2016 Seed Grant Awards
The Seed Grant Selection Committee is thrilled to announce that, after a rigorous evaluation process involving multiple referee reports, the following grant proposals were chosen for funding by the Moore-Sloan Data Science Environment.
- Brian Parker and Christine Vogel: “Statistics Meets Transcriptomics: Time-Series Responses of Post-Transcriptional Regulation By Families of Conserved RNA Structures”
- Ralph Grishman and Alastair Smith: “Health and Death of Political Leaders”
- Jonathan Winawer and Heiko Müller: “The Standard Cortical Observer”
- Florian Knoll and Carlos Fernandez-Granda: “Estimation of Multiple Tissue Compartments from Magnetic-Resonance-Fingerprinting Data”
- Preeti Raghavan and Aaditya Rangan: “Determining Treatment Algorithms for Patient Subgroups in Stroke Rehabilitation”
- Thomas Kirchner and Kyunghyun Cho: “Image-based Community Asset and Risk Factor Surveillance System using Deep Learning”
- Nathaniel Beck and David Sontag: “Applying Machine Learning Methods to Integrated Time Series”
Congratulations to the award winners!
2016 NYU Data Science Seed Grant Application
The Moore Sloan Data Science Environment at NYU is announcing a unique funding opportunity, open to all NYU faculty, that aims to bring together data scientists and domain scientists to foster collaborations and generate new ideas. We expect to fund 6-8 proposals of either up to $25,000, or up to $6,000 in addition to software engineering assistance from the data science incubator. We expect that most budgets will request seed funding for 1 graduate student for 1 semester. However, budgets including data / materials / software purchases or other incidental expenses will also be considered. The fund cannot be used toward faculty salary.
1. The proposal must be interdisciplinary in nature. Each proposal must have two NYU PIs from two different scientific domains (same/different school does not matter), one person serving the role of a methods expert and the other as a domain scientist. The proposed project should be aligned with the aims of the Moore-Sloan Data Science Environment.
2. There is a strong preference toward innovative ideas and new collaborations/ties across NYU.
3. An interested applicant must first submit an online letter of interest (by March 25th) including a brief description of your areas of expertise and a very brief description of proposed project areas that you believe could benefit from this seed grant (either innovative data science applications in the domain field or a domain field problem that requires a data science solution). You don’t have to identify a joint PI yet, but if you can, please identify the schools / departments / research groups where you think you may find a match. An example can be a two-sentence pitch, where the first sentence starts with “what you can provide”, and the other one starts with “what you are looking for”.
4. You must attend the “open dating” session on April 4th to pitch your ideas to the other attendees. This session is only open to those who have submitted a letter of interest. We will send you a list of potential matches before the event based on the letters of interest. There will be no formal presentations but you could bring handouts/posters (details will be announced later). The open session is your opportunity to identify a match/joint-PI. At the end of the event, if you believe you have found a match and are interested in submitting a formal proposal for the seed grant, please indicate your project topic and the names/affiliations of the two PIs to the event organizer(s).
5. The PIs must submit a formal proposal (1-2 pages) within two weeks of the “open dating” session (by April 18th). Each PI can only be (formally) involved in one project. The proposals will be reviewed by the MSDSE Methods Working Group based on the project impact, innovation and scientific merits of the proposal. The results will be announced by May 13, 2016.