August 4, 2005
Preparing Statistics Ph.D.’s for a Multidisciplinary Research Career
Alicia Carriquiry
Department of Statistics,
Alicia@iastate.edu
Problems arising in most scientific fields today are complex and best addressed by teams of researchers from two or more disciplines. Unprecedented advances in measurement technologies result in massive datasets, and at the same time, uncertainties and sources of variation in the data are increasingly complex. Yet statistics doctoral students are rarely active participants in cross-disciplinary teams. Thus, inclusion of an experiential research component (involving serious participation in a multidisciplinary research group working on a substantive problem) is an important potential improvement to graduate education in our discipline.
This kind of experiential research component is the cornerstone of a new National Science Foundation (NSF)-sponsored Research Training Group (RTG) in Statistics for the Physical and Engineering Sciences that will begin operating in the Department of Statistics at Iowa State University (ISU) in the fall of 2005. The project has received NSF funding for an initial duration of four years. The objective of the program is to provide early experiential research and learning opportunities for the next generation of statisticians in the physical and engineering sciences.
The Department of Statistics at ISU will interact with initial partners Los Alamos National Laboratory, Lucent Technologies, and the National Institute of Standards and Technology. In addition, several physical and engineering sciences research groups within ISU have also agreed to be RTG partners. As part of their doctoral work, students will be encouraged to spend from a few months to a year at one of the partner sites collaborating on a real problem.
This focus on the physical and engineering sciences is natural for Statistics at ISU because the department has a large number of nationally recognized faculty members who work in that area. Furthermore:
· The challenges posed by problems in the physical and engineering sciences today require the participation of statisticians who not only are experts in existing sophisticated statistical theory and methodology but also have the background needed to lead the development of new tools.
· Physical and engineering sciences problems arise in many newly important homeland security contexts in addition to more well-established research and development activities in industry and government.
·
The
development of cutting-edge technology is fundamental to
· As the outstanding list of partner laboratories indicates, there is strong external interest in collaborating with an established group of statisticians working on physical and engineering sciences problems. This type of partnership has the potential to significantly increase the pace and quality of research in the focus area.
However, such an approach can be implemented in areas other than the physical and engineering sciences. We hope that the information in this article will be of use to other departments thinking about implementing innovations of this kind.
Getting started
The NSF RTG program is one of the building blocks of the broader Enhancing the Mathematical Sciences Workforce in the 21st Century (EMSW21) at NSF. The overall goal of EMSW21 is to increase the number of US citizens, nationals, and permanent residents who are trained in the mathematical sciences and who then pursue research careers in the mathematical sciences or in other disciplines supported by NSF. While student and post-doc participants must be US citizens, nationals, or permanent residents, no such restrictions apply to the principal investigators.
A group of nine faculty members in the Department of Statistics at ISU collaborated on the design of the RTG in the Department, and will participate in the research and training activities to be carried out under the grant. We fully anticipate much broader faculty participation once the program is up and running. In the past, RTG grants have been made mostly to research groups in pure and applied mathematics. Our success suggests that there is a great opportunity for attractive proposals from Statistics departments to receive funding.
What do we hope to accomplish at ISU?
While NSF RTG funding is restricted to US citizens, nationals, or permanent residents, funds from other sources can be used to attract a broader group of talented students to the program. We hope to:
·
Attract
a larger number of outstanding students (particularly
· Provide enhanced research and mentoring opportunities for doctoral students interested in statistics and its applications in the physical and engineering sciences.
· Build an even more cohesive, focused research group of faculty, post-docs, and graduate students in the department, with the resources and the time to actively collaborate with scientists at partner laboratories on problems of mutual interest.
· Establish long-term collaborations with scientists in government agencies and industry who are “problem owners” and can provide access to and understanding of real-world, complex problems and data for students and faculty in the department.
· Focus research efforts on challenging, multi-disciplinary research problems of national importance with partners from industry and government.
· Enhance the level of statistical training and understanding of collaborating researchers and graduate students, and thus help to raise the level of statistical sophistication they can bring to their professions “from within.” At the same time, we will enhance the scientific understanding and sophistication of statistics faculty, thereby preparing faculty to more effectively mentor doctoral students with an interest in interdisciplinary research.
How will the RTG function?
The RTG will have student, faculty, and partner scientist members. A student who is accepted into the program can expect to spend his or her first two years at ISU taking courses and passing the written portion of the doctoral preliminary examination. At the beginning of the third year, the student would select a general research area and a partner site either off or on campus. With guidance from his or her major professor and local mentoring at the partner site, the student will then begin learning about a real problem in his or her general research area. During this on-site period, the student will closely collaborate with partner scientists, will learn about the subject matter problem, and will get invaluable experience. The student’s major professor will actively participate in the research problem as well, and will travel periodically to the partner site. By providing office space and access to computing facilities, state-of-the-art scientific facilities, proprietary data, and scientists who understand the context and quality of those data, the partner laboratories will be an integral component of the program.
In addition
to actively participating in the research to be carried out at the partner
laboratories, faculty will develop new graduate-level courses in novel areas
such as metrology, and monitoring for dynamic wireless networks. At
The next steps
The success of the RTG program depends heavily on the quality of the students that can be recruited into the program. We are now in the process of advertising the new NSF-RTG fellowships and hope to attract a group of outstanding candidates from the mathematical, physical, and engineering sciences. As part of this effort, we hope to expand the number of students who wish to pursue a joint Ph.D. degree in Statistics and some areas in the physical and engineering sciences. To accomplish that goal, we have extended our Ph.D. degree offerings to include a joint degree where a student must satisfy the doctoral requirements in statistical theory (but only the M.S.-level requirements in statistical methods) while also satisfying a reduced set of doctoral course requirements in the area of application.
The goals of this project are consistent with the goals of the Statistics Partnership among Academe, Industry and Government (SPAIG), an ASA committee that encourages collaboration between scientists in universities, industry and government. We hope that more departments can find ways to use funding from business, industry and government agencies to create such partnerships while at the same time extending the frontiers of research, learning and teaching in statistics.
Please contact us!
If you wish to learn more about this new initiative, please feel free to contact any of the participating faculty in the RTG. These include (in alphabetical order): Alicia Carriquiry (alicia@iastate.edu), Song Xi Chen (songchen@iastate.edu), Heike Hoffman (hoffman@iastate.edu), Ranjan Maitra (maitra@iastate.edu), Bill Meeker (wqmeeker@iastate.edu), Max Morris (mmorris@iastate.edu), Derrick Rollins (drollins@iastate.edu), Steve Vardeman (vardeman@iastate.edu) and Huaiqing Wu (isuhwu@iastate.edu). New departmental faculty including Karen Kafadar and Arka Ghosh will contribute additional expertise to this initiative. Otherwise, please visit our web site at http://www.stat.iastate.edu/.