Computational Sustainability- How to Solve Environment Management Challenges Using AI
Ednali Zehavi
Obtaining data and creating prediction models are integral parts of environmental management. An environmental scientist collects and analyzes samples and then creates prediction models and mitigation programs as part of regulatory and best practice requirements. Applying machine learning algorithms results in improved prediction models without the constraints and restrictive assumptions that are typical for a traditional (deterministic and stochastic) approach.
This talk will give an overview of several research projects that used machine learning (which is a part of AI) to solve environmental management challenges related to mining. We will discuss the differences between machine learning and traditional approaches and how the two methods can work together. We will highlight myths of Big Data and will discuss how we can create algorithms to support the modelling with machine learning.
Ednali is Senior Advisor of business development for the environment division at Saskatchewan Research Council (SRC). Her academic background is in the areas of economics, decision making, computational statistics and data analysis, medicine, agriculture economics, environment and sustainability from universities in Israel, Italy and Canada. She has more than 15 years of experience in the areas of strategic planning, management, financing and business development in environmental, mining, research and consulting sectors.
Facilities for this event have kindly been provided by Saskatchewan Research Council. The event will be available via teleconference as well.
Join us for an hour of networking, socializing, and learning something new!