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2016IEEE International ConferenceonBig DataDecember 5 - December 8, 2016 Washington DC, USA1

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2016 IEEE International Conference on Big DataIEEE Big Data 2016 Program Schedule . 4Conference Paper Presentations . 15Industry and Government Paper Presentations . 24Panels . 27Special Sessions . 33Manufacturing Symposium . 38Tutorials . 42Workshops . 45Posters . 63Hyatt Regency Washington on Capitol Hill Floor Plan. 67Conference WiFi Instruction. 68IEEE BigData 2017 CFP . . .693

IEEE Big Data 2016 Program ScheduleWashington DC, USADecember 5 - December 8, 2016Keynote Lecture: 60 minutes (about 45 minutes for talk and 15 minutes for Q and A)Main conference regular paper: 25 minutes (about 20 minutes for talk and 5 minutes for Q and A)Main conference short paper: 15 minutes (about 11 minutes for talk and 4 minutes for Q and A)All conference activities take place at the Hyatt Regency Washington on Capitol Hill.Sunday, 4-December3:00 – 8:00 pmLocation:RegistrationRegency FoyerMonday, 5-December7:20am-6:00pmLocation:10:00-10:20 amand3:30 – 3:50 pmLocation:2:00 – 6:00 pmLocation:TimeRegistrationRegency FoyerCoffee BreakRegency FoyerPoster Session (Set up only)Regency Foyer and Hall of BattlesSession/WorkshopsSession ChairW2, 2nd International workshop on Big Data forsustainable DevelopmentFull DayWorkshops8:00 – 6:30 pmLocationDr. Aki-Hiro SatoRegency AW3&W14, 3rd Workshop on Advances in Software andHardware for Big Data to Knowledge Discovery (ASH)and 4th International Workshop on Distributed StorageSystems and Coding for Big DataDr. Hui Zhang, Dr. Weijia Xu,Dr. Hongfeng Yu, Dr. Bing ZhuRegency BW9, The 1st IEEE International Workshop on Big SpatialData (BSD)Dr. Chengyang Zhang, Dr.Abdeltawab Hendawi, Dr.Farnoush Banaei-kashaniRegency CW15, IEEE Workshop on Big Data Metadata andManagement (BDMM 2016)Dr. Alex Kuo, Dr. YinglongXia, Dr. MahmoudDaneshmand, Dr. ChonggangWangRegency DW21, The 3rd Workshop on Pattern Mining andApplication of Big Data (BigPMA 2016)Dr. Yi-Cheng Chen, Dr. JiunLong HuangColumbia A4

Monday, 5-December - continuedTimeSessions/WorkshopsSession ChairLocationNam-Luc TRAN, SabriSKHIRI and ThomasPEELColumbia BW10, IEEE Workshop on Big Data and Machine Learningin Telecom (BMLIT)Dr. Jin Yang, Dr. HuiZang,Dr. Li LiuColumbia CW13, Big Data Challenges, Research, and Technologies inthe Earth and Planetary SciencesDr. Tom Narock, Dr. DanCrichtonCongressional CDr. Wilson RiveraConcordW19, 3rd International Workshop on High PerformanceBig Graph Data Management, Analysis, and Mining(BigGraphs 2016)Dr. Kamesh Madduri, Dr.Mohammad Al Hasan, Dr.Nesreen AhmedColumbia FoyerW20, 3rd Big Data Analytic Technology forBioinformatics and Health Informatics (KDDBHI)WorkshopDr.Donghui Wu, Dr. XinDeng, Ph.D.W27, Textual Customer Feedback Mining and TransferLearning WorkshopDr. Xin Deng, Dr. MingShao, Dr. Ross Smith, Dr.Yun FuW5, Real-time and Stream Analytics in Big DataWorkshopSessions8:00 – 12:00 pmW16, Workshop on Big Data in Smart Grids12:00 - 1:30 pmTimeTutorial1:30 – 6:00 pmCongressional BLunch (on own)Sessions/Workshops/TutorialsSession ChairLocationTutorial 1: Large Scale Text Mining – Techniques andApplications (1:30-3:30 pm)Prof. Ronen Feldman, Prof.Ron BekkermanColumbia BTutorial 5: Anomalous and Significant SubgraphDetection in Attributed Networks (4:00 -6:00 pm)Feng Chen, PetkoBogdanov, Daniel B. Neill,Ambuj K. SinghColumbia BDr. Ata TurkColumbia CW4 First Workshop on Open Science in Big Data (OSBD)Dr. Shannon QuinnConcordW7, Methods to Manage Heterogeneous Big Data andPolystore Databases WorkshopDr. Vijay GadepallyLexingtonW12, 2nd International workshop on Methodologies toImprove Big Data ProjectDr. Jeffrey SaltzBunker HillW1, Big Data for Cloud Operations Management:Problems, Approaches, Tools, and Best PracticesWorkshopSessions1:30 – 6:30 pmLexingtonW17, 3rd Solar & Stellar Astronomy Big Data (SABiD) Dr. Rafal A. Angryk, Dr. Congressional CWorkshop on Management, Search and Mining of Massive Piet C. Martens, Dr. RusselJ. WhiteRepositories of Solar and Stellar Astronomy DataW22, Advances in High Dimensional (AdHD) Big DataDr. Sotiris Tasoulis, Dr.Liang WangCongressional DW26, Ieee Workshop On Big Data Analytics InManufacturing And Supply ChainsDr. Zhang NengshengAllan, Ms. Mika KawaiColumbia FoyerDr. Paul RaysonCongressional BW28, Big Data and Natural Language Processing (BigNLP-2016) Workshop5

Tuesday, 6-December7:20-6:00 pmLocation:TimeRegistrationRegency Foyer B WallSessionsSession ChairLocation8:30-08:45Opening and WelcomeSudarsan Rachuri,Lyle Ungar,Philip S. Yu,James Joshi,Ling Liu,George Karypis8:45-09:45Keynote Session 1:Database Decay and How to Avoid ItDr. Michael Stonebraker, Paradigm4/MIT, USALing LiuRegency ABCD9:45-10:45Keynote Session 2:Leveraging High Performance Computing to DriveAdvanced Manufacturing R&D at the US Department ofEnergyDr. Mark Johnson, Director, Advanced ManufacturingOffice, U.S. Department of EnergySudarsan RachuriRegency ABCD8:30-10:45Special Session: Intelligent Data MiningDr. Uraz YavanogluConcordCoffee Break10:45 – 11:05amLocation:11:05 am -12:45pmRegency FoyerPoster Session (Set up only)Regency Foyer and Hall of BattlesSessionsSession ChairLocationL1 Cloud/Stream Computing for Big DataLatifur Khan, UT DallasRegency ABCL2 Link and Graph Mining IL3 Visual Analytics and MobilityL4 Big Data in HealthcareJohn A Miller, Universityof GeorgiaAthanasios V. Vasilakos,Lulea University ofTechnologyAki-Hiro Sato, KyotoUniversityColumbia AColumbia BRegency DI&G-Regular 1: Big Data AnalyticsShakti AwaghadColumbia FoyerManufacturing SymposiumDr. Sudarsan Rachuri, TinaLee, Dr. Ronay Ak, Dr.Anantha Narayanan,Dr. Soundar Srinivasan ,Dr. Rumi Ghosh , Dr.Steve EglashColumbia CSpecial Session: Intelligent Data MiningDr. Uraz YavanogluConcordDr. Akira Ishii,Dr. FujioToriumi, Dr. YasukoKawahataLunch (provided by conference)Regency ABCPoster Session Sets Up and DisplaysRegency Foyer and Hall of BattlesW6 Application of Big Data for computational socialscience12:45 – 2:00 pmLocation:Regency ABCD6Lexington

2:00 – 4:05 pmSessionsSession ChairLocationL5 High Performance Platforms for Big DataJohn A Miller, Universityof GeorgiaRegency ABCL6 Spatiotemporal and Stream Data ManagementJianwu Wang, UMBCColumbia AL7 Big Data Processing/MiningAthanasios V. Vasilakos,Lulea University ofTechnologyColumbia BL8 Big Data Applications IAki-Hiro Sato, KyotoUniversityRegency DI&G-Regular 2: Big Data Applications (1)Yinglong XiaColumbia FoyerManufacturing SymposiumDr. Sudarsan Rachuri, TinaLee, Dr. Ronay Ak, Dr.Anantha Narayanan,Dr. Soundar Srinivasan ,Dr. Rumi Ghosh , Dr.Steve EglashColumbia CSpecial Session: Intelligent Data MiningDr. Uraz YavanogluConcordDr. Akira Ishii,Dr. FujioToriumi, Dr. YasukoKawahataLexingtonW6 Application of Big Data for computational socialscience4:05 – 4:25 pmLocation:4:25 -6:25 pmCoffee BreakRegency FoyerPoster Session Sets Up and DisplaysRegency Foyer and Hall of BattlesSessionsSession ChairModerator: Ling Liu,Panel 1 (Moderator: Ling Liu)Georgia Institute ofTechnologyLocationRegency ABCS1 Visualization, Multimedia, & CrowdsourcingHaiying Shen, Universityof VirginiaColumbia AS2 Computational Models, and Social MediaRecommendationPanagiotis Liakos,University of AthensColumbia BS3 Energy-Efficiency and Data Quality/ProcessingYongluan Zhou.University of SouthernDenmarkRegency DDr. Michael E. SharpColumbia FoyerManufacturing SymposiumDr. Sudarsan Rachuri, TinaLee, Dr. Ronay Ak, Dr.Anantha Narayanan,Dr. Soundar Srinivasan ,Dr. Rumi Ghosh , Dr.Steve EglashColumbia CSpecial Session: Intelligent Data MiningDr. Uraz YavanogluConcordDr. Akira Ishii,Dr. FujioToriumi, Dr. YasukoKawahataLexingtonI&G –Short 1: Big Data Algorithms & SystemsW6 Application of Big Data for computational socialscience7

Wednesday, 7-December7:30-6:00 pmLocation:8:30 – 8:45RegistrationRegency Foyer B WallOpening remarks / AnnouncementsTimeSessionsSession ChairLocation8:45 -9:45 amKeynote Speech 3:Harnessing the Data Revolution: A Perspective from theNational Science FoundationDr. Chaitanya Baru, National Science FoundationLing LiuRegency ABCD9:45 -10:45 amKeynote Speech 4:On the Power of Big Data: Mining Structures fromMassive, Unstructured Text DataProf. Jiawei Han, Abel Bliss Professor, University ofIllinois at Urbana-Champaign, USAJames JoshiRegency ABCD8:00-10:45amW25, 3rd International Workshop on Privacy and Securityof Big Data (PSBD 2016)Dr. Alfredo CuzzocreaBunker Hill10:45 - 11:05amLocation:11:05- 12:45 pmCoffee BreakRegency FoyerPoster Session DisplaysRegency Foyer and Hall of BattlesSessionsSession ChairJun (Luke) Huan,L9 Link and Graph Mining IIUniversity of KansasWeijia Xu,L10 Social Networks/MediaUT AustinAki-Hiro Sato, KyotoL11 Big Data Applications IIUniversityL12 Stream Data Mining /Cloud - Big Velocity DataI&G-Regular 3: Big Data Platforms & FrameworksManufacturing Symposium12:45 - 2:00 pmLocation:Time2:00 – 4:05 pmLocationRegency ABCColumbia AColumbia BJianwu Wang, UMBCRegency DPavan KapanipathilColumbia FoyerDr. Sudarsan Rachuri, TinaLee, Dr. Ronay Ak, Dr.Anantha Narayanan,Dr. Soundar Srinivasan ,Dr. Rumi Ghosh , Dr. SteveEglashColumbia CW11 4th Workshop on Scalable Cloud Data ManagementMr. Felix GessertWorkshop (SCDM)W25, 3rd International Workshop on Privacy and SecurityDr. Alfredo Cuzzocreaof Big Data (PSBD 2016)Lunch (provided by Conference)Regency ABCPoster Session DisplaysRegency Foyer and Hall of BattlesSessionsSession ChairConcordBunker HillLocationL13 Big Data Analytics and Security/Privacy IZhiyuan Chen, UMBCRegency ABCL14 Architecture/Systems and Big Data AnalyticsWeijia Xu, UT AustinColumbia AL15 Data Management & ApplicationsL16 Algorithms and Systems for Big Data SearchI&G Panel Session (2:00pm 3:00pm)Big Data Regional Innovation Hubs: Accelerating the Big8Aki-Hiro Sato, KyotoUniversityAthanasios V. Vasilakos,Lulea University ofTechnologyDr. Lea ShanleyColumbia FoyerRegency DColumbia B

Data Innovation Ecosystem4:05 – 4:25 pmLocationTimeI&G-short2 (3:00pm 4:05pm) Massive Processing &ExperienceDr. William Z. BernsteinColumbia BManufacturing SymposiumDr. Sudarsan Rachuri, TinaLee, Dr. Ronay Ak, Dr.Anantha Narayanan,Dr. Soundar Srinivasan ,Dr. Rumi Ghosh , Dr. SteveEglashColumbia CW11 4th Workshop on Scalable Cloud Data ManagementMr. Felix GessertWorkshop (SCDM)W25, 3rd International Workshop on Privacy and SecurityDr. Alfredo Cuzzocreaof Big Data (PSBD 2016)Coffee BreakRegency FoyerPoster Session DisplaysRegency Foyer and Hall of BattlesSessionsSession ChairModerator:Panel 2 (Moderator: James Joshi)Eui-Hong (Sam) Han, TheWashington PostJun (Luke) Huan,S4 Link and Graph Mining IIIUniversity of KansasConcordBunker HillLocationColumbia BColumbia AS5 Big Data Analytics and Security/Privacy IIZhiyuan Chen, UMBCBunker HillS6 Algorithms and Systems for Big Data IIDirk Van den Poel, GhentUniversityRegency DI&G-regular4: Big Data Applications (2)Dr. Lijun QianColumbia FoyerManufacturing SymposiumDr. Sudarsan Rachuri, TinaLee, Dr. Ronay Ak, Dr.Anantha Narayanan,Dr. Soundar Srinivasan ,Dr. Rumi Ghosh , Dr. SteveEglashColumbia C4:25- 6:25 pm7:00 – 9:00 pmLocationW11 4th Workshop on Scalable Cloud Data ManagementMr. Felix GessertWorkshop (SCDM)Banquet (Ticket required)Regency ABC1. Best Paper Award, PC Co-chairs2. Best Application Paper Award9Concord

Thursday, 8-December07:30-6:00pmLocation:Time8:30 – 9:45 am8:45 - 09:45 am9:45 - 10:45 am8:00-10:45am10:45 - 11:05 amLocation:TimeRegistrationRegency Foyer B WallSessionSession ChairOpening Remarks / AnnouncementsKeynote Speech 5:Big Data Security and PrivacyProf. Elisa Bertino, Purdue University, USAKeynote Speech 6:Cognitive Computing: From breakthroughs in the lab toapplications on the fieldDr. Guruduth S. Banavar, Vice President and ChiefScience Officer, Cognitive Computing, IBMGranular Computing Special Session: Data Scienceand ComputingWhole dayworkshop8:30am - 6pm12:45- 2:00 pmTime2:00 – 4:303:30 –4:00 pmJames JoshiRegency ABCJames JoshiRegency ABCT.Y. LinColumbia FoyerCoffee BreakRegency FoyerPoster Session DisplaysRegency Foyer and Hall of BattlesSessions/Tutorial/WorkshopL17 Computational Models for BigData I11:05am –12:45pmLocationSession ChairSeung-Jong Jay Park,Louisiana State UniversityLocationRegency AL18 Computational Models for BigData IIPanagiotis Liakos,University of AthensRegency BS7 Theoretical Models for Big DataAlfredo CuzzocreaUniversity of TriesteRegency CS8 Software Systems/Platform for Big Data ComputingKyong Jin Shim,Singapore ManagementUniversityRegency DTutorial 2: Trajectory Data Mining (11am-1pm)Prof. Zhenhui (Jessie) Li,Fei Wu, Prof. Jiawei HanColumbia FoyerTutorial 3: Large Scale Matrix Factorization(11am-1pm)Fei Wang, Wei TanConcordTutorial 4: Dynamic Big Data Processing in the Web ofThings: Challenges, Opportunities and Success Stories(11am-1pm)Ljiljana Stojanovic, NenadStojanovicLexingtonW18, Computational Archival Science: digital records inthe age of big dataDr. Mark HedgesBunker HillLunch (provided by conference)Regency ABCPoster Session DisplaysRegency Foyer and Hall of BattlesSessions/WorkshopsSession ChairAthanasios N.S9 Cloud/High Performance/Parallel Computing and BigNikolakopoulos,DataUniversity of PatrasKyong Jin Shim,S10 Big Data Applications IIISingapore ManagementUniversityS11 Big Data Search and Mining in Social Media andPanagiotis Liakos,WebUniversity of AthensAlfredo CuzzocreaS12 Data Management & IntegrationUniversity of TriesteCoffee Breeak10LocationRegency ARegency BRegency CRegency D

Keynote LecturesKeynote 1: Database Decay and How to Avoid ItSpeaker:Dr. Michael Stonebraker, Paradigm4/MIT, USAAbstract:The traditional wisdom for designing database schemas is to use a design tool (typically based on a UML or ER model) toconstruct an initial data model for one's data. When one is satisfied with the result, the tool will automatically construct acollection of 3rd normal form relations for the model. Then applications are coded against this relational schema. When businesscircumstances change (as they do frequently) one should run the tool again to produce a new data model and a new resultingcollection of tables. The new schema is populated from the old schema, and the applications are altered to work on the newschema, using relational views whenever possible to ease the migration. In this way, the database remains in 3rd normal form,which represents a "good" schema, as defined by DBMS researchers. "In the wild", schemas often change once a quarter or moreoften, and the traditional wisdom is to repeat the above exercise for each alteration. In this paper we report that the traditionalwisdom appears to be rarely-to-never followed "in the wild" for large, multi-department applications. Instead DBAs appear toattempt to minimize application maintenance (and hence schema changes) instead of maximizing schema quality. This leads toschemas which quickly diverge from ER or UML models and actual database semantics tend to drift farther and farther from 3rdnormal form.We term this divergence of reality from 3rd normal form principles database decay. Obviously, this is a veryundesirable state of affairs. In this paper we explore the reasons for database decay and tactics to avoid it. These includedefensive schemas, defensive application programs and a different model for interacting with a databaseShort Bio:Dr. Stonebraker has been a pioneer of data base research and technology for more than forty years. Hewas the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES.These prototypes were developed at the University of California at Berkeley where Stonebraker was aProfessor of Computer Science for twenty five years. More recently at M.I.T. he was a co-architect ofthe Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, the H-Storetransaction processing engine, the SciDB array DBMS, and the Data Tamer data curation system.Presently he serves as Chief Technology Officer of Paradigm4 and Tamr, Inc.Professor Stonebraker wasawarded the ACM System Software Award in 1992 for his work on INGRES. Additionally, he wasawarded the first annual SIGMOD Innovation award in 1994, and was elected to the National Academyof Engineering in 1997. He was awarded the IEEE John Von Neumann award in 2005 and the 2014Turing Award, and is presently an Adjunct Professor of Computer Science at M.I.T, where he is codirector of the Intel Science and Technology Center focused on big data.Keynote 2: Leveraging High Performance Computing to Drive Advanced Manufacturing R&D at the US Departmentof EnergySpeaker:Dr. Mark Johnson, Director, Advanced Manufacturing Office, U.S. Department of EnergyAbstract:Manufacturing is a critical component of the U.S. economy, responsible for 12.5% of GDP, direct employment for over 12million people, and close to 75% of U.S. exports of goods. The U.S. manufacturing sector, while it produces 17% of the world'smanufacturing output, also represents a quarter of the country's energy consumption. On the R&D side, it is responsible for 70%of all private sector R&D performed (in 2010 and 2011) and nearly 60% of patent applications. A number of emergingtechnologies are driving shifts in traditional manufacturing, in particular the convergence of information and communicationtechnology with the materials and process technologies of manufacturing. Particularly for energy intensive and energy-dependent11

industries, harnessing IT to reduce energy usage while simultaneously making companies more competitive is essential to thefuture of U.S. manufacturing, competitiveness, and productivity.This talk will review the Advanced Manufacturing Offices work to leverage high performance computing, smart manufacturingapproaches for the U.S. clean energy manufacturing sector—through targeted R&D in modeling and simulation and partnershipswith industry, academia, technology incubators and other stakeholders.Short Bio:Mark Johnson, Ph.D. serves as the Director of the Advanced Manufacturing Office (AMO) in theOffice of Energy Efficiency and Renewable Energy (EERE). AMO is focused on creating a fertileinnovation environment for advanced manufacturing, enabling vigorous domestic development of newenergy-efficient manufacturing processes and materials technologies to reduce the energy intensity andlife-cycle energy consumption of manufactured products.Previously, Mark served as a Program Director in the Advanced Research Projects Agency–Energy(ARPA-E) where he had the longest tenure in that post—from ARPA-E's formation in 2010 to mid2013. At ARPA-E, Mark led initiatives to advance energy storage and critical materials, as well asprojects in small business, advanced semiconductor, novel wind architectures, superconductors andelectric machinesHe also served as the Industry and Innovation Program Director for the Future Renewable Electric Energy Delivery andManagement (FREEDM) Systems Center. This is a National Science Foundation Gen-111 Engineering Research Center targetingthe convergence of power electronics, energy storage, renewable resource integration and information technology for electricpower systems.Mark joins EERE on assignment from North Carolina State University, where he is an Associate Professor of Materials Scienceand Engineering. His research has focused on crystal growth and device fabrication of compound semiconductor materials withelectronic and photonic applications. Mark also taught in the Technology, Entrepreneurship and Commercialization programjointly between the NC State Colleges of Management and Engineering. In addition to his academic career, Mark is anentrepreneur and early stage leader in Quantum Epitaxial Designs (now International Quantum Epitaxy), EPI Systems (nowVeeco) and Nitronex (now GaAs Labs).Mark has a bachelor's degree from MIT and a Ph.D., from NC State, both in Materials Science and Engineering.Keynote 3: Harnessing the Data Revolution: A Perspective from the National Science FoundationSpeaker:Dr. Chaitanya Baru, NSF, USAAbstract:This talk will introduce NSF's vision for moving beyond initial, isolated approaches for data science research, services, andinfrastructure, towards a cohesive, federated, national-scale approach to harness the data revolution and transform US science,engineering, and education over the next decade and beyond.Short Bio:Chaitan Baru is Senior Advisor for Data Science in the Computer and Information Science andEngineering (CISE) Directorate at the National Science Foundation. He is there on assignment from theSan Diego Supercomputer, UC San Diego, where he is Associate Director for Data Initiatives. At NSF,he coordinates the cross-Foundation BIGDATA research program, advises the NSF Big Data Hubs andSpokes program, assists in strategic planning, and participates in interdisciplinary and inter-agency DataScience-related activities. He co-chairs the Big Data Inter-agency Working Group, and is co-author /NSTC/bigdatardstrategicplannitrd final-051916.pdf), released in May 2016 under the auspices of the Networking and InformationTechnology R&D (NITRD) group of the National Coordination Office, White House Office of Science12

and Technology Policy.Keynote 4: On the Power of Big Data: Mining Structures from Massive, Unstructured Text DataSpeaker:Prof. Jiawei Han, Abel Bliss Professor, University of Illinois at Urbana-Champaign, USAAbstract:The real-world big data are largely unstructured, interconnected, and in the form of natural language text. One of the grandchallenges is to turn such massive unstructured data into structured ones, and then to structured networks and actionableknowledge. We propose a data-intensive text mining approach that requires only distant supervision or minimal supervision butrelies on massive data. We show quality phrases can be mined from such massive text data, types can be extracted from massivetext data with distant supervision, and relationships among entities can be discovered by meta-path guided network embedding.Finally, we propose a D2N2K (i.e., data-to-network-to-knowledge) paradigm, that is, first turn data into relatively structuredinformation networks, and then mine such text-rich and structure-rich networks to generate useful knowledge. We show such aparadigm represents a promising direction at turning massive text data into structured networks and useful knowlege.Short Bio:Jiawei Han is Abel Bliss Professor in the Department of Computer Science, University of Illinois atUrbana-Champaign. He has been researching into data mining, information network analysis, databasesystems, and data warehousing, with over 700 journal and conference publications. He has chaired orserved on many program committees of international conferences, including PC co-chair for KDD,SDM, and ICDM conferences, and Americas Coordinator for VLDB conferences. He also served as thefounding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data and the Director ofInformation Network Academic Research Center supported by U.S. Army Research Lab, and is the coDirector of KnowEnG, an NIH funded Center of Excellence in Big Data Computing. He is a Fellow ofACM and Fellow of IEEE, and received 2004 ACM SIGKDD Innovations Award, 2005 IEEE ComputerSociety Technical Achievement Award, 2009 M. Wallace McDowell Award from IEEE ComputerSociety. His co-authored book "Data M ining: Concepts and Techniques" has been adopted as a textbook popularly worldwide.Keynote 5: Big Data Security and PrivacySpeaker:Prof. Elisa Bertino, Purdue University, USAAbstract:Technological advances and novel applications, such as sensors, cyber-physical systems, smart mobile devices, cloud systems,data analytics, and social networks, are making possible to capture, and to quickly process and analyze huge amounts of datafrom which to extract information critical for security-related tasks. In the area of cyber security, such tasks include userauthentication, access control, anomaly detection, user monitoring, and protection from insider threat. By analyzing andintegrating data collected on the Internet and Web one can identify connections and relationships among individuals that may inturn help with homeland protection. By collecting and mining data concerning user travels and disease outbreaks one can predictdisease spreading across geographical areas. And those are just a few examples; there are certainly many other domains wheredata technologies can play a major role in enhancing security. The use of data for security tasks is however raising major privacyconcerns. Collected data, even if anonymized by removing identifiers such as names or social security numbers, when linkedwith other data may lead to re-identify the individuals to which specific data items are related to. Also, as organizations, such asgovernmental agencies, often need to collaborate on security tasks, data sets are exchanged across different organizations,resulting in these data sets being available to many different parties. Apart from the use of data for analytics, security tasks suchas authentication and access control may require detailed information about users. An example is multi-factor authentication thatmay require, in addition to a password or a certificate, user biometrics. Recently proposed continuous authentication techniquesextend access control system. This information if misused or stolen can lead to privacy breaches.It would then seem that in orderto achieve security we must give up privacy. However this may not be necessarily the case. Recent advances in cryptography aremaking possible to work on encrypted data – for example for performing analytics on encrypted data. However much more needsto be done as the specific data privacy techniques to use heavily depend on the specific use of data and the security tasks at hand.13

Also current techniques are not still able to meet the efficiency requirement for use with big data sets. In this talk we will discussmethods and techniques to make this reconciliation possible and identify research directions.Short Bio:Elisa Bertino is professor of computer science at Purdue University, and serves as Research Director ofthe Center for Information and Research in Information Assurance and Security (CERIAS). She is alsoan adjunct professor of Computer Science & Info tech at RMIT. Prior to joining Purdue in 2004, shewas a professor and department head at the Department of Computer Science and Communication of theUniversity of Milan. She has been a visiting researcher at the IBM Research Laboratory (now Almaden)in San Jose, at the Microelectronics and Computer Technology Corporation, at Rutgers University, atTelcordia Technologies. Her recent research focuses on data security and privacy, digital identitymanagement, policy systems, and security for the Internet-of-Things. She is a Fellow of ACM and ofIEEE. She received the IEEE Computer Society 2002 Technical Achievement Award, the IEEEComputer Society 2005 Kanai Award, and the ACM SIGSAC 2014 Outstanding Contributions Award.She is currently serving as EiC of IEEE Transactions on Dependable and Secure Computing.Keynote 6: Cognitive Computing: From breakthroughs in the lab to applications on the fieldSpeaker:Dr. Guruduth S. Banavar, Vice President and Chief Science Officer, Cognitive Computing, IBMAbstract:In the last decade, the availability of massive amounts of new data, the development of new machine learning technologies, andthe availability of scalable computing infrastructure, have given rise to a new class of computing systems. These "CognitiveSystems" learn from data, reason from models, and interact naturally with us, to perform complex tasks better than either humansor machines can do by themselves. These tasks range from answering questions conversationally to extracting knowledge fordiscovering insights to evaluating options for difficult decisions. These cognitive systems are designed to create new partnershipsbetween people and machines to augment and scale human expertise in every industry, from healthcare to financial services toeducation. This talk will provide an overview of cognitive computing, the technology breakthroughs that are enabling this trend,and the practical applications of this technology that are transforming every industry.Short Bio:Dr. Guru Banavar is vice president and chief science officer for cognitive computing at IBM. He isresponsible for advancing the next generation of cognitive technologies and solutions with IBM's globalscientific ecosystem, including academia, government agencies and other partners. Most recently, he ledthe team responsible for creating new AI techn

W2, 2nd International workshop on Big Data for sustainable Development Dr. Aki-Hiro Sato Regency A W3&W14, 3rd Workshop on Advances in Software and Hardware for Big Data to Knowledge Discovery (ASH) and 4th International Workshop on Distributed Storage Systems and Coding for Big Data Dr