Hao Zhang - US grants

Ghosh
0703392

This CSUMS project, NCSU CUSP, prepares students to engage
in a significant research experience, and to be fluent in the
languages of computing, mathematics, and statistics. The
investigator and his colleagues provide inquiry-guided learning
to train undergraduates in exciting new approaches to problems
involving massive datasets or computationally intensive methods.
The program couples extensive coursework in computing for
contemporary statistical analysis with a practicum and research
lab focusing on an area of application such as drug discovery,
pattern recognition, statistical genetics, data assimilation, or
financial risk. The practicum and lab provide scientific
background, an overview of statistical and computational
approaches, training and feedback on teamwork and communication
skills, and a significant mentored research experience. Faculty
members from interdisciplinary teams conducting research in the
areas of data mining, geophysical and environmental data
assimilation, statistical genetics and bioinformatics, Bayesian
hierarchical modeling, financial risk modeling and time series
analysis serve as NCSU CUSP mentors and as co-mentors for
students from neighboring Meredith College. The NCSU CUSP meets
four specific objectives. It (1) prepares students to take
advantage of computing advances and make sophisticated computing
an integral part of the statistical and mathematical methodology
curriculum and research experience; (2) improves students'
non-technical skills, including public speaking and written
communication, working in teams, and ethical reasoning, (3)
provides the research experience to apply initiative and
creativity in developing statistical and computing approaches to
interdisciplinary scientific problems; and (4) prepares and
motivates a diverse pool of highly qualified students to pursue
interdisciplinary graduate studies in the mathematical and
computational sciences.

Aided by rapid advances in technology, massive amounts of
new data are generated daily in many scientific disciplines and
the volumes are growing at a rate unprecedented in human history.
For the US to remain competitive and innovative, a diverse pool
of researchers trained in novel and powerful techniques is
critically needed to illustrate, model, and analyze these
large-sized, high-dimensional, and nonlinearly-structured data.
Building on resources of one of the country's largest statistics
departments, NCSU CUSP becomes one of the first computationally
intensive statistics programs for undergraduates in the nation.
This project leads to development of new computationally
intensive courses and interdisciplinary courses, which will have
a long term impact. The project is also committed at the outset
to increasing diversity in the emerging field of computational
statistics. NCSU CUSP increases awareness of statistical science
among mathematics majors and faculty, fosters greater
collaboration between interdisciplinary programs, and encourages
a diverse pool of well-prepared students to pursue graduate
studies in quantitative sciences. Training in communication
skills helps develop graduates who can bring scientific research
results to the public and policy makers. NCSU CUSP methods and
results are widely publicized to the mathematical science and
computational communities through regional and national
conferences, participation in workshops, a CUSP website, and
published articles. The project is supported by the MPS Division
of Mathematical Sciences, the MPS Office of Multidisciplinary
Activities, and the EHR Division of Undergraduate Education.

The global community is increasingly exploring underground environments for sustainable and resilient solutions to societal problems. New opportunities and challenges in water access, quality, and storage, geothermal energy, and carbon sequestration collectively point to underground environments as the next frontier. Underground environments are, however, notoriously hazardous for humans; accordingly, inspecting underground environments and performing rescues during underground catastrophes is essential to achieve this new underground frontier. The proposed infrastructure will support research in human-robot teaming, networking, planning, and human-robot interaction, as well as collaborative research with other researchers in other fields and application-driven research into underground information collection, monitoring, surveying, rescue, and crisis management. The proposed infrastructure will also be used for community outreach programs, through workshops, presentations, and partnerships with area K-12 after-school programs.

The proposed infrastructure will provide a team of heterogeneous robots for deployment in underground environments, as well as sensors, networking equipment, and augmented reality headsets to facilitate their effective use. This infrastructure will support the institutional theme of research on underground environments, including underground inspection and search and rescue applications. This infrastructure will include amphibious, ground, and aerial robots; robotic arms and grippers to be mounted on ground robots; augmented reality headsets designed for safety-critical domains; visual, range, and audio sensors; and networking equipment. These hardware elements will be integrated together and deployed within the Edgar Mine, an underground research and evaluation facility owned and operated by the Colorado School of Mines.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.