Generative AI Theme: The Era of Ai Shaping Us

Pavlo Yalovol is a forward-thinking executive with over two decades of expertise in automotive and geospatial technologies. His robust portfolio of designed and completed projects showcases Pavlo's ability to translate complex technological challenges into tangible business solutions.

As the Vice President of Innovation, he leads initiatives to integrate AI/ML power into Intetics clients' products, contribute to the design and implementation of geospatial solutions, and drive substantial process improvements within the company.

Siqin (Sisi) Wang, Ph.D., is an Associate Professor (Teaching) of Spatial Sciences with the Spatial Sciences Institute in the Dornsife College of Letters, Arts and Sciences at the University of Southern California. Dr. Wang's research interests are in GIScience, spatiotemporal big data analytics, computational social science, digital health geography, human-centered GeoAI, human mobility and migration, smart cities and human-climate interactions and she has published extensively in these areas. Her co-first author 2021 paper on human mobility and COVID-19 transmission received the 2022 Best Paper Award and Most Downloaded Paper from the Annals of GIS in 2023.

Her professional roles include service as the Associated Chair for the Spatial Data Lab affiliated with Harvard University and as Vice Chair of the Young Scientist Innovation Network for Digital Earth of the International Society for Digital Earth.

Prior to joining the USC Spatial Sciences Institute, Dr. Wang was an Adjunct Senior Lecturer at the Royal Melbourne Institute of Technology, Australia, and an Honorary Lecturer/Research Fellow with the University of Queensland, Australia. From April 2022 to July 2023, she also was a JSPS Research Fellow with the University of Tokyo, Japan, researching healthcare access and social vulnerability in the post-COVID Japan.

Doyi advances disaster management through satellite imagery and AI. Her expertise includes deploying deep learning techniques like video prediction, generation models, and weather observation datasets to enhance nowcasting skills for heavy precipitation events. Her work ensures swift processing of vast data, facilitating rapid weather predictions. Doyi has earned first prize in the GeoNet challenge at ICCV23 and a special prize in the Weather4cast challenge at NeurIPS22, showcasing domain adaptation, robust learning across geographies in computer vision, and rainfall prediction.