IASC News June 2023
Results of the election of the IASC Executive Committee 2023-2025
Title: New IASC executive committee
Summary: The new IASC executive committee has been elected and will continue to promote the activities of IASC.
The Elected Members of IASC Executive Committee for the period 2023-2025 are the following:
Position Name Country
Past-President Christophe Croux France
President Chun-houh Chen Taiwan
Newly Elected Officers
President-Elect Paulo Canas Rodrigues Brazil
Scientific Secretary Ying Chen Singapore
Treasurer Zdeněk Hlávka Czech Republic
Webmaster Kosuke Okusa Japan
ISI WSC Conference Officer Ray-Bing Chen Taiwan
ISI Nominations Officer Philip Leung-ho Yu Hong Kong, China
Publication Officer Karel Hron Czech Republic
Summer School Officer Thomas Fung Australia
Young Statisticians Representative Natalia da Silva Uruguay
IASC Membership Officer Rosaria Lombardo Italy
Data Analysis Competition Officer Carlo Cavicchia The Netherlands
ISI Short Course and Outreach Officer Monday Adenomon Nigeria
Webinar Officer Luis Firinguetti Chile
2023 IASC Nominating Committee:
Monday Adenomon (Nigeria)
Chun-houh Chen (President-Elect, Taiwan)
Christophe Croux (President, France)
Luis Firinguetti (Chile)
Patrick J.F. Groenen (The Netherlands)
Fumitake Sakaori (Japan)
JDSSV – Call for papers for a special issue on Explainable Machine and Statistical Learning
Title: Call for contributions for a special issue on Explainable Machine and Statistical Learning of the Journal of Data Science, Statistics and Visualization
Summary: Submissions to this special issue should be done at jdssv.org following the standard requirements of the journal and by selecting “Special Issue on Explainable Machine and Statistical Learning.” Submissions will follow the standard JDSSV peer review process and is open until July 31, 2023.
The development of data analysis for large scale data and statistical learning methods for data science is gaining importance for researchers interested in extracting insight from data. To advance data science methods, collaboration between different scientific disciplines, such as, statistics, computer science, computational mathematics, physics, social sciences, economics, amongst others is needed to develop methodologies and approaches.
For this special issue on Explainable Machine and Statistical Learning with guest editors Tomaso Aste (University College London), Paola Cerchiello (University of Pavia), Nicola Torelli (University of Trieste) and Rosanna Verde (University of Campania “Luigi Vanvitelli” ), we call for papers treating themes related to the modeling and analysis of complex data (structured, non-structured, mixed), using data analytics, statistical learning, and machine learning methods. Submissions are encouraged that propose novel approaches and visualization tools to provide the explainability of such models, particularly in real applications. Finally, papers emphasizing multidisciplinary topics are especially welcome.
Submissions to this special issue should be done at jdssv.org following the standard requirements of the journal and by selecting “Special Issue on Explainable Machine and Statistical Learning.” Submissions will follow the standard JDSSV peer review process. Submission is open until July 31, 2023. We offer dual submissions, that is, papers that do not fit into the Special Issue will automatically be transferred to the regular submission channel unless the author specifies to submit only to the Special Issue. Papers will enter the review process immediately upon receipt (i.e., guest editors will not wait until the end of the submission window to start the review process). We intend to publish all accepted papers as a single special issue in 2024 after finalization of the review process.