Conferences and Meetings on Information & Knowledge Management, Big Data Computing

The ADT 2019 conference focus is on algorithmic decision theory broadly defined, seeking to bring together researchers and practitioners coming from diverse areas of Computer Science, Economics and Operations Research in order to improve the theory and practice of modern decision support.

Algorithms, Argumentation Theory, Artificial Intelligence, Computational Social Choice, Database Systems, Decision Analysis, Discrete Mathematics, Game Theory, Machine Learning, Matching, Multi-agent Systems, Multiple Criteria Decision Aiding, Networks, Optimization, Risk Management, and Utility Theory

Operational research,    Neural Networks and Artificial Intelligence, Machine Learning

The 8th conference on Artificial Intelligence and Natural Language (AINL 2019) invites everyone interested in intellectual technologies, both from academic institutes and innovative companies. The conference aimed to bring together experts for creating a platform for sharing experience, extending contacts and searching for possible collaboration.

text mining, speech technologies, dialogue systems, information retrieval, machine learning

Natural Language Processing, Computational Linguistics,    Neural Networks and Artificial Intelligence, Machine Learning

The British Institute of Radiology

This one-day event has a distinguished panel of speakers including radiologists, medical informaticists, data scientists, experts in public health and people interested in using technology to improve patient care. This event is suitable for radiologist (consultants and trainees), radiation oncologists, medical physicists, radiographers, public health doctors, epidemiologists, researchers, academics, healthcare managers, policy makers, healthcare IT professionals and industry representatives.

The British Institute of Radiology;     Phone: [+442036682230];     Email: conference@bir.org.uk

Healthcare Technologies,    Clinical Data Management, e-Health

Big Data Conference Europe is a three-day conference with technical talks in the fields of Big Data, High Load, Data Science, Machine Learning and AI. Conference brings together developers, IT professionals and users to share their experience, discuss best practices, describe use cases and business applications related to their successes. The event is designed to educate, inform and inspire – organized by people who are passionate about Big Data and Data Exploration. We look forward to seeing you there!

Email: evelina@dataminer.lt

Big Data, High Load, Machine Learning, AI, Data Science.

Asian Regional Section of the International Association for Statistical Computing (IASC-ARS)

Statistical Computing for AI and Big Data

Neural Networks and Artificial Intelligence, Machine Learning,    Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic

Prague University of Economics

CONFENIS 2019 provides an international forum for Enterprise Information System (EIS) researchers and practitioners from all over the world to come together, present and discuss their latest research findings and ideas. The conference is specifically aiming at facilitating the exchange of ideas and advances in all aspects and developments of EIS.

Email: antonin.pavlicek@vse.cz

EIS, Enterprise Information System, Big Data, Cloud Computing, Internet of Things

Embedded Systems & Ubiquitous Computing, RFIDs,    Internet of Things (IoT) and Sensor Networks

The American University Center for Data Science will run the Institute for Data Science and Big Data on campus, which is open to all under a university course credit or certificate option, both geared to working professionals. The institute will cover the basics of data science, including obtaining relevant data, cleaning and exploring data, creating models, stating inferences, making reliable predictions, and communicating findings. The course consists of a mixture of lectures, guest speakers, and group assignments. It will take place over 10 working days, Monday through Saturday, 9 AM to 5 PM. To apply, interested parties can submit a resume and letter of interest to dsi@american.edu.

The Organizing Committee is pleased to announce that 2020 3rd International Conference on Big Data and Smart Computing (ICBDSC 2020) will take place in Sydney, Australia on January 12-15, 2020 as a workshop of ICSIM 2020. The conference is addressed to academics, researchers and professionals with a particular interest related to the conference topic. It brings together academics, researchers and professionals in the field of Big Data and Smart Computing making the conference a perfect platform to share experience, foster collaborations across industry and academia, and evaluate emerging technologies across the globe.

Air Traffic Management Research Institute (ATMRI), School of Mechanical and Aerospace Engineering, NTU

The aim of the conference is to bring together world leading experts in Artificial Intelligence and Air Transportation on one platform to promote a fruitful research on well-described Air Transportation problems, using and developing techniques from Artificial Intelligence and Data Science, such as Machine Learning, Evolutionary Computation, Constraint Programming, Graph-based methods, Data-driven methods, Data Analytics, etc.

Operational research,    Aviation & Spaceflight

Networks, Internet,    Search Engines and Data Mining

CHIIR provides a forum for the dissemination and discussion of research on the user-centered aspects of information interaction and information retrieval. CHIIR focuses on elements such as human involvement in search activities, and information seeking and use in context. The conference represents a merger of two successful past events: the Information Interaction in Context conference (IIiX) and the Human Computer Information Retrieval symposium (HCIR).

Human-Computer Interaction, User Experience,    Search Engines and Data Mining

C3DIS aims to build a national community of practice of scientists, researchers, and computing, data and information management specialists from public sector research organisations. All of these professionals share a common interest: the production of breakthrough science outcomes that require large scale, complex computations and analyses to be carried out over massive data sets.

Scientific Computing ,    High Performance Computing, Supercomputing, Parallel Computing

Welcome to the fourth edition of Data Innovation Summit. It is going to be bigger, better, more insightful and more exciting than ever. This year’s event will focus on practical case studies on Applied Innovation, Analytics and Visualisation, Machine Learning, Artificial Intelligence, Data Management, Data engineering, IOT insight and technology.

Neural Networks and Artificial Intelligence, Machine Learning,    Database Technology and Design

The advancement in computing and storage capabilities of modern computational clusters fosters use of novel statistical techniques in machine learning and deep networks. Such data-driven techniques allow one to learn model features and characteristics that are difficult for mathematical methods alone to reveal. Many computational methods achieve model and complexity discovery using methods that lie at the nexus of mathematical, statistical, and computational disciplines. Statistical methods often employ "big data" approaches that glean predictive capability from diverse and enormous databases of information. Emerging methods in machine learning and deep networks can provide impressive results. This workshop gathers researchers at the frontier of large-scale statistical computation, data science, tensor decompositions and approximations, and data-driven model learning, to focus on modern challenges that use data to reduce complexity of models.

DECHEMA, Gesellschaft für Chemische Technik und Biotechnologie e.V.

Big Data Analytics has become important to the process industry. It reveals new market opportunities and could lead to process advantages and reductions in production costs. Whether in the chemical, pharmaceutical, biotech, energy or other related industries: enormous amounts of data are created every second. These huge amounts of data need to be analyzed to further improve processes, enhance production, develop innovative products, plan maintenance and, in general, understand what will happen next. The application areas in which data analytics can be used profitably are diverse and nowhere near exhausted in process industry.

INSTICC – Institute for Systems and Technologies of Information, Control and Communication

The purpose of the 22nd International Conference on Enterprise Information Systems (ICEIS) is to bring together researchers, engineers and practitioners interested in the advances and business applications of information systems. Six simultaneous tracks will be held, covering different aspects of Enterprise Information Systems Applications, including Enterprise Database Technology, Systems Integration, Artificial Intelligence, Decision Support Systems, Information Systems Analysis and Specification, Internet Computing, Electronic Commerce, Human Factors and Enterprise Architecture.

1 . Databases and Information Systems Integration, 2 . Artificial Intelligence and Decision Support Systems, 3 . Information Systems Analysis and Specification, 4 . Software Agents and Internet Computing5 . Human-Computer Interaction, 6 . Enterprise Architecture

Software Engineering,    Human-Computer Interaction, User Experience

Institute for Systems and Technologies of Information, Control and Communication (INSTICC)

The internet of things (IoT) is a platform that allows a network of devices (sensors, smart meters, etc.) to communicate, analyse data and process information collaboratively in the service of individuals or organisations. The IoT network can generate large amounts of data in a variety of formats and using different protocols which can be stored and processed in the cloud. The conference looks to address the issues surrounding IoT devices, their interconnectedness and services they may offer, including efficient, effective and secure analysis of the data IoT produces using machine learning and other advanced techniques, models and tools, and issues of security, privacy and trust that will emerge as IoT technologies mature and become part of our everyday lives. Big Data (BD) has core values of volume, velocity, variety and veracity. After collecting much data from IoT, BD can be jointly used with machine learning, AI, statistical and other advanced techniques, models and methods, which can create values for people and organizations adopting it, since forecasting, deep analysis and analytics can help identify weaknesses and make improvements based on different analysis. Maintaining a high level of security and privacy for data in IoT are crucial and we welcome recommendations, solutions, demonstrations and best practices for all forms of security and privacy for IoT and BD.

Phone: [+351 265 520 184];     Email: iotbds.secretariat@insticc.org

Institute for Systems and Technologies of Information, Control and Communication (INSTICC)

COMPLEXIS – The International Conference on Complexity, Future Information Systems and Risk, aims at becoming a yearly meeting place for presenting and discussing innovative views on all aspects of Complex Information Systems, in different areas such as Informatics, Telecommunications, Computational Intelligence, Biology, Biomedical Engineering and Social Sciences. Information is pervasive in many areas of human activity – perhaps all – and complexity is a characteristic of current Exabyte-sized, highly connected and hyper dimensional, information systems. COMPLEXIS 2020 is expected to provide an overview of the state of the art as well as upcoming trends, and to promote discussion about the potential of new methodologies, technologies and application areas of complex information systems, in the academic and corporate world. COMPLEXIS 2020 seeks papers reporting research work, applications or case-studies, on topics indicated below in the section “Conference Areas”. Papers describing advanced prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged. Both technological and social-oriented papers are accepted. All papers must describe original work, not previously published or submitted to another conference. Accepted papers, presented at the conference by one of the authors, will be published in the Proceedings of COMPLEXIS under an ISBN, and will be indexed by major indexes. Acceptance will be based on quality, relevance and originality. Both full research reports (regular papers) and work-in-progress reports (position papers) are welcome. There will be both oral and poster sessions. Special sessions, dedicated to case-studies and focused presentations, as well as tutorials dedicated to technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial, workshop or special session are invited to contact the conference secretariat or visit the conference website.

Phone: [+351 265 520 184];     Email: complexis.secretariat@insticc.org

Complex Networks,    Complex Systems, Chaos and Self-Organisation

Huazhong University of Science and Technology(HUST) in Wuhan

KES International

KES-IDT-20 is an international scientific conference for research in the area of intelligent decision technologies with subjects considering theory and application. This conference is dedicated to techniques that improve decision making using intelligent paradigms and other methods.

Institute for Mathematical Sciences/National University of Singapore

Causal inference is the study of quantifying whether a treatment, policy, or an intervention, denoted as A, has a causal effect on an outcome interest, denoted as Y. What distinguishes a causal effect of A on Y from an associative effect of A on Y, say by computing the correlation between A and Y, is that under a causal effect, intervening on the treatment A leads to changes in the outcome Y. Hence, a causal effect is a stronger notion of a relationship between A and Y than an associative effect.

Applied Mathematics (in general),    Courses and Events for Math Students and Early Career Researchers

Institute for Mathematical Sciences/National University of Singapore

The more data we have, the more data we need to process. Whether it is internet traffic or biological data, the hardware is never fast enough. The aim of this workshop is to focus on analysing data under new models: when the data cannot be stored (e.g., identifying viruses in the Internet traffic), when we use multiple cores to analyse the data, and when we are generating short sketches of the data to be sent and analysed by someone else. We believe a new set of algorithmic techniques (which rely mostly on statistics and on data structures) can be used in these models, and wish to find such techniques and employ them. An important focus of this workshop is to find algorithms which are elegant, and thus can also be used in practice. To develop these algorithms, it is critical to connect the key subareas of algorithmic research on big data. These key subareas include streaming, sketching, and sampling. The goal of the workshop is to bring researchers together from these different sub-areas and to establish strong collaborations among the attendees.

Applied Mathematics (in general),    Algorithms

The annual SIGIR conference is the major international forum for the presentation of new research results, and the demonstration of new systems and techniques, in the broad field of information retrieval (IR). The 43rd ACM SIGIR conference, to be held in Xi'an, China, welcomes contributions related to any aspect of information retrieval and access, including theories and foundations, algorithms and applications, and evaluation and analysis.

Institute for Mathematical Sciences/National University of Singapore

The field of optimization has undergone tremendous growth in its applications in science, engineering, business and finance in the past few decades. The growth has accelerated in recent years with the advent of big data analytics where optimization forms the core engine for solving and analyzing the underlying models and problems of extracting meaningful information from available data for the purpose of better decision making or getting better insights into the data sources. Spurred by the application needs and motivated by new emerging models in machine learning and data analytics, optimization research (in theory and algorithms) has also undergone rapid transformation and progress in recent years. In particular, demands for fast algorithms to solve extremely large-scale optimization problems arising from big data analytics have spurred numerous exciting new research directions in optimization theory and algorithms. The latter in turn helps to shape the development of optimization models and techniques in machine and statistical learning.

Applied Mathematics (in general),    Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic

Association of Computing Machinery (acm)

The 22nd International Conference on Knowledge Engineering and Knowledge Management is concerned with all aspects about eliciting, acquiring, modeling and managing knowledge, and the construction of knowledge-intensive systems and services for the semantic web, knowledge management, e-business, natural language processing, intelligent information integration, and so on.

The International Semantic Web Conference (ISWC) is the leading conference for research on Semantic Web topics. It is held annually and is the successor of the Semantic Web Working Symposium (SWWS).