Jip Dekker

Jip Dekker is a Research Fellow at the Department of Data Science & AI, Monash University. His expertise lies in constraint programming, optimization, and neuro-symbolic AI. He holds a PhD from Monash University (2021), an MSc from Uppsala University (2017), and a BSc from Radboud University (2014).

Research interests include constraint-based modeling languages, SAT solving techniques, hybrid optimization solvers, and applications in transportation scheduling. He has contributed to projects such as the Next-Gen Lazy Clause Generation (NLCG) and sports scheduling optimization frameworks.

Recent work spans neuro-symbolic AI explainability, circadian rhythm protocols, and rail dispatch algorithms. His articles demonstrate cross-disciplinary impact across computer science, operations research, and biomedical research.

• Received the OPTIMA Education Award (2022) and recognition for SETU results (2020)
• Contributed to 6 peer-reviewed publications since 2017, with 15+ citations

Advising roles include collaborative projects on sports fixtures and constraint solver development. Active in organizing international conferences like CPAIOR and AAAI, and maintains visiting researcher ties with Uppsala University.