CALL  FOR  PAPERS
                  Publisher: SPRINGER NATURE
         July 26-29, 2021, Luxor (MGM), Las Vegas, USA

                          ICAI'21
   23rd International Conference on Artificial Intelligence
    https://www.american-cse.org/csce2021/conferences-ICAI

                         ICDATA'21
        17th International Conference on Data Science
   https://www.american-cse.org/csce2021/conferences-ICDATA

****************************************************************

PAPER SUBMISSION PORTAL:  https://american-cse.org/

This year's research congress will be a hybrid event that combines
a “live” in-person event with a “virtual” online component.

ICAI'21 SCOPE: TOPICS OF INTEREST INCLUDE, BUT NOT LIMITED TO:

   PROLOGUE: Artificial Intelligence (AI) is the science and engineering
   of making intelligent machines and systems. AI is an important multi-
   disciplinary field which is now an essential part of technology
   industry, providing the heavy lifting for many of the most challenging
   problems in computer science. Since Machine Learning has strong ties
   with AI, the conference also covers the field of Machine Learning. The
   list of topics below is by no means meant to be exhaustive.

   ARTIFICIAL INTELLIGENCE:
   – Brain models, Brain mapping, Cognitive science
   – Natural language processing
   – Fuzzy logic and soft computing
   – Expert systems
   – Decision support systems
   – Automated problem solving
   – Knowledge discovery
   – Knowledge representation
   – Knowledge acquisition
   – Knowledge-intensive problem solving techniques
   – Knowledge networks and management
   – Intelligent information systems
   – Intelligent web-based business
   – Intelligent agents
   – Intelligent networks
   – AI and evolutionary algorithms
   – Intelligent tutoring systems
   – Reasoning strategies
   – Distributed AI algorithms and techniques
   – Neural networks and variations, including: Deep Learning
   – Heuristic searching methods
   – Constraint-based reasoning and constraint programming
   – Intelligent information fusion
   – Learning and adaptive sensor fusion
   – Search and meta-heuristics
   – Multisensor data fusion using neural and fuzzy techniques
   – Integration of AI with other technologies
   – Social intelligence (markets and computational societies)
   – Social impact of AI
   – Emerging technologies
   – Applications (including: computer vision, signal processing,
     military, surveillance, robotics, medicine, pattern recognition,
     face recognition, finger print recognition, finance and
     marketing, stock market, education, emerging applications, …)

   MACHINE LEARNING; MODELS, TECHNOLOGIES & APPLICATIONS:
   – Statistical learning theory
   – Unsupervised and Supervised Learning
   – Multivariate analysis
   – Hierarchical learning models
   – Relational learning models
   – Bayesian methods
   – Meta learning
   – Stochastic optimization
   – Heuristic optimization techniques
   – Neural networks and variations (eg. Deep Learning)
   – Reinforcement learning
   – Multi-criteria reinforcement learning
   – General Learning models
   – Multiple hypothesis testing
   – Markov chain Monte Carlo (MCMC) methods
   – Non-parametric methods
   – Graphical models
   – Gaussian graphical models
   – Bayesian networks
   – Particle filter
   – Cross-Entropy method
   – Ant colony optimization
   – Time series prediction
   – Fuzzy logic and learning
   – Inductive learning and applications
   – Grammatical inference
   – Graph kernel and graph distance methods
   – Graph-based semi-supervised learning
   – Graph clustering
   – Graph learning based methods
   – Motif search
   – Aspects of knowledge structures
   – Computational Intelligence
   – Knowledge acquisition and discovery techniques
   – General Structure-based approaches in information retrieval,
     web authoring, information extraction, and web content mining
   – Latent semantic analysis
   – Aspects of natural language processing
   – Intelligent linguistic
   – Computational Neuroscience

ICDATA'21 SCOPE: TOPICS OF INTEREST INCLUDE, BUT NOT LIMITED TO:

   – ALGORITHMS FOR BIG DATA:
        Data and Information Fusion
        Algorithms (including Scalable methods)
        Signal Processing
        Simulation and Modeling
        Data-Intensive Computing
        Parallel Algorithms
        Testing Methods
        High-dimensional Big Data
        Multilinear Subspace Learning
        Sampling Methodologies
        Streaming

   – BIG DATA FUNDAMENTALS:
        Novel Computational Methodologies
        Algorithms for Enhancing Data Quality
        Models and Frameworks for Big Data
        Graph Algorithms and Big Data
        Computational Science
        Computational Intelligence

   – INFRASTRUCTURES FOR BIG DATA:
        Cloud Based Infrastructures (storage & resources)
        Grid and Stream Computing for Big Data
        High Performance Computing
        Autonomic Computing
        Cyber-infrastructures and System Architectures
        Programming Models and Environments to Support Big Data
        Software and Tools for Big Data
        Big Data Open Platforms
        Emerging Architectural Frameworks for Big Data
        Paradigms & Models for Big Data

   – BIG DATA MANAGEMENT AND FRAMEWORKS:
        Database and Web Applications
        Federated Database Systems
        Distributed Database Systems
        Distributed File Systems
        Distributed Storage Systems
        Knowledge Management and Engineering
        Massively Parallel Processing (MPP) Databases
        Novel Data Models
        Data Preservation and Provenance
        Data Protection Methods
        Data Integrity and Privacy Standards and Policies
        Novel Data Management Methods
        Crowdsourcing
        Stream Data Management
        Scientific Data Management

   – BIG DATA SEARCH:
        Multimedia and Big Data
        Social Networks
        Data Science
        Web Search and Information Extraction
        Scalable Search Architectures
        Cleaning Big Data, Acquisition & Integration
        Visualization Methods for Search
        Time Series Analysis
        Recommendation Systems
        Graph Based Search and Similar Technologies

   – PRIVACY IN THE ERA OF BIG DATA:
        Cryptography
        Threat Detection Using Big Data Analytics
        Privacy Threats of Big Data
        Privacy Preserving Big Data Collection
        Intrusion Detection
        Socio-economical Aspect of Big Data + Privacy & Security

   – APPLICATIONS OF BIG DATA:
        Big Data as a Service
        Big Data Analytics in e-Government and Society
        Applications in Science, Engineering, Healthcare, Visualization,
           Business, Education, Security, Humanities, Bioinformatics,
           Health Informatics, Medicine, Finance, Law, Transportation,
           Retailing, Telecommunication, all Search-based applications, …

   – DATA MINING/MACHINE LEARNING TASKS:
        Regression/Classification
        Time series forecasting
        Segmentation/Clustering/Association
        Deviation and outlier detection
        Explorative and visual data mining
        Web mining
        Mining text and semi-structured data
        Temporal and spatial data mining
        Multimedia mining (audio/video)
        Mining “Big Data”

   – DATA MINING ALGORITHMS:
        Artificial Neural Networks / Deep Learning
        Fuzzy logic and rough sets
        Decision trees/rule learners
        Support vector machines
        Evolutionary computation/meta heuristics
        Statistical methods
        Collaborative filtering
        Case based reasoning
        Link and sequence analysis
        Ensembles/committee approaches

   – DATA MINING INTEGRATION:
        Mining large scale data/big data
        Data and knowledge representation
        Data warehousing and OLAP integration
        Integration of prior domain knowledge
        Metadata and ontologies
        Agent technolog ies for data mining
        Legal and social aspects of data mining

   – DATA MINING PROCESS:
        Data cleaning and preparation
        Feature selection and transformation
        Attribute discretisation and encoding
        Sampling and rebalancing
        Missing value imputation
        Model selection/assessment & comparison
        Induction principles
        Model interpretation

   – DATA MINING APPLICATIONS:
        Bioinformatics
        Medicine Data Mining
        Business / Corporate / Industrial Data Mining
        Credit Scoring
        Direct Marketing
        Database Marketing
        Engineering Mining
        Military Data Mining
        Security Data Mining
        Social Science Mining
        Data Mining in Logistics

   We particularly encourage submissions of industrial applications
   and case studies from practitioners. These will not be evaluated
   using solely theoretical research criteria, but will take general
   interest and presentation into consideration.

ALL ACCEPTED PAPERS WILL BE PUBLISHED BY

   Publisher: Springer Nature – Book Series:
            Transactions on Computational Science & Computational
            Intelligence
            https://www.springer.com/series/11769 (ISSN: 2569-7072)

   Indexation: Subject to Springer science indexation which includes:
            online Springer Link (link.springer.com/), Scopus
            (www.info.scopus.com), SCI Compendex, EI Compendex
            (www.ei.org), EMBASE, Web of Science, Inspec, ACM digital
            library, Google Scholar, EBSCO, and others.

INTRODUCTION:

   We anticipate having between 1,000 and 2,000 participants in the
   event (CSCE Congress) that this event is part of. In order
   to leverage synergy between various CS & CE fields, the program
   committees of a number of major research meetings have their
   2021 events held at one venue (same location and dates). This joint
   research event is composed of a number of tracks (joint-conferences,
   sessions, workshops, poster and panel discussions); all
   will be held simultaneously, same location and dates: July 26-29,
   2021. For the complete list of joint conferences, refer to:
   https://www.american-cse.org/csce2021/conferences
   This year's Congress will be a hybrid event that combines a “live”
   in-person event with a “virtual” online component.

   We anticipate having between 1,000 and 2,000 participants in the
   Congress. The congress includes 20 major tracks, composed of: 122
   technical, research, and panel sessions as well as a number of
   keynote lectures. Last year, the Congress had attracted speakers,
   authors and participants affiliated with over 158 different
   universities (including many from the top 50 ranked institutions),
   major IT corporations (including: Microsoft, Google, Apple, SAP,
   Facebook, Oracle, Amazon, Yahoo, Samsung, IBM, Ebay, GE, Siemens,
   Philips, Ericsson, BAE Systems, Hitachi, NTT, Twitter, Uber
   Technologies, …), major corporations (including: Exxon Mobil,
   Johnson & Johnson, JPMorgan Chase, PetroChina, GlaxoSmithKline, HSBC,
   Airbus, Boeing, Hyundai, Goldman Sachs, Deutsche Bank, …), government
   research agencies (NSF, NIH, DoE, US Air Force, NSA National Security
   Agency, Central Intelligence Agency, …), US national laboratories
   (including, NASA National Aeronautics and Space Administration, ANL
   Argonne National Lab, Sandia National Lab, ORNL Oak Ridge National Lab,
   Lawrence Berkeley National Lab, Lawrence Livermore National Lab,
   Los Alamos National Lab, Pacific Northwest National Lab, …), and a
   number of Venture Capitalists as well as distinguished speakers
   discussing Intellectual Property issues. Last year, 54% of attendees
   were from academia, 25% from industry; 20% from government and
   funding agencies; and 1% unknown. About half of the attendees were
   from outside USA; from 69 nations.

   See the web links below for a small subset of publications based on
   papers accepted for this set of conferences: many of these books and
   journal special issues have already received the top 25% downloads
   in their respective fields and/or identified as “Highly Accessed” by
   publishers and/or science citation index trackers.

   https://www.american-cse.org/csce2021/special_issues
   https://www.american-cse.org/csce2021/publisher
   https://www.springer.com/series/11769?detailsPage=titles

KEYNOTE LECTURES AND TUTORIALS:

   There will be between 10 and 15 Keynote lectures and Invited Talks;
   speakers include world-renowned scientists and educators. Featured
   Keynote Speakers in recent years have included:

   – Prof. David A. Patterson (pioneer, architecture, UC Berkeley)
   – Prof. Ian Foster (known as Father of Grid Computing; U. of Chicago & ANL)
   – Prof. John Koza (known as Father of Genetic Programming; Stanford U.)
   – Prof. Barry Vercoe (Founding member of MIT Media Lab, MIT)
   – Dr. K. Eric Drexler (known as Father of Nanotechnology)
   – Dr. Jose L. Munoz (NSF Program Director and CTO of NSF Office of
     Cyber-infrastructure)
   – Prof. Michael J. Flynn (Stanford U.; known for Flynn's taxonomy)
   – Dr. Firouz Naderi (former Head of NASA Mars Exploration Program;
     former Administrator and/or Director of Jet Propulsion Lab,
     CalTech/NASA; NASA's JPL Solar System Exploration
   – Prof. Ruzena Bajcsy (pioneer, VR, UC Berkeley)
   – Prof. Viktor K. Prasanna (pioneer, U. of Southern California)
   – Prof. David Lorge Parnas (pioneer of software engineering)
   – Prof. Eugene H. Spafford (Executive Director, CERIAS and Professor,
     Purdue University)
   – Prof. Haym Hirsh (Dean, Cornell University & former NSF admin)
   – Prof. Alfred Inselberg (Tel Aviv U, Israel; Senior Fellow, San Diego
     Supercomputing Center; Inventor of the multidimensional system of
     Parallel Coordinates and author of textbook)
   – Prof. H. J. Siegel (Abell Endowed Chair Distinguished Professor of ECE
     and Professor of CS; Director, CSU Information Science and Technology
     Center (ISTeC), Colorado State University, Colorado, USA)
   – Prof. Amit Sheth (LexisNexis Eminent Scholar; Founder/Executive Director,
     Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis))
   – Prof. John H. Holland (known as Father of Genetic Algorithms;
     U. of Michigan)
   – Prof. Lotfi A. Zadeh (Father of Fuzzy Logic, UC Berkeley)
   – Dr. Leonid I. Perlovsky (Harvard University and CEO LP Information Tech)
   – Dr. James A. Crowder (Chief Engineer, Raytheon Intelligence)
   – Prof. Diego Galar (Director & Pro-Vice-Chancellor, Lulea University of
     Technology, Sweden)
   – and over 200 other distinguished speakers.

   The Congress is among the top five largest annual gathering of
   researchers in computer science, computer engineering, data science,
   artificial intelligence, STEM, and applied computing. We anticipate
   to have attendees from about 75 countries and territories. To get a
   feeling about the conferences' atmosphere, see some delegates photos
   available at (over 2,000 photos): https://photos.ucmss.com/

SUBMISSION OF PAPERS:  Submission portal:  https://american-cse.org/

   All accepted papers will be published by

   Publisher: Springer Nature – Book Series:
            Transactions on Computational Science & Computational
            Intelligence
            https://www.springer.com/series/11769  (ISSN: 2569-7072)

   Indexation: Subject to Springer science indexation which includes:
            online Springer Link (link.springer.com/), Scopus
            (www.info.scopus.com), SCI Compendex, EI Compendex
            (www.ei.org), EMBASE, Web of Science, Inspec, ACM digital
            library, Google Scholar, EBSCO, and others.

   Prospective authors are invited to submit their papers by uploading
   them to the evaluation web site at:  https://american-cse.org/
   Submissions must be uploaded by the due date (see IMPORTANT DATES)
   and must be in either MS doc or pdf formats (maximum of 10 pages for
   Regular Research Papers; maximum of 6 pages for Short Research
   Papers; and maximum of 3 pages for Extended Abstract/Poster Papers –
   the number of pages includes all figures, tables, and references).
   ALL REASONABLE TYPESETTING FORMATS ARE ACCEPTABLE (many authors use
   Springer's one-column style format for their submissions or IEEE
   style format: later, the authors of accepted papers will be asked
   to follow a particular typesetting format to prepare their final
   papers for publication). Papers must not have been previously
   published or currently submitted for publication elsewhere.

   The first page of the paper should include the followings:
      – Title of the paper
      – Name, affiliation, postal address, and email address of each
        author (identify the name of the Contact Author)
      – Abstract (between 100 and 120 words)
      – A maximum of 5 topical keywords that would best represent the
        work described in the paper
      – Write the type of the submission as “Regular Research Paper”,
        “Short Research Paper”, or “Extended Abstract/Poster Paper”.
      – The actual text of the paper can start from the first page
        (space permitting).
      Submissions are to be uploaded to the submission/evaluation web site
      portal at https://american-cse.org/

   Type of Submissions/Papers:

     – Full/Regular Research Papers (maximum of 10 pages):
       Regular Research Papers should provide detail original research
       contributions. They must report new research results that
       represent a contribution to the field; sufficient details and
       support for the results and conclusions should also be provided.
       The work presented in regular papers are expected to be at a
       stage of maturity that with some additional work can be published
       as journal papers.

     – Short Research Papers (maximum of 6 pages):
       Short Research Papers report on ongoing research projects. They
       should provide overall research methodologies with some results.
       The work presented in short papers are expected to be at a stage
       of maturity that with some additional work can be published as
       regular papers.

     – Extended Abstract/Poster Papers (maximum of 3 pages):
       Poster papers report on ongoing research projects that are still
       in their infancy (i.e., at very early stages). Such papers tend
       to provide research methodologies without yet concrete results.

   Each paper will be peer-reviewed by two experts in the field for
   originality, significance, clarity, impact, and soundness. In cases
   of contradictory recommendations, a member of the conference program
   committee would be charged to make the final decision (accept/reject);
   often, this would involve seeking help from additional referees.
   Papers whose authors include a member of the conference program
   committee will be evaluated using the double-blinded review process.
   (Essay/philosophical papers will not be refereed but may be considered
   for discussion/panels).

PROPOSAL FOR ORGANIZING WORKSHOPS/SESSIONS:

   The Congress is composed of a number of tracks. A track can be a session,
   a workshop, or a symposium. A session will have at least 6 papers; a
   workshop at least 12 papers; and a symposium at least 18 papers. Track
   chairs will be responsible for all aspects of their tracks, including:
   soliciting papers, reviewing, selecting, … The names of track chairs
   will appear as Track Editors in the conference proceedings and they
   will be presented achievement awards at appropriate professional levels
   during the Award Ceremony on site at the congress. Track chairs who
   attract a sufficient number of solid papers can propose to edit books
   with a major publisher based on the extended versions of the papers
   accepted in their tracks (the congress will facilitate and help such
   track chairs to get the publisher's approval: such as Springer,
   Elsevier, …).

   Proposals to organize tracks (sessions, workshops, or symposiums) should
   include the following information: name and address (+ email) of proposer,
   his/her biography, title of track, a 100-word description of the topic of
   the track, the name of the conference the track is submitted for
   consideration (i.e., ICAI, ICDATA), and a short description on how the
   track will be advertised (in most cases, track proposers solicit papers
   from colleagues and researchers whose work is known to the track
   proposer). E-mail your track proposal to cs@american-cse.org . We would
   like to receive the track proposals as soon as possible.

CAREER, JOB, & EDUCATION FAIR:

   https://www.american-cse.org/csce2021/career_fair
   The CSCE 2021 Congress plans to host a one-day Career, Job, & Education
   Fair on July 27, 2021. This annual strategic event provides the congress
   attendees and participants with opportunities to connect with employers
   and educators and learn more about career options. Corporations and
   Universities can also exhibit their products, services, and degree programs
   during the event. Interested parties should contact cs@american-cse.org .

IMPORTANT DATES:

   As Soon As Possible: Track/Session/Workshop/Symposium Proposals

   March 31, 2021:      Submission of papers: https://american-cse.org/
                        – Full/Regular Research Papers (maximum of 10 pages)
                        – Short Research Papers (maximum of 6 pages)
                        – Abstract/Poster Papers (maximum of 3 pages)

   April 11, 2021:      Notification of acceptance (+/- two days)
   May 10, 2021:        Final papers + Copyright + Registration
   July 26-29, 2021:    ICAI'21:  23rd International Conference on Artificial
                                  Intelligence
                        https://www.american-cse.org/csce2021/conferences-ICAI
                        +
                        ICDATA'21: 17th International Conference on Data Science
                        https://www.american-cse.org/csce2021/conferences-ICDATA
                        +
                        Affiliated/joint events:
                        https://www.american-cse.org/csce2021/

CONTACT:
   Questions and inquiries should be sent to:
   Conference Secretariat: cs@american-cse.org