Computational Intelligence

We are primarily interested in Operational Research and Machine Learning aspects of experimental domains, that is, algorithmic design for practical physical- and life-sciences problems whose computerized models are unavailable or too expensive to be executed, and thus require real-world measurements when applying search/learning.

We foresee Computational Intelligence algorithms as facilitators that will assist experimental scientists in achieving optimal behavior of their systems and in identifying targeted phenomena. Our long-term research plan is to establish algorithmically-guided discovery tools for bio-systems. A primary pathway, adhering to this plan, is actively to devise specific algorithms for experimental optimization and learning of specific bio-systems.

Enlisted below are ongoing research projects at the Shir group:

• Experimental combinatorial optimization of Postharvest protocols (with Dr. Dan Gamrasni)
• Benchmarking Quantum Computers on Combinatorial Optimization Problems: A Pilot Study (with Dr. Alberto Moraglio/Exeter-U)
• Randomized search heuristics for integer programming (with Prof. Thomas Bäck/Leiden-U and Prof. Michael Emmerich/Jyväskylä-U)