2020 IDEaS Data Science Awards Announced

<p>Data points arranged into an award cup.</p>

Data points arranged into an award cup.

IDEaS recently awarded a series of grants to stimulate the research efforts of Georgia Tech’s brightest minds in data science and related disciplines. Faculty and student research programs targeted for IDEaS awards must demonstrate research goals that will be highly cross-disciplinary and emphasize how data science can assist in related research areas.

The Data Science Research Scholarships program will support scholarships for the Spring 2020 semester and focus on Ph.D. student research that enables new collaborative research or adds a data science dimension to established research projects. Each scholarship will fund 50% of the cost of a GRA appointment, with the project PI funding the remaining 50%. 

Data Science Research Scholarships 2020 Awards

  • JC Gumbart (Physics) & David Sherrill (Chemistry): Force-field Development to Enable Simulations of Xeno-nucleic Acids
  • Xiuwei Zhang (CSE) & Haesun Park (CSE): Development of an Integrative Clustering Method for Single Cells
  • Vince Calhoun (ECE) & Audrey Duarte (Psych): The Chronnectomics of Memory
  • Annalisa Bracco (EAS), Jie He (EAS) & Matt J. Kusner (University College London): Machine-learning Techniques for Cloud Modeling
  • Toyya Pujol-Mitchell (ISYE), Nicoleta Serban (ISyE) & Constantine Dovrolis (CS): Network Weight Prediction Using Node Attributes
  • Xiaofan Liang (City & Reg Planning), Clio Andris (City & Reg Planning) & Diyi Yang (IC): Advancing Metrics for Spatial Social Networks in the Era of Big Data
  • Omar Asensio (Public Policy): Do Micromobility Options Reduce Traffic Congestion? Quasi-experimental Evidence from Uber Movement Data
  • Constantine Dovrolis (CS) & Kelly F. Ethun (Emory/Yerkes): Connections Between Social Behavior and Food Intake in Rhesus Macaques
The Data Curation Awards for faculty support the acquisition or curation of datasets critical to inform all-discipline research projects and drive goal attainment. These grants support a variety of projects, including human annotation of unlabeled data, developing software for collecting data, and developing domain-relevant formats for storing data.
  • Diyi Yang (IC) & Mai ElSherief (IC): Defining, Characterizing, and Detecting Implicit Discriminatory Speech Online
  • Umakishore Ramachandran (CS) & Zhuangdi Xu (CS): Generating Labeled Vehicle Tracking Dataset for Large-scale Geo-Distributed Camera Networks
  • Surya R. Kalidindi (ME/CSE/MSE) & Christopher Saldana (ME): Advanced Materials-Manufacturing Data Curation
  • Agata Rozga (IC), Thomas Ploetz (IC) & external: Annotation of Datasets from Severe Behavior Treatment Program at the Marcus Autism Center
 
The Data Science Partnership Awards for faculty provide travel cost coverage for awardees who will visit companies, federal agencies, or government labs to initiate collaboration in data science foundations or data-driven discovery in any area. Funds may also be utilized to visit academic institutions that serve underrepresented groups, or for visits to non-research-intensive universities and colleges for broadening collaborative participation data science research.
 
Data Science Partnership 2020 Awards
  • Diyi Yang (IC): Allen Institute for AI and University of Washington
  • Josh Kacher (MSE): Lawrence Livermore National Laboratory
  • Rachel Cummings (ISyE): Georgetown University and U.S. Census Bureau
 
Data Science Speaker Travel Awards supports visits to the Georgia Tech campus by external experts in the areas of data science foundations or data-driven discovery in any discipline. Funds may be used to host a guest speaker for the IDEaS seminar series, or to participate in another on-campus event, conference, or seminar series. Awardees’ invited guests are experts in either mathematical data science or data science engineering. 
 
Data Science Speaker Travel 2020 Awards
  • Betsy DiSalvo (IC): Data Work Civic Engagement Panel
  • Diyi Yang (IC): Natural Language Processing/Computational Social Science Seminar