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
972-4-6489923
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
Michal Horovitz
Ph.D. 2017, Technion, Israel
Postdoctoral Research Associate

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
Multi-objective mixed-integer quadratic models: A study on mathematical programming and evolutionary computation
IEEE Trans. Evol. Comp. doi: 10.1109/TEVC.2024.3374519
2024
Avoiding Redundant Restarts in Multimodal Global Optimization
In M. Affenzeller M., et al. Rds.), Parallel Problem Solving from Nature: Lecture Notes in Computer Science. Springer, Cham
2024
Multi-Objective Mixed-Integer Quadratic Models: A Study on Mathematical Programming and Evolutionary Computation
This paper appears in: IEEE Transactions on Evolutionary Computation On page(s): 1-15 Print ISSN: 1089-778X Online ISSN: 1941-0026 Digital Object Identifier: 10.1109/TEVC.2024.3374519
2024
Towards AI Research Agents in the Chemical Sciences
ChemRxiv. Cambridge: Cambridge Open Engage; 2024
2024
Contact Information
Research Group Leader
Prof. Ofer Shir
972-4-7700527
ofers@migal.org.il