Dr. Nick Duffield, Director of the Texas A&M Institute of Data Science (TAMIDS), is excited to announce the inaugural awardees of the TAMIDS Data Resource Development Program.
Programs Goals and Award Criteria
The TAMIDS Data Resource Development Program supports work that will enable, promote and increase the usage of data resources and tools that can exploit them for research at Texas A&M. Criteria for the awards included: enabling usage of new data resources; enabling usage of data resources by new users; connecting researchers, practitioners and data providers and/or users in multiple disciplines(s); involving of other researchers in project planning and definition; demonstrating new use cases and applications that would be enabled by project; prior demonstration of community interest in project and potential to increase competitiveness for external funding. The further criterion of responsiveness to the COVID-19 health crisis was added after the announcement of the program.
2020 Awardees
Awards were determined by a committee of experts convened by TAMIDS. This was no easy task, due to extraordinarily high quality of all of the submission. The 2020 Awardees are drawn from different disciplines across campus, with PIs and Co-PIs and collaborators in the Colleges of Architecture, Engineering, Veterinary Medicine, and Geosciences , and the School of Public Health.
Congratulations to the awardees:
- Raymundo Arroyave (PI), Department of Materials Science & Engineering, Development of a Software Platform For Accelerated Microstructure Design: From Data Generation to Curation and Analysis.
- Amir Behzadan (PI), Department of Construction Science, Theodora Chaspari (Co-PI), Department of Computer Science and Engineering, Preeti Zanwar (Collaborator): Department of Epidemiology & Biostatistics, CoFABS-Q: A dataset of face, body and speech cues in web-mined COVID-19 conversational vlogs.
- James Cai (PI), Department of Veterinary Integrative Biosciences, Enabling Single-Cell Data Resource to TAMU Investigators in Interdisciplinary Research.
- Xia Ben Hu (PI), Department of Computer Science and Engineering, AutoAD: Exploiting Automated Machine Learning for Anomaly Detection.
- Zhe Zhang (PI), Department of Geography, A Spatial Decision Support System for Cardiovascular Disease Risk Assessment in Response to the COVID-19 Crisis.
- Lei Zou (PI), Department of Geography, Jian Tao (Co-PI), Texas A&M Engineering Experiment Station, Ali Mostafavi (Co-PI), Departmental of Civil and Environmental Engineering, Tracking Social and Governmental Responses to Covid-19 Using Geospatial Big Data.
TAMIDS is looking forward to contributing to the success of these projects and the interdisciplinary impact of Data Science at Texas A&M University. TAMIDS Director Dr. Nick Duffield will work with the supported investigators to strengthen Data Science community in Texas A&M through these projects.