Data Science Association Committees
Conference Planning Committee
Plan & Organize Conferences
Seeking members to help plan and organize data science conferences around the world. Current conference locations include:
America:
New York City
Silicon Valley
Jackson Hole, Wyoming
Buenos Aires, Argentina
São Paulo, Brazil
Kauai, Hawaii
Aspen, Colorado
Telluride, Colorado
Revelstoke, Canada
Valle Nevado, Chile
Cruise / Sail - Virgin Islands
Asia
Suzhou / Shanghai, China
Bangalore, India
Cruise / Sail - Mekong River
Niseko United, Japan
Europe
Paris, France
Moscow, Russia
Cruise / Sail - Mediterranean
Kitzbuhel, Austria
Oceania
Melbourne, Australia
Auckland, New Zealand
Treble Cone, New Zealand
Cruise / Sail - South Pacific Islands
Africa
Nairobi, Kenya
Cape Town, South Africa
Cruise / Sail - Cape Town to Mombasa
Presentations & Papers
Conferences shall be focused on data science education and thus tax deductible in almost all legal jurisdictions.
Conference attendees shall have the opportunity to conduct a live presentation and/or present a paper.
Papers meeting requirements will have the opportunity to be published in the International Journal of Data Science (IJDS). The IJDS publishes both academic research and applied data science practitioner papers. Special Issues devoted to important topics may be published.
Conference Topics
Conference topics include both research data science and applied data science. The below list is not exclusive and other topics may be approved in the sole discretion of the committee.
Applied Data Science / investing
Applied Data Science / asset allocation
Applied Data Science / trading
Applied Data Science / artificial intelligence
Applied Data Science / healthcare
Applied Data Science / bio-technology
Applied Data Science / legal
Applied Data Science / decision-making
Applied Data Science / business
Applied Data Science / marketing
Applied Data Science / human resources
Applied Data Science / government
Applied Data Science / policy making
Applied Data Science / risk assessment & mitigation
Big data cloud, mining and management
Big data storage, processing, sharing and visualisation
Big data systems, tools, theory and applications
Business analytics, intelligence and mathematics
Computer science, hacking skills
Informatics and information systems and technology
Machine learning, web-based decision making
Management science, social sciences and statistics
Mathematical optimisation and mathematics of decision sciences
Multiple source data processing and integration
Network and social-graph analysis
Optimisation, performance measurement
Security and privacy
System analysis and theory
Volume, velocity and variety of big data on cloud