Machine Learning in Image Generation and Analysis: Forestry, Medicine and Visual Arts

We are joined by three experts from different disciplines to learn about updates on how machine learning has changed what is valuable expertise in image analysis and generation in their respective fields.  The evening will start with small, focused lectures from our guests followed by a moderated panel discussion of themes that cut across disciplines and how best to adapt to the evolving capabilities of AI in career planning and for life-long learning.    

Steve DiPaola is a pioneer in AI based computational creativity exploring the marriage of cognitive science and artificial intelligence-based modelling.  He looks at how they can be modelled in computational/cognitive modelling with applications in science, e-health, education, and the arts. Steve directs the I-Viz Lab (~10 computer-based PhDs, Postdocs, Grads – 72% women) which uses cognitive-based Artificial Intelligence and Virtual Reality techniques and computational modeling. He parallels a professional art career.  His expertise conjoins neuroscience, artificial intelligence with human mechanisms of creativity, expression, and empathy. As Past Director of the Cognitive Science program and a invited member of Royal Society of Canada, Steve and his lab build foundational cognitive theories on how humans are creative, how they express, have empathy, creating new forms of computational, social, and artistic artifacts. His fine artwork has been exhibited at major museums including the MOMA, Tate and Whitney museums. As a cognitive based AI scientist, he has over 100 scientific papers including his AI systems that emulate fully talking, perceiving, empathetic 3D chatbot characters.

Paul Pickell is an Assistant Professor of Teaching in the Faculty of Forestry at the University of British Columbia where he primarily teaches geographic information systems (GIS) and remote sensing across multiple professional graduate programs. Paul is also a Faculty in Residence at the Emerging Media Lab, where he studies the use of immersive virtual reality and augmented reality in teaching. He is broadly interested in how technology impacts learning and specifically the development of spatial reasoning skills. Paul teaches computer vision applications with spatial data and use other tools such as UBC's augmented reality sandbox and video game engines in his teachings.

Roger Tam obtained his Ph.D. in computer science in 2004 from the University of British Columbia in the research areas of computational geometry, shape modelling and visualization. He joined the UBC Department of Radiology as a faculty member in 2007. In 2018, he became a founding member of the UBC School of Biomedical Engineering. His research interests centre on image analysis, machine learning and personalized medicine.

This Leading Scholars series brings together leading experts from diverse fields to explore the transformative potential of Artificial Intelligence (AI) in the context of education at UBC. Through a multidisciplinary lens, this series aims to delve into the promises and challenges that AI presents, beginning with an introduction to generative models for text and images. Then, through a series of panels, organizers will probe into the incorporation of AI in future workflow, on how recent generative models have changed the concept of lifelong learning, the impact of AI on our interactions with images across disciplines, and AI’s potential for language learning, revitalization and reclamation from an Indigenous perspective.

Series Conveners: Anwar Ahmed, Language and Literacy Education; Tamara Etmannski, Civil Engineering; Christopher Hammerly, Linguistics; Giulia Toti, Computer Science; Lily Wenya Zhou, Neurology; Ignacio Barbeito, Forest Resources Management; Katherine Wagner, Economics; Shoufu Yin, History; Thomas Pasquier, Computer Science