SPSTAt 2026
International Conference on Statistics, Data Science, and Analytics
in celebration of the Philippine National Statistics Month 2026
When
October 19–21, 2026
Three days of keynotes, talks, and workshops
Where
MSU-IIT
Iligan City, Philippines
What
Highlights
Keynotes, papers, posters, workshops & more
Get involved
Open Call
Submit your abstract
Important Dates
1 August 2026
Call for Papers Opens
25 August 2026
Abstract Submission Deadline
30 August 2026
Notification of Acceptance
19–21 October 2026
Conference Date
Note: Early screening for the submission begins on August 15, 2026, because slots are limited.
About the Conference
The SPSTAt 2026 International Conference on Statistics, Data Science, and Analytics brings together statisticians, data scientists, researchers, educators, students, government practitioners, industry professionals, users of statistics, and enthusiasts from around the world to exchange ideas, share research, foster collaborations, and advance evidence-based decision-making. Held annually in October in celebration of the Philippine National Statistics Month, the conference aims to become one of the highlights of the national celebration by promoting excellence in statistical science, interdisciplinary research, innovation, and international collaboration. Participants will have opportunities to present original research, engage with distinguished keynote speakers, participate in workshops and special sessions, expand professional networks, and contribute to meaningful discussions on the role of statistics and data science in addressing today's most pressing societal challenges. The conference will also host the SPSTAt Annual Scientific Convention and General Assembly, marking the Society's continuing commitment to strengthening the statistics community and fostering collaboration among academia, government, industry, and international partners.
Tracks
SPSTAt 2026 welcomes contributions across the following areas.
A. Statistical Theory and Methodology
- Probability Theory
- Statistical Inference
- Bayesian Statistics
- Sampling Theory
- Experimental Design
- Sequential Analysis
- Time Series Analysis
- Survival Analysis
- Longitudinal Data Analysis
- Categorical Data Analysis
- Multivariate Analysis
B. Applied Statistics
- Official Statistics
- Government Statistics
- Agricultural Statistics
- Environmental Statistics
- Climate Statistics
- Fisheries Statistics
- Health and Biostatistics
- Epidemiology
- Financial Statistics
- Industrial Statistics
- Quality Improvement
- Sports Analytics
C. Data Science and Artificial Intelligence
- Machine Learning
- Deep Learning
- Statistical Learning
- Predictive Analytics
- Big Data Analytics
- Data Mining
- Business Analytics
- Artificial Intelligence
- Explainable and Responsible AI
D. Computational Statistics
- Statistical Computing
- High-Performance Computing
- Monte Carlo Methods
- Simulation
- Optimization
- Scientific Computing
- R, Python, Julia and Related Applications
E. Spatial and Spatio-temporal Analytics
- Spatial Statistics
- Geostatistics
- GIS Applications
- Disease Mapping
- Environmental Monitoring
- Remote Sensing
- Climate Analytics
F. Citizen Science and Community Analytics
- Citizen Science
- Participatory Data Collection
- Community-based Research
- Indigenous Knowledge Systems
- Sustainable Development Analytics
- Public Policy Analytics
G. Statistics Education
- Teaching Innovations
- Statistics Education Research
- Curriculum Development
- Technology-enhanced Learning
- Assessment
- Outreach Programs
Publication Opportunities
Conference Abstract Book
Accepted abstracts will be published in the SPSTAt 2026 Conference Abstract Book.
Proceedings & Partner Journals
Selected full papers may be invited for publication in conference proceedings or partner journals, subject to peer review.
Conference Highlights
International Keynote and Invited Speakers
Scientific Paper Presentations
Poster Presentations
Workshops
Student Research Forum
Professional Networking Activities
SPSTAt Annual Scientific Convention and General Assembly
Keynote Speakers
View all speakers →
Prof. Dr. Olivier Thas
Hasselt University, Belgium · Professor, Ghent University, Belgium · Honorary Professor, University of Wollongong, Australia
Prof. Dr. Thomas Neyens
UHasselt Data Science Institute (DSI) & Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat) · Professor of Biostatistics, KU Leuven, Belgium
Prof. Dr. Paulo Canas Rodrigues
Federal University of Bahia (UFBA), Brazil · Director, Statistical Learning Laboratory (SaLLy)
Hosted by
Mindanao State University–Iligan Institute of Technology
Department of Mathematics and Statistics
Premier Research Institute of Science and Mathematics – Center for Computational Analytics and Modeling
In collaboration with
- PRISM-Center for Mathematical and Theoretical Physical Sciences (PRISM-CMPTS)
- Southern Philippines Society of Theoretical and Applied Statistics (SPSTAt) Inc.
- VLIR-UOS TEAM SEABREEZE Project - BIGSEA Initiative