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Recipient of the award for 2021


Portrait photo
Lana Khalifa, recipient of the award, 2021

The student presented orderly results for each track in order to identify the most cost-effective alternatives for investment, given today's technological readiness.

Using a Monte Carlo simulation, the student developed the heuristic to select probability distributions (Gaussian, female, and uniform) based on a low number of observations, available from the literature, for each technological trajectory.

The innovation in Lana Khalifa's project is in the development of the innovative methodology using LCA data, the ability to develop a significant probability model based on a low number of observations and obtain results guiding decision makers in public policy to reduce climate change.

Acrobat PDF document Probabilistic life cycle model using Matlab

Acrobat PDF document Committee announcement (Hebrew)