Summary
Artificial Intelligence (AI) and machine learning are terms referring to the ability for trained software to carry out “intelligent” analytical and creative tasks usually reserved for humans. AI is rapidly evolving and changing the workspace for many technical and writing/visualization fields. Participants in this training will learn about both the generative (creative) and analytical types of AI tools. They will be exposed to examples of tools appropriate for specific needs. They will be able to ask questions about AI from experts in the field, helping them to make decisions about where and whether these tools are appropriate.
Organizer and moderator
Fraser Shilling, PhD is lead organizer for ICOET and director of the Road Ecology Center at UC Davis. Since 2017, he has been using and supervising development of analytical AI tools for wildlife image processing (ecology and driver warning) and for crash analysis. He will introduce the training and be the primary contact for participants in the training.
Trainer 1
Gopi Prashanth is a vice-president in charge of AI at Salesforce, the largest enterprise-application company in the world, with >72,000 employees. He has extensive experience as a developer, supervisor and user of AI applications. For 10 years, he was director of Amazon’s AI-based tool development, supervising engineers developing the various “Go” and other technologies from Amazon.
He will provide an overview of how AI works and the ecosystem of AI tools that transportation and ecology scientists can use for creative and analytical jobs.
Trainer 2
Roland Dijkhuizen is a research scientist at Arcadis Nederland B.V. He has over 10 years experience with image analysis and 3 years working with AI tools for pattern analysis. Arcadis is one of the few consultant firms offering AI analytical services.
He will provide an overview of a specific type of analysis using AI: land use and land cover prediction and classification. He will use examples of mixed land-use/cover analysis from the Netherlands, including agricultural, wetland and aquatic areas.