Artificial intelligence (AI) is today support for different powerful data science and optimization techniques. For instance, data science commonly relies on artificial intelligence algorithms to efficiently solve classification, regression, and clustering problems. On the other hand, complex optimization problems that cannot be tackled via traditional mathematical programming techniques are commonly solved with AI-based optimization approaches such as the metaheuristics. Data science and AI-based optimization have also largely been used to solve problems related to scientific programming. Various examples are reported by the literature on task assignment in distributed/parallel systems, knowledge discovery, large-scale data mining, big data, distributed/parallel search, and text analysis/process/classification, among others. This special issue is devoted to publishing high-quality papers that involve theoretical and practical aspects of Scientific Programming related to data science and/or AI-based optimization. Reviews on this topic are also welcome.

Potential topics include but are not limited to the following:

• Large-scale data science and/or AI-based optimization
• Hybrids involving data science and AI-based optimization for scientific programming
• Integration of AI-based optimization, data science, and autonomous/distributed search
• Parallel/distributed data science and/or AI-based optimization
• Big data in scientific programming
• High performance computing and data science
• High performance computing and AI-based optimization
• Data science and/or AI-based optimization frameworks for scientific programming
• Data science and/or AI-based optimization for manufacturing and scheduling using scientific programming
• Data science and/or AI-based optimization for civil and financial engineering using scientific programming
• AI-based optimization and/or data science in robotics