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DSAA 2019 : The 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2019) | |||||||||||||||
Link: http://dsaa2019.dsaa.co/ | |||||||||||||||
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Call For Papers | |||||||||||||||
2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2019)
5-8 October 2019, Washington, DC, USA DSAA'2019 website: dsaa2019.dsaa.co DSAA'2019 submission website: https://easychair.org/conferences/?conf=dsaa2019 -------------------------------- Tentative Program Highlights: -------------------------------- * 3 high profile keynote speakers that bridge statistics and computer science with other fields * A Data Science for Social Impact day * Research track and Applications track * Late-breaking Poster session with lightening talks highlighting recent research advances * Special sessions with papers published in the main conference IEEE proceedings for EI indexing through INSPEC by IEEE. * Special sessions on statistics/mathematics for data science and advanced analytics, industry data science, and emerging areas, recent trends and controversies of data science and advanced analytics. * Best papers selected for journal extension. * A strong interdisciplinary research program spanning the areas of data science, machine learning, data mining, and statistics, etc. * Strong cross-domain culture and industry & government engagement. * Industry and research exhibition opportunities. * Both traditional and hands-on tutorials. * Double blind, and 10 pages in IEEE 2-column format. * The conference is jointly sponsored and supported by IEEE CIS, ACM SIGKDD and ASA. -------------------------------- Available Calls: -------------------------------- * Call for Papers (research track and applications track): DSAA has maintained a very competitive acceptance rate for the main conference papers. * Call for Late-breaking Posters: Posters for lightning talks highlighting recent research advances. * Call for Tutorials: Both hands-on and technical tutorials are welcome. Each tutorial receives one free registration. * Call for Sponsors: There are different levels of sponsorship at DSAA. Contact sponsorship chairs for more information. * Call for Next Generation Data Scientist (NGDS) Awards: The prestigious NGDS Award is the only one in data science community, USD$1,000 for each award. -------------------------------- Important Dates: -------------------------------- 16 April 2019: Special session proposals submission 19 April 2019: Special session notification 22 May 2019: Tutorial proposals submission 24 May 2019: Tutorial notification 20 May 2019: Paper submission 25 July 2019: Paper acceptance notification 2 August 2019: Late-breaking poster submission 8 August 2019: Final Camera-ready papers due 14 August 2019: Notification of poster acceptance 15 August 2019: Early registration deadline 21 August 2019: Final camera-ready poster due 5-8 October 2019: DSAA'2019 conference dates ----------------------------------------------- Research Track This track solicits the latest, original and significant contributions related to foundations and theoretical developments of Data Science and Advanced Analytics. Topics of interest include but are not limited to: Foundations: Models and algorithms; asymptotic analysis; model evaluation, selection and model averaging; dimensionality reduction; strategies for handling missing data; relational/structured learning; matrix and tensor methods; deep learning; time series, spatial, or grouped data; feature/covariate selection and regularization; nonparametric Bayesian methods; computational methods for Bayesian inference; manifold learning, classification, clustering, regression; semi-supervised and unsupervised learning; personalization, security, privacy; visualization; optimization, inference and regularization; social network analysis. Infrastructure: Large-scale databases; cloud computing; big-data engineering and processing; large-scale processing and distributed/parallel computing; human-machine interaction; storage, search, and retrieval. Social Issues: Reproducibility and replicability; model explainability and provenance; data quality and model quality; bias and unintended consequences of algorithms and results; p-hacking and data dredging; publication bias and pre-analysis plans; trust, risk, and informed consent; data integrity and data ethics; matching, record linkage, and sharing; de-identification and re-identification; generalizability of results; causal inference. -------------------------------- Applications Track This track solicits high-quality, original papers describing applications of Data Science and Advanced Analytics across various disciplines and domains, including business, government, health and medical science, physical sciences, and social sciences. The focus is on papers that would be of interest to practitioners of Data Science and Advanced Analytics, or would highlight new challenges for researchers driven by the specific needs and characteristics of application areas. Topics of interest include but are not limited to: Case Studies describing work on a real-world problem using Data Science and Advanced Analytics that highlight important application domain-specific discoveries, lessons learned and/or challenges encountered from deploying real-world systems containing Data Science and Advanced Analytics approaches, data science and analysis-related ethical issues and solution approaches related to real-world applications. Infrastructure, Platforms, and Tools that were built to operationalize Data Science and Advanced Analytics, including the development and deployment of new hardware and software infrastructure and its associated challenges; the development, deployment, and use of reusable libraries and software implementations; and tools that are in production and are used by end-users either in a stand-alone capacity or as part of a business process. Submissions for both the research and applications tracks should very clearly specify the problem being solved, what methodologies were used to solve the problem, what data was used, how the results were evaluated, and how the solution is being used (ideally in production). Applying new data science methods to public data or data downloaded from competition sites (such as kaggle), without a real problem (and problem owner) will not be accepted in this track. ---------------------------------- Special Sessions Special sessions play a big role in promoting relevant focused areas that are not well covered in the main conference tracks, bringing together researchers, industry experts, practitioners and potential users who are interested in different aspects of data science and analytics. We have 6 special sessions that will be part of DSAA 2019: 1. EnGeoData’2019: Environmental and Geo-spatial Data Analytics 2. Machine Learning and Artificial Intelligence for Biomedical Health Data (MLAI4N) 3. Data and information quality: Toward Better Data Science 4. Beyond IID – Non-IID Learning 5. Data Science in Computational Psychiatry and Psychiatric Research 6. Flows of (Mis)Information Online Submission deadlines for special sessions are the same as for the main conference. -------------------------------- Location -------------------------------- DSAA’2019 will take place at the historic Omni Shoreham Hotel overlooking Rock Creek Park in Washington, DC. It has easy access to the Metro subway and airports in the DC area. -------------------------------- Papers Formatting -------------------------------- The paper length allowed is a maximum of ten (10) pages, in 2-column U.S. letter style using IEEE Conference template (see the IEEE Proceedings Author Guidelines: https://www.ieee.org/conferences/publishing/templates.html ). -------------------------------- What is IEEE DSAA? -------------------------------- The IEEE International Conference on Data Science and Advanced Analytics (DSAA) aims to be the flagship annual meeting spanning the interdisciplinary field of Data Science. DSAA focuses on the science of data science, as well as the implications of the science for applications to industry, government, and society. From the science side, DSAA spans all of the component fields of data science, including statistics, probabilistic and mathematical modeling, machine learning, data mining and knowledge discovery, complexity science, network science, business analytics, data management, infrastructure and storage, retrieval and search, security, privacy and ethics. From the applications side, DSAA aims both to show researchers important problems and issues that are revealed by real applications, and to show practitioners and users how the science can be applied to realize value. DSAA is intended to reflect the interdisciplinary nature of data science and analytics, as an alternative to the highly specialized disciplinary conferences. For the information about the DSAA conference series, participating and hosting DSAA etc.: www.dsaa.co |
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