Screenshot 2015-09-30 11.45.38

Invasion of the Built Environment by a Microbiologist 

Screenshot 2015-09-30 11.45.38So – I thought some people here would be interested in this.  As someone who has been involved in the Alfred P. Sloan Foundation’s program in “Microbiology of the Built Environment” for many years, I have been trying to get more involved with the built environment crowd.  And I have not always been exceptionally successful at this. But I keep trying.  I have been inspired by much of the work in this Sloan Foundation program that crossing over disciplinary boundaries is really important for this whole field.  Thus we keep up such efforts at microBEnet and I am always looking for new ways to cross over.  Again, I confess, I have not always been successful at this.

But I am pleased to announce that I am Co-PI on a new project at UC Davis. NSF Award Search: Award#1545193 – NRT-IGE: Data Science for the Built Environment.  This is a grant as part of the National Science Foundation’s Research Traineeship (NRT) program on Innovations in Graduate Education (IGE).  And the focus on this project is on training PhD students who are focusing on built environment work in data sciences.  And I am very happy that the other people on the grant (PI Deb Niemeier, CoPIs Duncan Lang, Megan Welsh and Nina Amenta) asked me if I would like to be involved.  The summary from the grant is below:

NRT-IGE: Data Science for the Built Environment

The availability of voluminous, high resolution data in both the spatial and temporal dimensions, coupled with increasingly fast, distributed computational resources offers enormous opportunities for tackling complex engineering and science challenges in urban settings. These data can also play an important role in interdisciplinary problem solving and have increasingly high value to multiple communities of scientists and engineers. However, research in the optimal instruction mechanisms to develop data science skills is still emerging. This is particularly true for engineering graduate students, who are a highly selected, technologically sophisticated population with the ability to quickly master material. This National Science Foundation Research Traineeship (NRT) award in the Innovations in Graduate Education (IGE) Track to the University of California-Davis will pilot, test, and compare modes of data science instruction. The testbed project will provide critical new information to inform the development of new learning platforms designed to cultivate robust computational, statistical, and data reasoning skills in engineering graduate students.

The project will implement a hybrid short-course approach that 1) bridges existing code camps and semester long classes, and 2) is coupled with a formal user group experience. A robust evaluation will be conducted to identify the individual effects of code camps, short courses, and users groups, as well as the effect of participating in combinations of experiences. In addition, learning gains, self-efficacy to engage in interdisciplinary studies that require data science principles, and career trajectories (including decisions to take additional coursework in data science and decisions to pursue interdisciplinary research and employment involving data science) will be examined. The project will generate new knowledge that addresses a particularly important gap in knowledge in terms of whether intense short-term learning experiences result in longer-term retention of skill development and computational reasoning. Findings on effectiveness of different modes of data science instruction in engineering will be broadly applicable to all data-enabled science and engineering fields.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Innovations in Graduate Education Track is dedicated solely to piloting, testing, and evaluating novel, innovative, and potentially transformative approaches to graduate education.

Basically I am going to be the outlier.  The only person not in the College of Engineering on the project and the only biologist.  I am hoping to bring in some biology focused people into the training program and also to try to better link studies of the built environment, training for Engineering PhD students, and microbiology.  Stay tuned for more about this project.

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Jonathan Eisen

I am an evolutionary biologist and a Professor at U. C. Davis. My lab is in the UC Davis Genome Center and I hold appointments in the Department of Medical Microbiology and Immunology in the School of Medicine and the Department of Evolution and Ecology in the College of Biological Sciences. My research focuses on the origin of novelty (how new processes and functions originate). To study this I focus on sequencing and analyzing genomes of organisms, especially microbes and using phylogenomic analysis (see my lab site here which has more information on lab activities).  In addition to research, I am heavily involved in the Open Access publishing and Open Science movements.