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.

Key Takeaways

Randi Foraker: When we think about the ‘digital transformation’, most people think about the technologies involved, but we really should be thinking about an overlapping Venn Diagram that includes the technologies, but also the processes we are using and the people involved.Guy Genin: The idea of what constitutes a computer is rapidly changing. Envision a future where everything around us is a computer. 
Jr-Shin Li: In many applications, topological properties matter, not the shapes. A topological data analysis approach can help in quantifying the impacts of climate change.William Yeoh: Optimizing AI performance alone without considering human counterparts is not adequate. To optimize the joint performance of human-AI teams, the AI agent must understand the behavior of its human teammate and make its behavior easily understandable to humans.
Digital Transformation

The Highlights

The final plenary, chaired by Professor Randi Foraker, director of the Center for Population Health Informatics at WashU, explored the dynamic realm of technological innovation and the exciting possibilities digital technologies hold for shaping our world. 

Guy Genin, Harold and Kathleen Faught Professor of Mechanical Engineering in the McKelvey School of Engineering, and Changqing Chen, head of the Department of Engineering Mechanics at Tsinghua University, have been working together to convert 3D-printed materials into fully functional computers. “An important part of the digital transformation is the transformation of what a computer is going to be,” said Genin. He invited the audience to envision a future where everything around us is a computer. Chen traced the role of materials as a prominent player throughout human history, from the stone age to the current AI age, posing the question whether information processing can become an inherent property of materials. Together, Genin and Chen are studying how mechanical metamaterials can be used to store and process information, with numerous potential applications.

Professors Chia-Cheng Wei and Shao-Yiu Hsu, both from National Taiwan University, joined Jr-Shin Li from the McKelvey School of Engineering, to present their seed grant-funded collaboration on “Learning global climate systems using computational topology.” Seed grant support allowed the team to pursue a “high-risk but very likely to be high-return project,” said Li. “Our ultimate goal is to learn global changes in climate systems using topological information inherent in big climate data.” As foundation of a large portion of modern mathematics, topology is concerned with the properties of a geometric object that are preserved under continuous deformation. The team discussed three topological properties—connectedness, dimension, and “hole” structure—and their various potential applications in analyzing global warming or the intensity of hurricanes. The team demonstrated the importance of topological tools and approaches in different domains, with examples from toxicology and geosciences, and at different scales—from 10-6m to 106m.

Professors William Yeoh and Chien-Ju Ho from the McKelvey School of Engineering and Sarah Keren from Technion – Israel Institute of Technology, have been working together to understand human-AI collaboration. Their overarching interest is in designing AI systems that can guide humans to make better decisions, particularly in cases where neither humans nor AI can solve a problem efficiently, and where it would make sense to combine the complementary strengths of both AI and humans. Yeoh explained that in disaster response situations, for example, AI robots have better sensors and better mobility than humans, but humans are nevertheless needed to make critical value judgment calls such as which search areas to prioritize. In the creative arts, AI systems may allow for greater creativity in generating unconventional designs for buildings, but human architects are still needed to ensure sound and feasible structures. The puzzle this team is trying to solve is how to make it easier for humans to figure out what the AI system is trying to do, how to account for human behavior so that AI can accurately infer what humans are trying to do, and how to jointly optimize who does what. The team has already made important contributions to the literature on goal recognition design, for example by looking into modifying the environment to remove possible actions. Their seed grant-funded project focuses on learning the expected average difficulty of a goal recognition problem, rather than assuming a worst-case measure for the problem’s difficulty. To do that, they are using data from a cooking simulation video game called “Overcooked.”

Saturday, October 7, 2023

Eric P. Newman Education Center (EPNEC), Medical School Campus

Plenary SessionDigital TransformationLocation
10:30 – 11:00amBreakEPNEC Foyer
11:00- 12:40pmMODERATOR
Randi Foraker, School of Medicine
Washington University in St. Louis


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

EPNEC Auditorium
12:40-12:45pmClosing Remarks
Laura Benoist, Director, McDonnell International Scholars Academy
EPNEC Auditorium
12:45 – 2:00pmLuncheonEPNEC 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 hosted at the Eric P. Newman Education Center (EPNEC) at Washington University School of Medicine.

Topological Data Science for Health and Environmental Systems Analysis

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.