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2022-2023 Networking Groups

During 2022-2023, two data science research networking groups will meet in-person around the topics described below.

 

Design + Nature

Embodied in countless examples of materials, organisms, and systems, Nature has inspired humans for centuries with elegant design strategies for ensuring continuous survival, relentless blossoming, and sustained evolutionary fitness. This group will explore interdisciplinary strategies for designing with Nature in mind to futureproof our society and planet in the face of myriad global challenges. To this end, how do we better design for Nature? Can we design with, like, or beyond Nature to ensure a more prosperous, equitable, and sustainable future? This group will explore these questions through new materials, technologies, and perspectives, looking towards biomedicine, sustainability, robotics, the arts, computation, synthetic biology, the humanities, and more to see how to best design for future innovations. Bringing together scientists, artists, engineers, and philosophers/historians of science, this group will aim to provide a comprehensive outlook on these emerging opportunities. This group will be led by Ange-Therese Akono from Civil and Environmental Engineering and Ryan Truby from Materials Science and Engineering and Mechanical Engineering, both in the McCormick School of Engineering.

 

The Art, Engineering, and Science of Movement and Sports

From the clumsy explorations of a crawling baby to the unreal agility and beauty of a Serena Williams serve or a Cristiano Ronaldo bicycle kick, movement is a critical aspect of our humanity. The choreographed or improvised collective movements of dancers, athletes, hunters, and warriors has been critical to our survival. The beauty and elegance of the human body in motion has been captured in statues, drawings, paintings, and photographs both for aesthetic and scientific purposes. The inner workings of nerves, tendons, and muscles has fascinated both artists and scientists. More recently, the flow of data has spurred the development of “moneyball” approaches to the design of more objective evaluations of performance. This group will bring together Northwestern scholars who are at the forefront of art, engineering, and science to jointly explore this academically overlooked world of learning, beauty, and performance. The group will explore directions such as how a new generation of sensors can bring about new insights about individual and collective movement; how new machine learning approaches can open up new directions for the description and prediction of performance at the individual and collective levels; how biomechanical models may help predict performance limits or recovery strategies; and how nutrition impacts both short term and long-term health.