Patrick J. Rosopa - US grants

The ADVANCE program is designed to foster gender equity through a focus on the identification and elimination of organizational barriers that impede the full participation and advancement of women faculty in academic institutions. Organizational barriers that inhibit equity may exist in areas such as policy, practice, culture, and organizational climate. The ADVANCE Institutional Transformation (ADVANCE-IT) track supports the development of innovative organizational change strategies within an institution of higher education to enhance gender equity in the science, technology, engineering, and math (STEM) disciplines.

Clemson University will implement TIGERS ADVANCE (Transforming the Institution through Gender Equity, Retention, and Support): a set of policy changes, procedural innovations, and institutional programs to improve the representation and status of women in STEM at Clemson. TIGERS ADVANCE has five goals: (a) transform the culture and improve the campus climate, (b) increase the representation of women in STEM disciplines, (c) ensure equitable workload distribution, (d) enhance faculty mentoring and leadership development, and (e) implement family-friendly policies. The social science research project embedded in the project will focus on chairs' decision making related to service assignments and workload among faculty.

Clemson University's ADVANCE-IT project is grounded in organizational identity theory. This is an innovative approach that envisions fostering individual identification with the university by creating the conditions for fair treatment of and improved institutional support for all faculty. Clemson is the leading STEM education institution in South Carolina, and will work through a regional network of institutions of higher education to communicate findings, provide policy recommendations, and share best practices to ensure recruitment, advancement, and retention of STEM women faculty.

The ultimate goal of this EArly-concept Grant for Exploratory Research (EAGER) project is to develop a crossdomain multiscale network and interdependent critical infrastructure (ICI) generator that captures many features of real networks and incorporates an arbitrarily large or small degree of stochasticity. Starting from samples of known or hypothesized networks, the generator will synthesize ensembles of networks and ICIs that will preserve, on average, a diverse set of topological and physical design properties at multiple scales of its structure. These properties will include several measures of centrality, assortativity, path lengths, clustering, flows, required physical capacities, and modularity. This approach introduces an unbiased variability across the ensemble in many of these properties at multiple scales which creates a desired realism of the synthesized system. The models will include human factor components incorporated in both topological and physical designs. A toolbox of algorithms and heuristics for generating synthetic networks of infrastructures and ICIs will be developed, and generated benchmarks will be disseminated.

Outcomes of this work will facilitate such tasks as simulation, policy testing and decision making for ICIs enabled by fundamental advancement in network generation algorithms. The toolbox will be designed using a modular approach that will allow it to evolve and to be applied in other domains. The interdisciplinary team of investigators comprising expertise in computer science, behavioral science, civil engineering, and network science and public health will ideally support the goal of realistic synthetic data generation. Perspectives and methodological approaches from network analysis, big data systems, machine learning, water networks, and organizational sciences will be brought to bear to develop a toolkit of methods that include a combination of network analytics, optimization, and statistical analysis techniques. The resulting products will include developed algorithms and generated synthetic datasets disseminated for a broad scientific community.