2019 Summer Research Projects will appear soon.
The Center for Data Science (CDS) and the Moore-Sloan Data Science Environment (MSDSE) have developed a summer research initiative to introduce MS in Data Science students to research projects around New York University. These research initiatives will help integrate the students into research and also help applied researchers around NYU to complete their projects. The MSDSE has funds to fully support some summer research associates for approximately 250 hours of (free to the relevant research unit) time. Those funds will be allocated on a competitive basis, but the initiative itself is open to all.
To help students connect with researchers, CDS and MSDSE will hold a research project fair at the end of February 2018. During this fair, invited researchers will have the opportunity to meet and talk to students interested in working on open projects. We are especially keen to hear from colleagues in the natural, physical and medical sciences.
CDS is a world-class institute for Data Science research, and its students are diligent, highly skilled and keen to work on ‘real’ research projects wherever they exist in the university. They have been trained in graduate level probability, statistics, machine learning, big data, and inference. Their specific domain knowledge varies from case-to-case but covers natural science, social science, computer science, mathematics, and cognate disciplines.
2018 Summer Research Projects Selected for Funding
- Cem Diaz, “Deep Learning-based Imaging Biomarkers for Knee Osteoarthritis”
- Krzysztof Geras, “Breast Cancer Screening with Deep Neural Networks Tracking Cancer Progression”
- Anna Harvey, “Predicting Risks to Officer Safety/Identifying Human Trafficking Victims”
- Carol Huang, “Towards a base-resolution, quantitative model of genetic and epigenetic effects on protein-DNA interaction”
- Anli Liu, “Optimization of Responsive Neurostimulation (RNS) Therapy Through Data Mining Approaches”
- Yvonne Lui, “Diffusion MRI and Working Memory”
- Narges Razavian, “Deep Learning for Segmentation of Brain MRI images”
- Heidi Schambra, “Quantifying Rehabilitation Training After Stroke”