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.
Principal Researcher
Prof. Ofer Shir
Computational Intelligence
972-4-7700527
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.
Team
Martin Feder
M.Sc. 2015, Technion, Israel
Research associate

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

Collaborations
Funding
Latest Publications
Toward an ImageNet Library of Functions for Global Optimization Benchmarking
arXiv preprint (2022)
2022
Algorithmically-guided discovery of viral epitopes via linguistic parsing: Problem formulation and solving by soft computing
Applied Soft Computing, Volume 129 (2022) 109509
2022
Algorithmically-guided postharvest by experimental combinatorial optimization
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022) 2027–2035
2022
Sequential Experimentation by Evolutionary Algorithms
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO-2022, New York, NY, USA, ACM Press (2022)
2022
Contact Information
Research Group Leader
Prof. Ofer Shir
972-4-7700527
ofers@migal.org.il