Juan J. de Pablo

Biosketch

As the Executive Vice President for Science, Innovation, National Laboratories, and Global Initiatives, Juan de Pablo helps drive and support the expanding reach of the University’s science, technology, and innovation efforts, along with their connection to policy and industry. He identifies and shapes emerging strategic scientific and technological initiatives, and provides oversight of entrepreneurship and innovation activities at the University’s Polsky Center for Entrepreneurship and Innovation. He also works with faculty, deans, and administrators to build global academic partnerships and international research collaborations while overseeing the University’s international centers. Juan de Pablo provides leadership for the University’s stewardship of two U.S. Department of Energy National Laboratories – Argonne and Fermilab – as institutions to advance science and technology in support of the nation’s interest. He collaborates with other leaders in research and innovation to build programs and links between and among the national laboratories and the University, as well as the Marine Biological Laboratory. A prominent materials scientist, de Pablo focuses his research on polymers, biological macromolecules such as proteins and DNA, glasses, and liquid crystals, a diverse class of materials widely used in many fields of engineering.

Research Interests

Juan de Pablo's research and scholarly interests are focused on macromolecular systems, including polymers, DNA and RNA, proteins, and liquid crystals. His work entails developing molecular and multi-scale models of materials, which are used to understand their function and to design new systems for specific applications. He has developed a broad range of theoretical and computational frameworks, as well as mathematical algorithms, that are widely used for the study of condensed matter. A cross-cutting and critical aspect of this work has been to establish well-defined connections between molecular characteristics and macroscopic behavior. In recent years, a growing emphasis has been to conceive new strategies for molecular and materials discovery that rely on emerging concepts from machine-learning and artificial intelligence, extensive experimental and computational data sets, and a combination of physics, chemistry, and engineering-based models. These strategies are have led to advances in a range of fields, such as drug development, epigenetics, defect control in advanced materials, and active matter, to name a few.