August 2019 - sem-grd - lists.ogf.org

IEEE BigData 2019 Call for Workshop Papers and Posters
by CFP Conference 28 Aug '19

28 Aug '19

*IEEE Big Data 2019 Call for Workshop Papers & Posters* 2019 IEEE International Conference on Big Data (BigData 2019) http://bigdataieee.org/BigData2019/ Dec 9-12, 2019, Los Angeles, CA, USA The IEEE Big Data 2019 has received more than 600 full papers in the main conference and industry and government program. If you miss the submission deadline, there are still chances for you to submit your research work to the IEEE Big Data 2019 workshops and Posters. The workshop papers and posters are published in the conference proceedings. (EI indexed) (1) * 44 Workshops (*Most of the workshop paper submission deadlines are early or middle October) *1.* Computational Archival Science: digital records in the age of big data <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S01…> *2.* International Workshop on Big Data Analytics for Cyber Threat Hunting (CyberHunt 2019) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S02…> *3.* The 2nd International Workshop on “Big Data Engineering and Analytics in Cyber-Physical Systems (BigEACPS) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S03…> *4.* 6th Workshop on Performance Engineering with Advances in Software and Hardware for Big Data Science (PEASH) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S04…> *5.* 5th International Workshop on Methodologies to Improve Managing Big Data projects <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S05…> *6.* 4th Workshop on Real-time and Stream Analytics in Big Data & Stream Data Management <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S06…> *7.* Applications of Big Data Technology in the Transport Industry <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S07…> *8.* The 3rd Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S08…> *9.* Advances in High Dimensional (AdHD) Big Data (AdHD Big Data) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S09…> *10.* BITS 2019: International Workshop on Big data for Intelligent Transportation Systems <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S10…> *11.* 8th Workshop on Scalable Cloud Data Management <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S11…> *12.* 5th IEEE Workshop on Big Data Analytics in Supply Chains and Transportation <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S12…> *13.* Analysis of Large-scale Disparate Data <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S13…> *14.* 3rd IEEE Big Data International Workshop on Policy-based Autonomic Data Governance (PADG) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S14…> *15.* The 4th IEEE International Workshop on Big Spatial Data (BSD 2019) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S15…> *16.* The First International Workshop on Big Data Against Darknet Crimes <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S16…> *17.* Second International Workshop on the Internet of Things Data Analytics (IOTDA) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S17…> *18.* 7th International Workshop on Distributed Storage and Blockchain Technologies for Big Data <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S18…> *19.* The 3rd International Workshop on Big Data Analytic for Cybercrime Investigation and Prevention <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S19…> *20.* The Third Annual Workshop on Applications of Artificial Intelligence in the Legal Industry <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S20…> *21.* Big Data Predictive Maintenance using Artificial Intelligence <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S21…> *22.* The 2nd International Workshop on Big Data for Marketing Intelligence and Operation Management <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S22…> *23.* 2nd Workshop on Energy-Efficient Machine Learning and Big Data Analytics <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S23…> *24.* The First International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S24…> *25.* The Third Human-in-the-loop Methods and Human-Machine Collaboration in BigData <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S25…> *26.* 4th Workshop on Open Science in Big Data (OSBD) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S26…> *27.* 3rd International Workshop on Big Data Analytics for Cyber Intelligence and Defense (BDA4CID 2018) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S27…> *28.* Sixth International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs 2019) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S28…> *29.* Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S29…> *30.* The 3rd Workshop on Graph Techniques for Adversarial Activity Analytics (GTA3 3.0) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S30…> *31.* 5th Solar & Stellar Astronomy Big Data (SABiD) – Workshop on Management, Search and Mining of Massive Repositories of Solar and Stellar Astronomy Data <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S31…> *32.* 2nd Workshop on Big Data for CyberSecurity (BigCyber-2019) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S32…> *33.* The 2nd International Workshop on Big Media Dataset Construction, Management and Applications <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S33…> *34.* Big Food and Nutrition Data Management and Analysis (BFNDMA 2019) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S34…> *35.* IoT Big Data 2019 <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S35…> *36.* The Third Workshop on Big Data for Economic and Business Forecasting <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S36…> *37.* Deep Graph Learning: Methodologies and Applications (DGLMA'19) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S37…> *38.* IEEE Workshop on Machine Learning for Big Data Analytics in Remote Sensing <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S38…> *39.* The First Workshop on Security and Privacy on Blockchain <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S39…> *40.* The 3rd International Workshop on Big Data for Financial News and Data <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S40…> *41.* 4th International Workshop on Big Data Transfer Learning (BDTL) -- Heterogeneous Representation and Networks <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S41…> *42.* The next frontier of big data from LIDAR <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S42…> *43.* Streaming Systems and Real-Time Machine Learning (STREAM-ML) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S43…> *44.* 6th International Workshop on Privacy and Security of Big Data (PSBD 2019) <https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=S44…> (2) *Po**ster *(Submission deadline: Nov 10) Poster abstracts are limited to one page, the format and style are flexible. Posters will be reviewed on the basis of their relevance to the scope of the conference and on the scientific quality of the work presented. Each poster paper will be published with maximum up to 3-page limit in the poster/workshop proceedings (EI indexed). (format instruction for publication will be included with the poster acceptance notification) Online Submission: https://wi-lab.com/cyberchair/2019/bigdata19/index.php To subscribe to this list, the user sends an email, with blank subject line, to listserv(a)lists.drexel.edu. In the text box, the user types: subscribe BIGDATA To unsubscribe from a list, the user sends an email to listserv(a)lists.drexel.edu with the message signoff BIGDATA ######################################################################## To unsubscribe from the BIGDATA list, click the following link: http://lists.drexel.edu/cgi-bin/wa?TICKET=NzM3MzI5IHNlbS1ncmRAT0dGLk9SRyBCS…

1 0

Tenure-track or tenured faculty positions in Autonomous Discovery Science, Computational Social Science, and AI and Ethics, Law, and Societal Issues (ELSI) at the Institute of Data Science, Maastricht University (NL)
by Info-ids (IDS) 21 Aug '19

21 Aug '19

We are thrilled to recruit *3* talented individuals to our highly interdisciplinary Institute of Data Science at Maastricht University. Open to all professor ranks, come join our rapidly growing team to pursue new research and training in wonderfully diverse and collaborative environment. The Institute of Data Science at Maastricht University invites applications for 3 tenure-track or tenured faculty positions in the areas of * autonomous discovery science; * computational social science; * AI ethics, law and societal issues. Deadline: 29 September 2019 For the full vacancy text and to apply, go to: https://www.academictransfer.com/en/284856/tenure-track-or-tenured-faculty-… Ambition: Despite vast and increasing amounts of data on the Web, our ability to find, obtain, understand, and use data by autonomous machine agents in a societal context remains highly limited owing to an interplay of scientific, technical, social, legal, and ethical factors. To address this challenge, the Institute of Data Science at Maastricht University seeks to bring together an outstanding team of collaborative researchers to join existing faculty and staff to pursue highly interdisciplinary applied research in this area. The team will develop externally funded research programs, interdisciplinary educational programming, and be active in broader outreach and community initiatives. Positions: Within the initiative, three positions have been created as either tenured or tenure track, focusing on three key research areas: Autonomous discovery science. The aim of the position is to undertake research and development towards an intelligent and autonomous systems to coordinate people and machines in a manner that furthers scientific knowledge. We welcome outstanding candidates with expertise in areas such as, but not limited to, autonomous systems, automated reasoning, collective intelligence, web-scale data mining, argumentation and other logics, explainable AI, deep learning, and life-long learning. Computational social science. The aim of the position is to develop computational methods to characterize, guide, and enhance digital interactions, particularly with machines. We welcome outstanding candidates with expertise in areas such as, but not limited to, computational social science, social media analysis, human-computer interaction, computational linguistics, and large-scale digital survey methodology. AI and Ethics, law and societal issues. The aim of this position is to contribute to our ELSI work and team, with a focus on how far AI developments fit with current governance approaches and requirements; how the presumptions about those approaches are challenged by the new developments; how different stakeholder groups and publics view AI developments in different settings, and how they view the governance of AI; what new governance structures might look like; how new governance structures resonate with different publics and regulators. We welcome outstanding candidates with expertise in areas such as, but not limited to, sociology, anthropology, socio-legal studies, cultural studies, anthropology, and public engagement. Tasks * Conduct cutting edge research in the foundation, applications, and/or governance of data science * Be involved in interdisciplinary research between the Institute of Data Science and other parts of the University * Develop and secure external funding to support research programme * Deliver educational programming at the undergraduate and graduate levels. * Establish and advocate for best practices in scientific reproducibility of all results, and to promote the responsible use of data. Requirements * A PhD in mathematics, computer science, data science, artificial intelligence, or equivalent; and sociology, anthropology, socio-legal studies, cultural studies, anthropology, public engagement or equivalent for the AI and ELSI position. * A record of outstanding research as evidenced by publications, grants, software developed, and other scholarly measures of impact * A record of successful research collaborations * Excellent written and oral presentation skills * Strong commitment to undergraduate and graduate teaching * Strong interpersonal, organizational, and communication skills * Strong analytical, computational, and quantitative abilities * Strong critical and qualitative ELSI skills for the AI and ELSI position. * English Fluency. For the full vacancy text and to apply, go to: https://www.academictransfer.com/en/284856/tenure-track-or-tenured-faculty-…

1 0

IEEE BigData 2019 Last CFP , deadline: Aug 19, 2019
by CFP Conference 18 Aug '19

18 Aug '19

*Call for Papers* *2019 IEEE International Conference on Big Data (IEEE BigData 2019)* http://bigdataieee.org/BigData2019/ December 10-13, 2019, Los Angeles, CA, USA In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data. · The first conference IEEE Big Data 2013 had more than 400 registered participants from 40 countries ( http://bigdataieee.org/BigData2013/) and the regular paper acceptance rate is 17.0%. · The IEEE Big Data 2017 ( http://bigdataieee.org/BigData2017/ , regular paper acceptance rate: 17.8%) was held in Boston, MA, Dec 11-14, 2017 with close to 1000 registered participants from 50 countries. · The IEEE Big Data 2018 ( http://bigdataieee.org/BigData2018/ , regular paper acceptance rate: 19.7%) was held in Seattle, WA, Dec 10-13, 2018 with close to 1100 registered participants from 47 countries. The 2019 IEEE International Conference on Big Data (IEEE BigData 2019) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications. We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. The conference adopts single-blind review policy. We expect to have a very high quality and exciting technical program at Seattle this year. *Example topics of interest includes but is not limited to the following*: 1. Big Data Science and Foundations a. Novel Theoretical Models for Big Data b. New Computational Models for Big Data c. Data and Information Quality for Big Data d. New Data Standards 2. Big Data Infrastructure a. Cloud/Grid/Stream Computing for Big Data b. High Performance/Parallel Computing Platforms for Big Data c. Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment d. Energy-efficient Computing for Big Data e. Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data f. Software Techniques and Architectures in Cloud/Grid/Stream Computing g. Big Data Open Platforms h. New Programming Models for Big Data beyond Hadoop/MapReduce, STORM i. Software Systems to Support Big Data Computing 3. Big Data Management a. Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data b. Algorithms and Systems for Big DataSearch c. Distributed, and Peer-to-peer Search d. Big Data Search Architectures, Scalability and Efficiency e. Data Acquisition, Integration, Cleaning, and Best Practices f. Visualization Analytics for Big Data g. Computational Modeling and Data Integration h. Large-scale Recommendation Systems and Social Media Systems i. Cloud/Grid/Stream Data Mining- Big Velocity Data j. Link and Graph Mining k. Semantic-based Data Mining and Data Pre-processing l. Mobility and Big Data m. Multimedia and Multi-structured Data- Big Variety Data 4. Big Data Search and Mining a. Social Web Search and Mining b. Web Search c. Algorithms and Systems for Big Data Search d. Distributed, and Peer-to-peer Search e. Big Data Search Architectures, Scalability and Efficiency f. Data Acquisition, Integration, Cleaning, and Best Practices g. Visualization Analytics for Big Data h. Computational Modeling and Data Integration i. Large-scale Recommendation Systems and Social Media Systems j. Cloud/Grid/StreamData Mining- Big Velocity Data k. Link and Graph Mining l. Semantic-based Data Mining and Data Pre-processing m. Mobility and Big Data n. Multimedia and Multi-structured Data- Big Variety Data 5. Ethics, Privacy and Trust in Big Data Systems a. Techniques and models for fairness and diversity b. Experimental studies of fairness, diversity, accountability, and transparency c. Techniques and models for transparency and interpretability d. Trade-offs between transparency and privacy e. Intrusion Detection for Gigabit Networks f. Anomaly and APT Detection in Very Large Scale Systems g. High Performance Cryptography h. Visualizing Large Scale Security Data i. Threat Detection using Big Data Analytics j. Privacy Preserving Big Data Collection/Analytics k. HCI Challenges for Big Data Security & Privacy l. Trust management in IoT and other Big Data Systems 6. Hardware/OS Acceleration for Big Data a. FPGA/CGRA/GPU accelerators for Big Data applications b. Operating system support and runtimes for hardware accelerators c. Programming models and platforms for accelerators d. Domain-specific and heterogeneous architectures e. Novel system organizations and designs f. Computation in memory/storage/network g. Persistent, non-volatile and emerging memory for Big Data h. Operating system support for high-performance network architectures 7. Big Data Applications a. Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication b. Big Data Analytics in Small Business Enterprises (SMEs), c. Big Data Analytics in Government, Public Sector and Society in General d. Real-life Case Studies of Value Creation through Big Data Analytics e. Big Data as a Service f. Big Data Industry Standards g. Experiences with Big Data Project Deployments *INDUSTRIAL Track* The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages). *Student Travel Award* IEEE Big Data 2019 will offer*student travel *to student authors (including post-docs) *Paper Submission:* Please submit a full-length paper (up to *10 page IEEE 2-column format*) through the online submission system. https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=BigD Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to "formatting instructions" below). *Formatting Instructions* 8.5" x 11" (DOC <ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc>, PDF <ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf>) *LaTex Formatting Macros* <ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.…> *Important Dates:* Electronic submission of full papers: August 19, 2019 Notification of paper acceptance: Oct 16, 2019 Camera-ready of accepted papers: Nov 10, 2019 Conference: Dec 9-12, 2019 *Conference Co-Chairs:* Dr. Roger Barga, Amazon.com, USA Prof Carlo Zaniolo, UCLA, USA *Program Co-Chairs:* Dr. Chaitanya Baru, San Diego Supercomputer Center/UC San Diego, USA Dr, Jun (Luke) Huan, Baidu Big Data Lab, China Prof. Latifur Khan, University of Texas at Dallas, USA *Vice Chairs in Big Data Science and Foundations* Prof. Jingrui He, UIUC, USA Prof. Wenqing Hu, Missouri S&T University, USA *Vice Chairs in Big Data Infrastructure* Prof. Hanghang Tong, UIUC, USA Dr. Yinglong Xia, Huawei, USA *Vice Chairs in Big Data Management* Prof. Christopher Jermaine, Rice University, USA Prof. Zhou Yongluan, Univ. of Copenhagen, Denmark *Vice Chairs in Big Data Search and Mining* Prof. Quanquan Gu, UCLA, USA Prof. Aditya Prakash, Virginia Tech, USA *Vice Chairs in Big Data Security, Privacy and Trust* Prof. Dongwon Lee, Penn State University, USA Prof. Julia Stoyanovich, New York University, USA *Vice Chairs in Hardware/OS Accelerating for Big Data* Prof. Sang-Woo Jun, UC Irvine, USA Prof. Harry Xu, UCLA, USA *Vice Chairs in Big Data Applications* Prof. Xia Ning, Ohio State University, USA Prof. Tim Weninger, Univ. of Notre Dame, USA *Industry and Government Program Committee Co-Chairs* Dr. Ronay Ak, NVIDIA, USA Dr. Yuanyuan Tian, IBM Almaden Research Center, USA, To subscribe to this list, the user sends an email, with blank subject line, to listserv(a)lists.drexel.edu. In the text box, the user types: subscribe BIGDATA To unsubscribe from a list, the user sends an email to listserv(a)lists.drexel.edu with the message signoff BIGDATA ######################################################################## To unsubscribe from the BIGDATA list, click the following link: http://lists.drexel.edu/cgi-bin/wa?TICKET=NzM3MzE5IHNlbS1ncmRAT0dGLk9SRyBCS…

1 0

IEEE BigData 2019 CFP: Aug 19, 2019 (6 days left)
by CFP Conference 13 Aug '19

13 Aug '19

*Call for Papers* *2019 IEEE International Conference on Big Data (IEEE BigData 2019)* http://bigdataieee.org/BigData2019/ December 10-13, 2019, Los Angeles, CA, USA In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data. · The first conference IEEE Big Data 2013 had more than 400 registered participants from 40 countries (http://bigdataieee.org/BigData2013/, and the regular paper acceptance rate is 17.0%. · The IEEE Big Data 2017 ( http://bigdataieee.org/BigData2017/,regular paper acceptance rate: 17.8%) was held in Boston, MA, Dec 11-14, 2017 with close to 1000 registered participants from 50 countries. · The IEEE Big Data 2018 ( http://bigdataieee.org/BigData2018/,regular paper acceptance rate: 19.7%) was held in Seattle, WA, Dec 10-13, 2018 with close to 1100 registered participants from 47 countries. The 2019 IEEE International Conference on Big Data (IEEE BigData 2019) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications. We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. The conference adopts single-blind review policy. We expect to have a very high quality and exciting technical program at Seattle this year. *Example topics of interest includes but is not limited to the following*: 1. Big Data Science and Foundations a. Novel Theoretical Models for Big Data b. New Computational Models for Big Data c. Data and Information Quality for Big Data d. New Data Standards 2. Big Data Infrastructure a. Cloud/Grid/Stream Computing for Big Data b. High Performance/Parallel Computing Platforms for Big Data c. Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment d. Energy-efficient Computing for Big Data e. Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data f. Software Techniques and Architectures in Cloud/Grid/Stream Computing g. Big Data Open Platforms h. New Programming Models for Big Data beyond Hadoop/MapReduce, STORM i. Software Systems to Support Big Data Computing 3. Big Data Management a. Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data b. Algorithms and Systems for Big DataSearch c. Distributed, and Peer-to-peer Search d. Big Data Search Architectures, Scalability and Efficiency e. Data Acquisition, Integration, Cleaning, and Best Practices f. Visualization Analytics for Big Data g. Computational Modeling and Data Integration h. Large-scale Recommendation Systems and Social Media Systems i. Cloud/Grid/Stream Data Mining- Big Velocity Data j. Link and Graph Mining k. Semantic-based Data Mining and Data Pre-processing l. Mobility and Big Data m. Multimedia and Multi-structured Data- Big Variety Data 4. Big Data Search and Mining a. Social Web Search and Mining b. Web Search c. Algorithms and Systems for Big Data Search d. Distributed, and Peer-to-peer Search e. Big Data Search Architectures, Scalability and Efficiency f. Data Acquisition, Integration, Cleaning, and Best Practices g. Visualization Analytics for Big Data h. Computational Modeling and Data Integration i. Large-scale Recommendation Systems and Social Media Systems j. Cloud/Grid/StreamData Mining- Big Velocity Data k. Link and Graph Mining l. Semantic-based Data Mining and Data Pre-processing m. Mobility and Big Data n. Multimedia and Multi-structured Data- Big Variety Data 5. Ethics, Privacy and Trust in Big Data Systems a. Techniques and models for fairness and diversity b. Experimental studies of fairness, diversity, accountability, and transparency c. Techniques and models for transparency and interpretability d. Trade-offs between transparency and privacy e. Intrusion Detection for Gigabit Networks f. Anomaly and APT Detection in Very Large Scale Systems g. High Performance Cryptography h. Visualizing Large Scale Security Data i. Threat Detection using Big Data Analytics j. Privacy Preserving Big Data Collection/Analytics k. HCI Challenges for Big Data Security & Privacy l. Trust management in IoT and other Big Data Systems 6. Hardware/OS Acceleration for Big Data a. FPGA/CGRA/GPU accelerators for Big Data applications b. Operating system support and runtimes for hardware accelerators c. Programming models and platforms for accelerators d. Domain-specific and heterogeneous architectures e. Novel system organizations and designs f. Computation in memory/storage/network g. Persistent, non-volatile and emerging memory for Big Data h. Operating system support for high-performance network architectures 7. Big Data Applications a. Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication b. Big Data Analytics in Small Business Enterprises (SMEs), c. Big Data Analytics in Government, Public Sector and Society in General d. Real-life Case Studies of Value Creation through Big Data Analytics e. Big Data as a Service f. Big Data Industry Standards g. Experiences with Big Data Project Deployments *INDUSTRIAL Track* The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages). *Student Travel Award* IEEE Big Data 2019 will offer*student travel *to student authors (including post-docs) *Paper Submission:* Please submit a full-length paper (up to *10-page IEEE 2-column format*) through the online submission system. https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=BigD Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to "formatting instructions" below). *Formatting Instructions* 8.5" x 11" (DOC <ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc>, PDF <ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf>) *LaTex Formatting Macros* <ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.…> *Important Dates:* Electronic submission of full papers: August 19, 2019 Notification of paper acceptance: Oct 16, 2019 Camera-ready of accepted papers: Nov 10, 2019 Conference: Dec 9-12, 2019 *Conference Co-Chairs:* Dr. Roger Barga, Amazon.com, USA Prof Carlo Zaniolo, UCLA, USA *Program Co-Chairs:* Dr. Chaitanya Baru, San Diego Supercomputer Center/UC San Diego, USA Dr, Jun (Luke) Huan, Baidu Big Data Lab, China Prof. Latifur Khan, University of Texas at Dallas, USA *Vice Chairs in Big Data Science and Foundations* Prof. Jingrui He, UIUC, USA Prof. Wenqing Hu, Missouri S&T University, USA *Vice Chairs in Big Data Infrastructure* Prof. Hanghang Tong, UIUC, USA Dr. Yinglong Xia, Huawei, USA *Vice Chairs in Big Data Management* Prof. Christopher Jermaine, Rice University, USA Prof. Zhou Yongluan, Univ. of Copenhagen, Denmark *Vice Chairs in Big Data Search and Mining* Prof. Quanquan Gu, UCLA, USA Prof. Aditya Prakash, Virginia Tech, USA *Vice Chairs in Big Data Security, Privacy and Trust* Prof. Dongwon Lee, Penn State University, USA Prof. Julia Stoyanovich, New York University, USA *Vice Chairs in Hardware/OS Accelerating for Big Data* Prof. Sang-Woo Jun, UC Irvine, USA Prof. Harry Xu, UCLA, USA *Vice Chairs in Big Data Applications* Prof. Xia Ning, Ohio State University, USA Prof. Tim Weninger, Univ. of Notre Dame, USA *Industry and Government Program Committee Co-Chairs* Dr. Ronay Ak, NVIDIA, USA Dr. Yuanyuan Tian, IBM Almaden Research Center, USA, To subscribe to this list, the user sends an email, with blank subject line, to listserv(a)lists.drexel.edu. In the text box, the user types: subscribe BIGDATA To unsubscribe from a list, the user sends an email to listserv(a)lists.drexel.edu with the message signoff BIGDATA ######################################################################## To unsubscribe from the BIGDATA list, click the following link: http://lists.drexel.edu/cgi-bin/wa?TICKET=NzM3MzE0IHNlbS1ncmRAT0dGLk9SRyBCS…

1 0

IEEE BigData 2019 paper submission deadline: Aug 19, 2019
by CFP Conference 08 Aug '19

08 Aug '19

*Call for Papers* *2019 IEEE International Conference on Big Data (IEEE BigData 2019)* http://bigdataieee.org/BigData2019/ December 10-13, 2019, Los Angeles, CA, USA In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data. · The first conference IEEE Big Data 2013 had more than 400 registered participants from 40 countries (http://bigdataieee.org/BigData2013/, and the regular paper acceptance rate is 17.0%. · The IEEE Big Data 2017 (http://bigdataieee.org/BigData2017/,regular paper acceptance rate: 17.8%) was held in Boston, MA, Dec 11-14, 2017 with close to 1000 registered participants from 50 countries. · The IEEE Big Data 2018 (http://bigdataieee.org/BigData2018/,regular paper acceptance rate: 19.7%) was held in Seattle, WA, Dec 10-13, 2018 with close to 1100 registered participants from 47 countries. The 2019 IEEE International Conference on Big Data (IEEE BigData 2019) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications. We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. The conference adopts single-blind review policy. We expect to have a very high quality and exciting technical program at Seattle this year. *Example topics of interest includes but is not limited to the following*: 1. Big Data Science and Foundations a. Novel Theoretical Models for Big Data b. New Computational Models for Big Data c. Data and Information Quality for Big Data d. New Data Standards 2. Big Data Infrastructure a. Cloud/Grid/Stream Computing for Big Data b. High Performance/Parallel Computing Platforms for Big Data c. Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment d. Energy-efficient Computing for Big Data e. Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data f. Software Techniques and Architectures in Cloud/Grid/Stream Computing g. Big Data Open Platforms h. New Programming Models for Big Data beyond Hadoop/MapReduce, STORM i. Software Systems to Support Big Data Computing 3. Big Data Management a. Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data b. Algorithms and Systems for Big DataSearch c. Distributed, and Peer-to-peer Search d. Big Data Search Architectures, Scalability and Efficiency e. Data Acquisition, Integration, Cleaning, and Best Practices f. Visualization Analytics for Big Data g. Computational Modeling and Data Integration h. Large-scale Recommendation Systems and Social Media Systems i. Cloud/Grid/Stream Data Mining- Big Velocity Data j. Link and Graph Mining k. Semantic-based Data Mining and Data Pre-processing l. Mobility and Big Data m. Multimedia and Multi-structured Data- Big Variety Data 4. Big Data Search and Mining a. Social Web Search and Mining b. Web Search c. Algorithms and Systems for Big Data Search d. Distributed, and Peer-to-peer Search e. Big Data Search Architectures, Scalability and Efficiency f. Data Acquisition, Integration, Cleaning, and Best Practices g. Visualization Analytics for Big Data h. Computational Modeling and Data Integration i. Large-scale Recommendation Systems and Social Media Systems j. Cloud/Grid/Stream Data Mining- Big Velocity Data k. Link and Graph Mining l. Semantic-based Data Mining and Data Pre-processing m. Mobility and Big Data n. Multimedia and Multi-structured Data- Big Variety Data 5. Ethics, Privacy and Trust in Big Data Systems a. Techniques and models for fairness and diversity b. Experimental studies of fairness, diversity, accountability, and transparency c. Techniques and models for transparency and interpretability d. Trade-offs between transparency and privacy e. Intrusion Detection for Gigabit Networks f. Anomaly and APT Detection in Very Large-Scale Systems g. High Performance Cryptography h. Visualizing Large Scale Security Data i. Threat Detection using Big Data Analytics j. Privacy Preserving Big Data Collection/Analytics k. HCI Challenges for Big Data Security & Privacy l. Trust management in IoT and other Big Data Systems 6. Hardware/OS Acceleration for Big Data a. FPGA/CGRA/GPU accelerators for Big Data applications b. Operating system support and runtimes for hardware accelerators c. Programming models and platforms for accelerators d. Domain-specific and heterogeneous architectures e. Novel system organizations and designs f. Computation in memory/storage/network g. Persistent, non-volatile and emerging memory for Big Data h. Operating system support for high-performance network architectures 7. Big Data Applications a. Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication b. Big Data Analytics in Small Business Enterprises (SMEs), c. Big Data Analytics in Government, Public Sector and Society in General d. Real-life Case Studies of Value Creation through Big Data Analytics e. Big Data as a Service f. Big Data Industry Standards g. Experiences with Big Data Project Deployments *INDUSTRIAL Track* The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages). *Student Travel Award* IEEE Big Data 2019 will offer*student travel *to student authors (including post-docs) *Paper Submission:* Please submit a full-length paper (up to *10-page IEEE 2-column format*) through the online submission system. https://wi-lab.com/cyberchair/2019/bigdata19/scripts/submit.php?subarea=BigD Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to "formatting instructions" below). *Formatting Instructions* 8.5" x 11" (DOC <ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc>, PDF <ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf>) *LaTex Formatting Macros* <ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.…> *Important Dates:* Electronic submission of full papers: August 19, 2019 Notification of paper acceptance: Oct 16, 2019 Camera-ready of accepted papers: Nov 10, 2019 Conference: Dec 9-12, 2019 *Conference Co-Chairs:* Dr. Roger Barga, Amazon.com, USA Prof Carlo Zaniolo, UCLA, USA *Program Co-Chairs:* Dr. Chaitanya Baru, San Diego Supercomputer Center/UC San Diego, USA Dr, Jun (Luke) Huan, Baidu Big Data Lab, China Prof. Latifur Khan, University of Texas at Dallas, USA *Vice Chairs in Big Data Science and Foundations* Prof. Jingrui He, UIUC, USA Prof. Wenqing Hu, Missouri S&T University, USA *Vice Chairs in Big Data Infrastructure* Prof. Hanghang Tong, UIUC, USA Dr. Yinglong Xia, Huawei, USA *Vice Chairs in Big Data Management* Prof. Christopher Jermaine, Rice University, USA Prof. Zhou Yongluan, Univ. of Copenhagen, Denmark *Vice Chairs in Big Data Search and Mining* Prof. Quanquan Gu, UCLA, USA Prof. Aditya Prakash, Virginia Tech, USA *Vice Chairs in Big Data Security, Privacy and Trust* Prof. Dongwon Lee, Penn State University, USA Prof. Julia Stoyanovich, New York University, USA *Vice Chairs in Hardware/OS Accelerating for Big Data* Prof. Sang-Woo Jun, UC Irvine, USA Prof. Harry Xu, UCLA, USA *Vice Chairs in Big Data Applications* Prof. Xia Ning, Ohio State University, USA Prof. Tim Weninger, Univ. of Notre Dame, USA *Industry and Government Program Committee Co-Chairs* Dr. Ronay Ak, NVIDIA, USA Dr. Yuanyuan Tian, IBM Almaden Research Center, USA, To subscribe to this list, the user sends an email, with blank subject line, to listserv(a)lists.drexel.edu. In the text box, the user types: subscribe BIGDATA To unsubscribe from a list, the user sends an email to listserv(a)lists.drexel.edu with the message signoff BIGDATA ######################################################################## To unsubscribe from the BIGDATA list, click the following link: http://lists.drexel.edu/cgi-bin/wa?TICKET=NzM3MzA5IHNlbS1ncmRAT0dGLk9SRyBCS…

1 0