2023 DSI Seed Grant Awardees
We're excited to share the news of our recent Seed Grant and Graduate Assistantship Awards, reflecting the collaborative spirit within the Data Science Initiative.
Join us in congratulating the following individuals whose outstanding contributions span diverse colleges and programs:
Chang Ge
Privacy-Preserving Data Publishing using Large Language Models
College of Science and Engineering, Computer Science and Engineering
Ruihang Zhang, Kun Zhang
Prediction of Wall Shear Stress in Open Cavity Models: An Integrated Study using CFD models and Data-Driven Sparse Sensing
College of Science and Engineering, Civil Engineering
College of Science and Engineering, Mechanical Engineering
Lance Augustin
CITE-seq Analysis of Bacterially Delivered Anticancer Immunotherapy
UMN Medical School, Surgery
Rick Jansen, Christy Henzler, Natalia Calixto Mancipe
Identifying Gene Interacting Networks in PDAC Using Deconvolution and Integrative Multi-omics Analysis
Clinical and Translational Science Institute
Minnesota Supercomputing Institute
Emil Lou
Defining Patterns of Spatial Genomic Changes in Clinical Specimens Before and After Cancer Treatment
UMN Medical School, Hematology, Oncology, and Transplantation
Erich Kummerfeld, Michael Bronstein, Alexander Rothman
Experimentally Dissecting Inter-analyst Reliability in Data Science: the Roles of Vague Questions and Imprecise Interpretations
Institute for Health Informatics,
UMN Medical School, Psychiatry and Behavioral Sciences
College of Liberal Arts, Psychology
Yulong Lu
Towards Robust Deep Learning Methods for Multiscale Simulation in Heterogeneous Materials
College of Science and Engineering, Mathematics
Jue Hou, Ju Sun, Margy McCullough-Hicks, Christopher Streib, Rui Zhang
Data Science Methods to Enable Real-world Evidence for Supporting Stroke Care (DRESS)
School of Public Health, Biostatistics and Health Data Science
College of Science and Engineering,
UMN Medical School, Neurology, Computational Health Sciences
Harrison Quick
Creating a Synthetic Vital Statistics Data Repository for Minnesota
School of Public Health, Biostatistics and Health Data Science
Ardeshir Ebtehaj, Michael Steinbach
Advancing Data Science Foundation for Shrinking the Uncertainties in Bottom-up Estimates of Methane Emission from Arctic Lakes
College of Science and Engineering, Civil, Environmental, and Geo-Engineering, Computer Science and Engineering
Rajesh Rajamani, Robert McGovern
Home-Based Individualized Analysis of Postural Instability in PD Patients
College of Science and Engineering, Mechanical Engineering
UMN Medical School, Neurosurgery
Chad Myers
Multi-task deep learning models for neurodegenerative disease risk prediction
College of Science and Engineering, Computer Science and Engineering
Cara Santelli, Tianhong Cui, Chang Ge, Yao-Yi Chiang
Prioritizing Tribal Data Benefits and Governance in Developing and Applying Chemical Sensors for Water Quality Monitoring
College of Science and Engineering, Earth and Environmental Sciences, Mechanical Engineering, Computer Science and Engineering
Lin Zhang, Joe Koopmeiners
Development of novel statistical imaging partitioning tools for interpretable lesion-wise cancer detection using 3D prostate imaging data
School of Public Health, Biostatistics and Health Data Science
Levi Teigen, Christopher Staley
Determination of Functional Drivers of Lewy Body Disease among the Intestinal Microbiota
CFANS, Food Science and Nutrition
UMN Medical School, Medical School
Stephen Guy, Rachel Hawe
Data-driven Metrics for Upper-Limb Motor Assessment in Children with Neurodevelopmental Disorders
College of Education and Human Development, Computer Science and Engineering, Biomechanics and Neuromotor Control
Zhang Rui, Steve Johnson, Anne Blaes
CancerLLM: Development of a Cancer-domain Large Language Model to Extract diagnostic information
UMN Medical School, Computational Health Sciences
Institute for Health Informatics, Oncology
Ju Sun, Zhaosong Lu
Stochastic Optimization for Constrained Deep Learning
College of Science and Engineering, Industrial and Systems Engineering
Steffen Ventz
Robust Bayesian Transfer learning
School of Public Health, Biostatistics and Health Data Science
We express gratitude for the diverse colleges and programs that participated in this joint effort, furthering the field of data science. The total amount awarded for this round is an impressive $972,058.00.
Congratulations to all the awardees, and best wishes to the applicants for the upcoming round!
Sincerely,
The Data Science Initiative
Explore a snapshot of the extensive research initiatives backed by our funding across diverse colleges and departments. Witness the collective brilliance that defines and energizes our dynamic data science community.
