Saturday, October 7, 2023
Eric P. Newman Education Center (EPNEC), Medical School Campus
Delving into the dynamic and ever-evolving realm of technological innovation, we gather to immerse ourselves in the exciting possibilities and transformative power that digital technologies hold for shaping our world. From the rapid advancements in artificial intelligence and big data analytics to the growing influence of the Internet of Things and blockchain technology, this session offers a unique opportunity to explore the far-reaching implications of digital transformation across industries, societies, and individuals. We will uncover the ways in which digital innovation is reshaping the way we live, work, communicate, and interact, and discuss the potential challenges and opportunities that lie ahead.
| Plenary Session | Digital Transformation | Location |
|---|---|---|
| 10:30 – 11:00am | Break | EPNEC Foyer |
| 11:00- 12:40pm | MODERATOR Randi Foraker, School of Medicine Washington University in St. Louis RESEARCH PROJECT PRESENTATIONS (11:00 – 12:05) Integrated machine learning and point-of-care technology to craft social policy that reduces viral spread during pandemics Guy Genin, Washington University in St. Louis Changqing Chen, Tsinghua University Learning global climate systems using computational topology Jr-Shin Li, Washington University in St. Louis Chia-Cheng Wei and Shao-Yiu Hsu, National Taiwan University Understanding and accounting for human behavior and beliefs in human-AI collaboration William Yeoh, Washington University in St. Louis Sarah Keren, Technion – Israel Institute of Technology PANEL DISCUSSION and AUDIENCE Q&A (12:05 – 12:40) | EPNEC Auditorium |
| 12:40-12:45pm | Closing Remarks Laura Benoist, Director, McDonnell International Scholars Academy | EPNEC Auditorium |
| 12:45 – 2:00pm | Luncheon | EPNEC Greatrooms A&B and Foyer |
Global Research Symposium Workshops: Digital Transformation
Please check back often for updates to available workshops and registration.
The faculty-driven workshops at our symposium offer a unique opportunity for participants to dive deep into specialized topics, guided by renowned experts in their respective fields. These workshops are designed to foster interactive learning, facilitate skill development, and encourage meaningful dialogue among attendees. Join us as we embark on an enriching journey of discovery and growth through our faculty-driven workshops.
Saturday, October 7, 2023 | 2:00 – 4:00 PM
All workshops will be hosted at the Eric P. Newman Education Center (EPNEC) at Washington University School of Medicine.
Led by: Professor Jr-Shin Li, Washington University in St. Louis
Professor Chia-Cheng Hsu and Professor Shao-Yiu Hsu, National Taiwan University
Notions and tools of topology and topological data science have been widely adopted and applied in diverse areas from physics and biology to computer science, while remaining remote to health and environmental science and engineering. For example, connectedness is an essential characteristic of climate, hydrology, and ecology systems. However, this fundamental property in topology is often overlooked in systems analysis in these domains. In this workshop, we will discuss the role of topology plays in systems analysis for public health, population science, and environmental engineering. The focus will be placed on offering the background, motivation, applications, and state-of-the-art results on utilizing topological techniques and topological data science for analyzing large-scale, high-dimensional complex systems and their big data. This research symposium aims to create a dialog between applied mathematicians, data scientists, health economists, population scientists, and environmental engineers to share knowledge and identify challenges from an interdisciplinary point of view. The overall objective is to brainstorm and exchange ideas to make innovative and effective methods for systems analysis and data analytics using topological properties, and to enhance the capability of understanding complex systems at large for optimal decision making.