Computational Intelligence

We are interested in learning and optimization questions related to systems within the Natural Sciences. Our group is especially interested in Machine/Statistical Learning and Global Optimization aspects of experimental domains, that is, practical physical-, life- and agro-sciences search-problems whose simulated models are unavailable and thus require real-world experimentation.

Prof. Ofer Shir


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 protein expression systems (with Dr. Noy/Migal)
  • Precision agriculture: geo-statistical learning (with Prof. Litaor/Migal)
  • Benchmarking randomized search heuristics (with Dr. Doerr/Sorbonne and Prof. Bäck/Leiden-U)
  • Effective Detection of Foliage Diseases in Vineyards (with Dr. Sharon/Migal)
  • Deep Learning of a Complementary Ensemble of Sporadic Input Maps (with Prof. Linker/Technion-IIT and Dr. Chen/Migal)

Principal Researcher

Prof. Ofer Shir

Prof. Ofer Shir
Computational Intelligence

The advent of modern laboratory and field experiments, as well as of computerized systems, enables researchers to control experiments and analyze their big-data in high-speed rates.


Assaf Israeli

M.Sc. 2020, Tel-Hai College. Israel
Research assistant and Ph.D. candidate



Latest Publications

Toward an ImageNet Library of Functions for Global Optimization Benchmarking

Yazmir B., Shir, O.M.
arXiv preprint (2022)

Algorithmically-guided discovery of viral epitopes via linguistic parsing: Problem formulation and solving by soft computing

Shir, O.M., Israeli, A., Caftory, A., Zepko, G., Bloch, I.
Applied Soft Computing, Volume 129 (2022) 109509

Algorithmically-guided postharvest by experimental combinatorial optimization

Shir, O.M., Yazmir, B., Israeli, A., Gamrasni, D.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022) 2027–2035

Sequential Experimentation by Evolutionary Algorithms

Shir, O.M., Bäck, T.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022)

Contact Information

Research Group Leader
Prof. Ofer Shir

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