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AAi Blackfriars BuildingAAi Business Model: RED AnalyticsThe RED ModelThe RED ApproachAAi has envisioned and evolved a uniquebusiness model - the RED Analytics model, athree-dimensional initiative that will driveFor the RED Analytics model to be long-termsustainable and successful, the key strategiccomponents will require AAi to: high-quality Research, high-calibre analytics Education high-impact Development with Industryand GovernmentBe a national and global hub thatencourages cross-disciplinarycollaborations and linkages with academicand industry partners Build a think tank with world-classresearch qualities, capabilities andrecognition Provide a very clear path to impact on, andmarket to, UTS data science and big dataanalytics Create a sustainable revenue model thatis supported in turn by a robust humanresourcing model.in the areas of data science and big dataanalytics.This positions AAi and UTS as one of the firstresearch groups (and probably the only one)to adopt this approach either in Australia orglobally.The RED model, though simple in concept,is in actuality a tightly integrated complexmodel requiring business vision foresight andmanagement sophistication. This calls forprofessional team building, adequate funding,strong industry engagement and partnerships,creating revenue streams through product spinoff and commercialisation and venturing intoprogram level consulting services.11

AAI DIRECTOR:PROFESSOR LONGBING CAOHomepage: http://www-staff.it.uts.edu.au/ lbcao/In Data Science and Advanced Analytics, Prof Cao12 Was one of the very few originally advocatedthe concept of “Data Science”, founded andchairs the IEEE Task Force on Data Scienceand Advanced Analytics, the IEEE InternationalConference on Data Science and AdvancedAnalytics, and ACM SIGKDD Australia andNew Zealand Chapter. Formed the lab “Data Science and KnowledgeDiscovery” at QCIS, and then the AdvancedAnalytics Institute (AAi) at UTS dedicated todata science RED. Established the globally-first Master ofAnalytics (Research) and PhD Thesis: Analyticsat UTS. Founded and drives the annual event BigData Summit in Sydney and Canberra widelyengaging industry, government and academia. Provides independent and insightfulconsultancies to many tier-one industry andgovernment organizations in Australia andglobally.

Longbing’s interest in data miningand machine learning has mainlybeen focused on complex dataanalytics, non-iidness learningfor big data analytics, coupledobject analysis, pattern relationlearning, domain-driven datamining/actionable knowledgediscovery, combined mining, andmulti-structured data learning forcomplex data and environment,as well as infrastructure, solutions,systems, algorithms and services forenterprise data mining and businessanalytics applications.ProfessorLongbing Caowas granted his first PhD in PatternRecognition and Intelligent Systemsfrom the Chinese Academy of Sciencesand was awarded another in ComputingScience by the University of TechnologySydney (UTS). In 2011, with the strategicsupport from the University and relevantfaculties and centres, he founded theuniversity research facility, the AdvancedAnalytics Institute. He formed and is acore member of the Data Sciences andKnowledge Discovery Lab in the Centrefor Quantum Computation and IntelligentSystems at the Faculty of Engineeringand IT, UTS. He is also Research Leaderof the Data Mining Program at theAustralian Capital Markets CooperativeResearch Centre, Chair of the IEEE TaskForce on Data Science and AdvancedAnalytics, Chair of the IEEE Task Forceon Behavioral, Economic, Socio-culturalComputing, was the Chair of the IEEETask Force on Educational Data Mining,and the Chair of the ACM SIGKDDAustralia and New Zealand Chapter. Heis a Senior Member of IEEE, the SMCSociety, and the Computer Society.He serves as associate editor or guesteditor on many journals, as conferenceco-chair of KDD2015, PAKDD13 andADMA13, and as program co-chair orvice-chair of PAKDD11, ICDM10, IAT11,and ADMA10, among others. He is aprogram committee member on some100 conferences including KDD, ICDMand AAMAS. He joined UTS in 2005 afterserving as an editor, marketing strategistand then Chief Technology Officer inChina.Longbing initiated and is leading researchon non-iidness learning in big data, datascience and analytics science, behaviourinformatics, agent mining, and domaindriven data mining, as well as generalefforts on data mining, machine learning,and open complex intelligent systems. Data science and big data analytics:as a pioneer researcher initiatingand leading research, educationand development on data sciences, Behaviour and economic computing:he initiated and has been leadingresearch on behaviour informatics,focusing on complex behaviour andsocial modelling and representation,and analysis of patterns, exceptions,networking, sentiment, grouping/community formation, nonoccurrences, evolution anddynamics, and risk, impact andutility for in-depth understanding andactive behaviour management. Hiscontinuous work in financial analyticsinvolves smart trading, marketsurveillance and cross-marketanalysis. Agent mining: the proposed conceptinvolves fundamental infrastructure,agent-based distributed multisource data mining, agentbehaviour learning, agent-basedcloud analytics, and applicationsin financial trading agents, amongothers. Artificial intelligence and intelligentsystems: including knowledgerepresentation, software engineeringand system design for open complexintelligent systems, meta-syntheticcomputing and engineering, andlearning systems.Longbing has created several specialinterest groups and IEEE Task Forcesto promote the above research on bigdata, data science, advanced analytics,behaviour and economic computing,agent mining, domain driven data mining,enterprise data mining and applications.Under his leadership, the UTS AdvancedAnalytics Institute, a cross-facultyuniversity research institute, is effectivelyimplementing a mixed business modelby integrating high-quality Research andhigh-calibre Education with high-impactDevelopment (RED) in broad-basedanalytics, to best advance theoreticalinnovation, education and training, andhands-on practices in real world big dataanalytics through a highly interdisciplinaryand cross-domain approach. UTS:AAi collaborates with leading expertsin the faculty of Engineering and IT,Science, Business, Health and Lawat UTS and with experts from industryand government, locally and globally.Longbing led to creat the first globallyavailable research degrees in analytics:the Master of Analytics (Research) andDoctor of Philosophy: Analytics. UTS:AAi is recognised as the largest researchgroup in analytics in Australia withdemonstrated wide engagements andhigh business impact acknowledgedby the community such as in the firstWhite Paper on big data issued by theAustralian Federal Government.In the last 20 years, he has been highlyinspired by challenging and critical realworld business, social and economicproblems. Driven by real-life big data, hehas continuously proposed novel andfundamental research issues, togetherwith the synergy of innovation, learningand practices in big data analytics.He has led major grants and projectssponsored by Federal Government, StateGovernments, banks, stock exchanges,financial firms, telecommunicationproviders, airways, insurance companies,health service providers, online andretail business, education providers, andworld-class vendors, working on bigdata analytics for business intelligence,customer relationship analysis, marketinganalytics, behaviour analytics, riskanalytics, community analytics, serviceenhancement, fraud detection, exceptionanalysis, debt analytics, learninganalytics, and compliance analyticstowards smarter business and decisionmaking. He has built and led a teamwith advanced expertise and hands-onexperience widely recognised in relevantcommunities, in enterprise applicationsof big data analytics and intelligentsystems and decisions in such areasas payment accuracy, fraud detection,outlier detection, risk management, socialsecurity, market surveillance, health care,insurance, investment, marketing, capitalmarkets and more. The team’s analyticswork and innovation-driven problemsolving has led to savings of millions ofdollars per year for major industry andgovernment.13

AAi Research Programs and CapabilitiesAs a pioneer in the age of big data and data science,AAi provides interdisciplinary innovation, expertiseand leadership in data science and engineering,analytics science and services, behaviour and socialinformatics, economic computing and advancedstatistics. Our team is globally recognised in areasthat include big data analytics, business analytics,data mining, machine learning, behaviour analytics,government analytics, financial analytics, multimediaanalytics, social analytics, bioinformatics, andrisk analytics and management. AAi offers crossdisciplinary, cross-domain research capabilities andhands-on experience in data science and big dataanalytics across historical data, real-time informationand future trends. The Institute fosters dedicatedresearch, education and development (RED) resourcesfor advanced analytics in the following researchprograms: Fundamental Issues in Data and Analytics Science Bioinformatics, Health and Medical Analytics Business and Social Analytics Multimedia and New Media Analytics Smarter Living Technologies14

Bioinformatics, Health and Medical AnalyticsProgram Leaders: Associate Professor Jinyan Li and and Professor Patricia DavidsonAt AAi, we are undertaking frontier researchin bioinformatics, health and medicalanalytics in the areas of: Multiple sources of health, medical andpublic data analysis Detection of signature patterns andtandem repeats in genomic sequences Rule discovery and disease geneidentification from miRNA and mRNAexpression dataSystematic approaches for analysinginterplay between multiple factors ofpatient, provider and health systemaspects B factors, O-ring hypothesis and watertheories for protein binding hotspotpredictionPatient behaviour and sentimentanalysis, and personalised service andtreatment recommendation Substructure module detection inprotein interaction networksEarly warning and prediction ofhealthcare problems Conformational B-cell epitopepredictionRisk rating and factor analysis of highrisk cases, areas and scenarios Antibody-antigen interactions ininfectious diseases such as H1N1influenza A Big medical and health data analyticsand decision-support Data-driven, evidence-based healthand medical benchmarking, hypothesisgeneration, and verification Instant detection and early prediction,warning, and intervention in relation tothe misuse, underuse and overuse ofhealth services and/or resources andfraud Performance evaluation, reviewand optimisation of health serviceresources, procedures, processesand treatments and service deliveryobjectivesDriven by the big data accumulated inbiological, health and medical services, AAiresearchers specialising in bioinformatics,health and medical analytics conduct datadriven evidence-based research that looksfor interesting new hypothesis, verificationof hypothesis, benchmarking, cause-effectanalysis, and active disease, patient andtreatment management.Our researchers have an establishedtrack record in developing and deployinganalytical tools for biological, healthand medical research in-house andin collaboration with major industryorganisations. AAi welcomes furtheropportunities for collaboration withhospitals, government, commercial andclinical groups.15

Business and Social AnalyticsProgram Leader: Professor Longbing CaoThe exponential increase of business and socialdata has become an emerging and criticalchallenge for all major businesses, governments,social domains and organisations. Businessand social domains contribute to major bigdata problems and value. Business and socialanalytics specialists at AAi are harnessing thecomplexity of this data to create real world problemdriven theoretical breakthroughs and practicalinnovations by engaging statistics, computerscience, behavioural and social sciences, businessprocess management, computational intelligence,behavioural economics, behaviour computing,social computing with data sciences and intelligencesciences.Our researchers are working on frontier researchand applied innovation in: 16Complex business and social data analytics,learning and mining; Behaviour representation, reasoning, learningand mining; Intent learning, opinion mining and sentimentanalysis; Pattern/rule and exception analytics, learningand mining; Network and networking representationanalytics, learning and mining; Community and hidden group analytics,learning and mining; Complex relation learning and presentation; Complex structure learning and presentation; Economic and financial data analytics, learningand mining; Environmental, organisational and social dataanalytics, learning and mining; Models, methods learning and presentation; Impact, profitability, utility and reliabilitymodelling and learning; Social media mining and social networkanalysis Customer analytics Web analytics Recommendation algorithms andrecommender systems; Optimisation; and Actionable knowledge discovery, tools andsystem delivery.AAi has been widely recognised for its smartsolutions, working systems and capabilitiesin combining theoretical breakthroughs withreal-world, large scale and complex data andenterprise innovation. AAi’s work has includedbusiness and social analytics from major business,government and social domains, including banking,capital markets, education, finance, healthcare,immigration, insurance, marketing, medicalbusiness, online business, payment business, publicsector, risk management, retail and shopping, socialnetworks, social media, social welfare and socialsecurity, taxation and telecommunication.

Fundamental Issues in Data and Analytics SciencesProgram Leader: UTS Distinguished Professor Louise RyanMobile, status updates, blog posts, geo-locations,social networks, video, genomics and sensor dataconstitute new information sources generating bigdata. The volume, variety, velocity, veracity, value,and depth, coupling relationship, multi-source andmulti-layered nature of big data arising from suchdiverse sources can sometimes be quite daunting.Gaining new insights from massive repositories ofbig data is challenging the existing paradigms andmethods of statistics, data engineering, analyticsscience, information science, and intelligencesciences.Big data presents new challenges to the testing ofexisting theories on an immensely large scale andof extreme complexity, as well as demanding theexploration of entirely new theories, approachesand tools for data acquisition, representation andmodelling, processing, learning, analytics, mining,presentation and management. Furthermore,possibilities exist to blend disparate sources of dataand to develop new theories. --ransformation and manipulation--Discretisation and fuzzification--Coding and decoding--Quality and assurance--Characteristics and distribution--Dynamics and evolution--Access, indexing, query, search andmanagement--Visualisation and presentation--Type and structure-specific analysisAdvanced analytics--Variable and value analysis--Feature selection, construction and mining--Domain-specific data analysis--Similarity and dissimilarity--Independency and couplings (dependency)--Relation learning and reasoning--Heterogeneity learningPushing well beyond statistical techniques and usingan implicit ‘no hypothesis’ approach, AAi researchersare exploring big data using statistics, informationprocessing, visualisation, data mining and analytics,and machine learning innovations. These cuttingedge explorations are in turn unlocking valuewhich has hitherto been deeply hidden within richcouplings, multi-structured data sets, and complexenvironments.--Invisibility learning--Intent learning and sentiment analysis--non-IIDness learning--Methodologies and processes--Structure learning and modelling--Behaviour informatics--Change and dynamics analysis--Social informaticsThe opportunity that big complex data presents totransform industry is driving the emergence of datascience and analytics science. AAi researchers areworking to ensure that we remain at the forefront ofthese new and exciting fields of scientific endeavour.--Semantic analysis--Document analysisCurrently, AAi researchers are working on frontiertechnologies and approaches in: Data engineering--Acquisition and generation--Representation and modelling Management and governance--Algorithms, methods and models--Patterns and outliers--Privacy, security and trust--Simulations and experiments--Evaluation and measurement--Governance of very large data sets17

Multimedia and New Media AnalyticsProgram Leader: Associate Professor Jian ZhangSpecialist multimedia and new media analyticsexperts at AAi are working on developing fast andeffective media information search tools with thecapacity to retrieve and share data across theInternet.Researchers are using their expertise in multimediasignal processing, computer vision, patternrecognition and data mining to develop innovativetheories and algorithms for a new search engine. AAiis undertaking multimedia and new media analysisresearch in the areas of: 18AAi Blackfriars CampusMultimedia--Combined multimedia and social mediasearch and retrieval on the Internet--Multimedia understanding and eventdetection in large scale datasetsComputer Vision--Object (e.g., human, vehicle, boat) detectionbased on multiple features and multiplemodels--Large scale 3D content processing forobject matching and retrieval--RGB-D sensing, scene reconstruction andscene understanding--Video surveillance for public security andsafety--Human gait recognition through view angletransformation--Human action detection and retrieval in keyframesSocial Media--Social media content analytics andrecommendation--User behaviour analytics in social medianetwork--Intrusion prevention and privacy protectionin social media network

MyEducation for student sentiment managementSmarter Livi

The Advanced Analytics Institute (AAi) was formally established in March 2011 as a university research institute. In 2011-2013, the AAi team has experienced many very demanding but . International affiliations and collaborations with academic, industrial and professional partners in informatics, big data, data science and analytics