The Nano | Human Interfaces Initiative revolutionizes the way in which research is conceptualized and accomplished by building a highly-impactful and highly-visible technical infrastructure leveraging Lehigh's intrinsic strengths in nanoscale interfacial science and materials characterization with Lehigh’s emerging strengths in data analytics, bioengineering, health, educational innovation, and health.
From the start of the Initiative, the interdisciplinary NHI research team has realized that there is a growing need to integrate social sciences and engineering in order to better educate the future workforce and provide future makers with the necessary tools to accelerate scientific discovery.
As an example, a research domain that is deeply embedded in Lehigh’s research culture is the use of advanced characterization tools to examine nanoscale material interfaces. While many technological advances have improved the capabilities of scientific tools (e.g. faster computers being integrated into electron microscopes), there has been a surprising lack in effort to improve the human relationship with machines, otherwise known as human-machine interfaces. In many ways, humans interact with electron microscopes the same way today that humans interacted with electron microscopes since they were invented nearly 80 years ago. Similar examples can also be found in other disciplines. Therefore, if the arguably decelerating trajectory of scientific progress is to be disrupted, there is a need to fundamentally change how humans interact with scientific instrumentation by creating more experiential research inquiries through technologically-enhanced interfaces to accelerate discovery.
That is our goal - through interdisciplinary research we strive to transform the human-machine relationship with scientific tools and accelerate scientific discovery by re-imagining and developing Nano | Human Interfaces.
Our collective idea is to integrate the latest advancements in data science, materials engineering, bioengineering, psychology, and human learning science to develop a whole new approach in how human beings experience, harness, visualize, and analyze massive amounts with high-throughput instruments.