Summer Research Initiative
Summer Research Initiative
The Center for Data Science’s (CDS) summer research initiative, developed as a part of the Data Science and Software Services (DS3) initiative, aims to introduce MS in Data Science students to research projects around NYU. CDS MS students are among the top young data scientists in the country, and through this initiative, CDS connects its students with the wider university community and its various research avenues, at the same time providing researchers around campus with highly skilled students for data science projects in their fields.
The summer research initiative is open to all and we expect most NYU partners to have the funds to support student summer research. Unfortunately, at this time, funding through CDS will be very limited on a competitive basis.
To help students connect with researchers, CDS holds a research project fair in the spring. During this fair, invited researchers will have the opportunity to meet and talk to students interested in working on open projects.
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. To learn more about the MS in Data Science curriculum, please visit the MS Curriculum page. To learn more about this initiative, please reach out to cds-masters@nyu.edu.
2023 Summer Research Projects Selected for Funding
- Chenjuan Ma, “Neighborhood characteristics and home health care”
- Victoria Stanhope, “Harnessing Natural Language Processing to Measure Person-Centered Care in Behavioral Health Settings”
- Kalman Victor and Yaacov Trope, “Social networks and linguistic abstraction: How language affects the way messages travel online”
2022 Summer Research Projects Selected for Funding
- Emily Balcetis and Jennie Qu-Lee, “Developing pupillometry analysis tool for dynamic stimuli”
- Hilke Schellmann, “Investigating Dialects and Accents in Speech to Text Transcriptions for Hiring”
- Ben Schmidt, “Archive of Computer Advertising”
2021 Summer Research Projects Selected for Funding
- Gernot Wager, “Social Cost of Delaying Climate Policy”
- Alexander Kushnir, “Deep learning to improve atrial fibrillation outcomes”
- Kimberly Carlson, “Mapping oil palm yields from space”
- Victoria Spirling, “Twitter trolls and Facebook activists: Reputational and prosocial motives for online outrage expression”
2020 Summer Research Projects Selected for Funding
- Justin Pargeter, “Using 3D markerless pose estimation and deep neural networks to understand Paleolithic skill acquisition and the origins of social learning”
- Matt Maurano, “Analysis of allelic heterogeneity in high-dimensional genetic data”
- Narges Razavian, “Natural Language Processing for Clinical Notes”
- Anna Harvey, “Jail Data Initiative”
- Alexej Jerschow, “Image classification, recognition, and synthetic data in diagnostics of rechargeable batteries”
- Michael Rizzo, “Metrics of Racial Inequality”
- Krzysztof Geras, “Building deep neural networks to diagnose breast cancer with multiple imaging modalities”
- Anli Liu, “Assessment of Right Temporal Lobe Function through Drawing”
- Yvonne Lui, “A practical DL-based tool for medical image specifications identification”
- Yingkai Zhang, “Drug design with deep learning”
- Stephanie Cook, “Features of social media usage and physical health among emerging adults”
- Petter Kolm, “Textual and sentiment analysis for trading”
- Cem Deniz, “Predicting Knee Osteoarthritis”
2019 Summer Research Projects Selected for Funding
- Ying Lu, “Developing Data-driven Analytics for Precision Rehabilitation”
- Anastasios Noulas, “Deep Learning Pattern Recognition in Augmented Reality Environments”
- Kevin C Chan, “Quantitative evaluation of brain changes driven by visual impairment or by sight restoration interventions”
- Alexej Jerschow, “Image classification, recognition, and synthetic data in diagnostics of rechargeable batteries”
- Sonali Shukla McDermid, “Evaluating ecosystem-climate interactions from MsTMIP”
- Florian Knoll, “End-to-end medical image reconstruction and diagnostic classification”
- Linda Moy, “Predicting the development of breast cancer in the future using current image data “
- Todd Gureckis, “Using Internet advertising to recruit participants for behavioral science”
- Yvonne Lui, “Predicting Missed Appointments in An Academic Radiology Practice”
- Barton Beebe, “Is Europe Running Out of Trademarks? Trademark Registration Practices in the European Union”
- Petter Kolm, “Reinforcement learning for dynamic replication and hedging of option portfolios”
- Anna Harvey, “Jail Data Initiative”
- Aristotelis Tsirigos, “Predict response to immunotherapy in lung cancer using deep learning”
- Douglas Kondziolka & Kenneth Bernstein, “Comparative Analytics from a Large Prospective Neurosurgery Registry”
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”