Call for Papers

First International Workshop on
Generative Problem Solving
(GPS 2026)
Part of ICSC 2026, AIxDKE 2026, AIxMM 2026

 

Generative Problem Solving (GPS) is defined as the capability of automatically or semi-
automatically generating data, problems, and solutions. In addition to text-based question answering, GPS addresses computational problem solving that integrates classic and modern AI technologies, data and knowledge engineering, and other computer science disciplines.

 

Areas of interest include, but are not limited to:

• STEM education at K–12 and higher education levels

• Core topics in computer science such as combinatorics, graph theory, and programming,, signal processing, circuit and chip design, data and knowledge engineering, robotic computing and communication

• Applications across medicine and healthcare, business, science, engineering, and technology, and humanities, education, and art

 

Contributions will be reviewed for quality and relevance to the workshop’s theme. Theoretical and applied papers and papers that capture best practices and lessons learned from field studies are encouraged. Submission of preliminary results would also be considered.

Submissions in PDF format through this link by December 15, 2025.
 
Workshop Organizers
Dick Bulterman, Vrije Universiteit Amsterdam, The Netherlands
Chih-Hung Chang, Washington University School of Medicine in St. Louis, USA
Bryan Chou, Cal State Pomona, USA (Co-Chair)
Tinglong Dai, Johns Hopkins University, USA
Daniela D'Auria, Free University of Bozen-Bolzano, Italy
Luca Muratore, IIT, Italy
​Fabio Persia, University of LAquila, Italy
Giovanni Pilato, Italian Research Council, Italy
Florian Schimanke, HSW University of Applied Sciences, Germany
Phillip C.-Y. Sheu, University of California, Irvine, USA (Chair)
Mustafa Sert, Başkent University, Turkey
Jackson Wu, Taipei Medical University, Taiwan
Atsuo Yoshitaka, JAIST, Japan