Application for the 2022 Spelman College Data Science Summer Research Program

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June 6th - July 15th, 2022 Spelman College will host its Second Annual Data Science Summer Research Program. SPELMAN STUDENTS FROM ALL MAJORS AND CLASSIFICATIONS ARE ELIGIBLE. Our only requirement for participation will be that students be in good academic standing (GPA > 2.0). Participants that successfully complete the program will earn a stipend of $3500.00, to be paid at the end of the program and upon completion of all assignments and surveys.

You must be available between the hours of 10 AM - 5 PM Monday - Friday between the dates of June 6th - July 15th, 2022 to participate.

The goal of the Data Science Summer Research Program is two-fold: (1) to provide students with the career development needed to identify data science careers within their disciplines and (2) to provide students with the technical skills and research experiences that will make them competitive for careers in data-science. Participants in the program will:

1) Attend regularly-scheduled lectures where they will learn skills used in the field of data science including data collection and manipulation, data representation/visualization, basic statistics, and cloud computing.

2) Work with Spelman College faculty on a data science research project of their choice.

3) Participate in weekly career and professional development workshops

4) Participate in weekly workshops on contemplative practices that focus on stress management, creative thinking, and organization, all of which are important to career success and general well-being.

One strength of the 2022 Virtual Data Science Summer Research Program is its focus on collaborative work. Accordingly, students will work in groups of 3-4 on a single, unique research question. Groups will implement the technical skills taught in lecture as they work in conjunction with faculty to conduct their research. All lectures and meetings will occur via Zoom and all assignments will be submitted via Moodle. At the end of the program, teams will present their findings to the Spelman College Community via a 20-minute virtual presentation.

Please apply by completing the information below. Applications are due Friday April 18th, 2022. Participants will be notified of their selection by May 7th.

Please contact Dr. Tiffany Oliver if you have any questions
toliver4@spelman.edu

メールアドレス *

Are you a previous participant of Spelman's Virtual Data Science Summer Research Program (No worries, you are still eligible)?

Yes

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I understand that the Data Science Program is Virtual. I agree to have my video turned on during all meetings and classes associated with the program.

Yes

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By checking below, you acknowledge that you have read and understand the program requirements. *

Yes, I have read and agree to the terms for participation

Yes, I have read and DO NOT agree to the terms for participation

必須

First Name *

Last Name *

900 number *

Email Address: *

Mailing Address: *

City: *

State: *

Telephone Number *

Classification *

Incoming Freshmen

Rising Sophomore

Rising Junior

Rising Senior

Major *

Do you have plans to participate in another program or summer school classes during the summer of 2021 *

Students participating in Spelman's 2021 Inaugural Data Science Summer Research Program will have the opportunity to participate in one of nine research projects. Please indicate your preferred project by selecting ONE of the six options below. Students are free to choose any project, regardless of their major, or classification. *

Project #1, led by Professor Lyrric Jackson - ARTS: I am a Professor of Dance and I am interested in creating a new system for tracking the historical migration of dance through mapping technology. Student working this project will build a digital database that can store archival images, film, definitions, and movement styles for the purpose of populating the data on a digital map.

Project #2, led by Professor Zhenbin Liu - HUMANITIES: I have an interest in exploring educational equity in the United States. For this project, I aim to look at this issue from the perspective of elementary schoolers' participation in after school programs. Student participants in this project will develop skills in conducting quantitative research, including deciding research questions, conducting literature review, data collection, data analysis and visualization, and drawing conclusions from data analysis

Project #3, led by Professor Robert Brown - SOCIAL SCIENCES: For my research project for this program, I would like to develop a multiyear dataset based on the states of the United States of America that examines the racial diversity of the nation, specifically African Americans. This dataset would include important demographic data of African Americans, important historical data as to whether the state began as either a free or slave state, and contemporary variables whether the state is considering voter suppression legislation. The intent of this research effort is to understand the demographic and historical influence of African Americans upon contemporary American politics (e. g., electoral behavior and voting in the recent Presidential elections). I will teach the students econometric analysis, panel analysis and data representation / visualization in order to conduct research analysis.

Project #4, led by Professor Derrick Hylton - STEM: In this project, we will solve computational problems in physics using a no-code programming approach (iFlow platform) and solve the same problems using Python (Google CoLab platform). We will define computational thinking and analyze how each approach can develop or enhance computational thinking in students, and how we can measure such development. Participants will be exposed to numerical methods, visualization, and programming with a deeper understanding of a computational approach in problem-solving. Some data collection may be done via various actual sensors or virtual sensors developed by the Institute of Future Intelligence.

Project #5, led by Professor Nazia Mojib: With the advancement of -omics technologies, the field of computational biology has generated a large amount of data addressing broad biological questions, followed by new and innovative approaches in bioinformatics to store, analyze and share these large datasets. My proposed research project is designed to employ a data mining approach to identify and study the evolution of biomolecules (especially receptors) in various signaling pathways and communication networks, in a range of biological systems, from prokaryotes, to unicellular and multicellular eukaryotes. The handling and analysis of such data require computational skills that usually needs training. This virtual data science summer research project is designed and organized to introduce students in biology to the computational analysis of big data to decipher the hidden message in these data.

Project #6 led by Professor Elethia Tillman: Students will use data science to study women's health issues which would include 1) identifying regions of and potential risk factors for high maternal mortality rates in black women, 2)identifying regions with lower mortality rates and the measures in place in those regions that support maternal health and 3) estimating the impact of applying the measures in higher-risk regions. Students could study different regions and/or different measures related to maternal mortality. 1) identifying regions of and potential risk factors for high maternal mortality rates in black women, 2)identifying regions with lower mortality rates and the measures in place in those regions that support maternal health and 3) estimating the impact of applying the measures in higher-risk regions. Students could study different regions and/or different measures related to maternal mortality.

必須

In 150 words or less, please indicate why you would like to participate in the project you selected above. *

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