2023 Graduate Assistantship Awardees
We are thrilled to announce the recipients of the 2023 Graduate Assistantship Awards, showcasing the innovative research supported by the Data Science Initiative.
Please join us in celebrating the achievements of the following individuals, whose remarkable contributions extend across various colleges and programs:
Claire Menard
Response of Crop Genomes to Environmental Stress
- School/Department: CFANS (College of Food, Agricultural and Natural Resource Sciences)
- Program: Agronomy and Plant Genetics, Plant and Microbial Biology
Evan Dastin-Van Rijn
Blackbox Optimization of Cognitive Control with Neuromodulation
- School/Department: CSE (College of Science and Engineering)
- Program: Biomedical Engineering
Drew Swartz
Effectiveness and Producers Perceptions of Camera-based Technology detecting early stages of lameness in dairy cows
- School/Department: College of Veterinary Medicine
- Program: Veterinary Population Medicine, Veterinary Medicine
Kate Dembny
Functional Connectivity as a Biomarker for Working Memory Dysfunction in Parkinson's Disease
- School/Department: CSE (College of Science and Engineering)
- Program: Biomedical Engineering
Jack Wolf
Innovative Statistical Methods for Personalized Treatment Decisions in Cancer Clinical Trials
- School/Department: School of Public Health, Division of Biostatistics
- Program: Biostatistics
Leikun Yin
Sustainable Cashew Plantation Expansion in West Africa: Balancing Industry Growth, Poverty Reduction, and Conservation using Deep Learning and Geospatial Data
- School/Department: CFANS (College of Food, Agricultural and Natural Resource Sciences)
- Program: Bioproducts and Biosystems Engineering, Bioproducts and Biosystems Science, Engineering and Management
Chris Wojan
Can biodiversity reduce Lyme disease prevalence? A data-driven approach
- School/Department: College of Biological Sciences
- Program: Ecology, Evolution, and Behavior
Mathew Fischbach
Enhancing Parkinson’s Disease risk prediction with genetic interaction-based machine learning models
- School/Department: CSE (College of Science and Engineering)
- Program: Computer Science and Engineering, Bioinformatics and Computational Biology
Jiacheng Liu
Identify potentially avoidable blood draws via estimating coagulation measurements for pediatric patients treated by heparin infusion
- School/Department: CSE (College of Science and Engineering)
- Program: Computer Science and Engineering
Jingxuan Deng
Optimizing Mineral Carbon Storage through High-performance Computing and Machine Learning
- School/Department: CSE (College of Science and Engineering)
- Program: Department of Earth and Environmental Sciences, Earth Sciences
Xiangyu Zhang
Searching for new signals under high background: a novel inferential framework
- School/Department: CLA (College of Liberal Arts)
- Program: School of Statistics
Cooper Gray
Novel Insights into CSF Flow Alterations to Inform Future Treatment of Neurodegenerative Diseases
- School/Department: CSE (College of Science and Engineering)
- Program: Mechanical Engineering
Seiya Wakahara
Precision Nitrogen and Irrigation Management of Potatoes based on Multi-source Data Fusion using Machine Learning and Crop Growth Modeling
- School/Department: CFANS (College of Food, Agricultural and Natural Resource Sciences)
- Program: Soil, Water, and Climate, Land and Atmospheric Science
Haoyu Yang
Personalized Disease Progression Modeling Using Privileged Information
- School/Department: CSE (College of Science and Engineering)
- Program: Computer Science and Engineering
The total amount awarded for this round is an impressive $678,864.83. Congratulations to all the awardees! The next round of applications will be in Oct. 2024.
Sincerely,
The Data Science Initiative
