nicta.com.au
    13. 13. Vision Science, Tech. & Applications Group • Major projects: – Spectral imaging – Smart cars – Medical image analysis – Surveillance Contact: Nick.Barnes@nicta.com.au
    14. 14. Smart Cars Pedestrian detection & tracking Speed sign detection & recognition Car detection & tracking A complete driver assistance system, focusing on driver safety Contact: Lars.Petersson@anu.edu.au
    15. 15. Automatic Anatomical Structure Extraction Topology repair Parametrisation Detection of Alzeihmer’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: Paulette.Lieby@nicta.com.au
    16. 16. Finally … • These slides are at: http://rsise.anu.edu.au/~thiebaux/HP.ppt • Many other projects, for exmple in: • Traffic control Philip.Kilby@anu.edu.au, Doug.Aberdeen@nicta.com.au • Game playing Adi.Botea@nicta.com.au, Nic.Schraudolph@nicta.com.au • Sensor networks Alex.Smola@nicta.com.au • Agent architectures John.Lloyd@anu.edu.au • Artificial AI, Trust Jochen.Renz@anu.edu.au • Automated deduction Rajeev.Gore@anu.edu.au, John.Slaney@anu.edu.au • Satisfiability Anbulagan@nicta.com.au, Jinbo.Huang@nicta.com.au, Jussi.Rintanen@nicta.com.au • If you like theory Tomasz.Kowalski@anu.edu.au • Apply for a summer scholarship with us!

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