SlideShare a Scribd company logo
1 of 16
DSI Summer Lab
Information Session
DSI Summer Lab
10-week, paid internship. Students
paired with interdisciplinary and CS
faculty to conduct research or
engineering project. Cohort
experience of ~30 HS and UG
students..
A 10-week, paid summer
research program, where
high school, undergraduate,
and Masters students work
on data science research
projects in a variety of fields.
UChicago Data Science Institute (DSI)
The Data Science Institute (DSI) at the University of
Chicago is a new unit that executes the University’s
bold, innovative vision of Data Science. Originally
launched in 2018 as the Center for Data and
Computing, DSI builds on the success of CDAC and
now expands its activities to include:
● seeding research on the interdisciplinary frontiers of
this emerging field;
● forming partnerships with industry, government, and
social impact organizations;
● supporting holistic data science education.
Summer Lab Program Goals
Inspiring and training students to become
the next generation of data scientists.
● Provide students first-hand research experiences
and access to cutting-edge research in data science
● Build a cohort of students centered
around positive peer interactions
● Equip students for sustained
futures in data science and
computing
Program Structure
Full-time Schedule
37.5 hours/week
(In Person)
Stipends $5,500
Direct Embedding in
Research Groups
Final Symposium, Poster
Session and Lightning Talks
Inclusive Cohort Environment
Research Project Topics
Engage in data science research projects from a wide range of applied,
interdisciplinary topics, including but not limited to:
DOMAIN AREAS
● Biology & Medicine
● Communications & Internet
● Economics & Business
● Energy
● Environmental Sciences
● Food & Agriculture
● Human Rights
● Policy
● Physics & Astronomy
TECHNICAL AREAS
● Computer Systems & Architecture
● Data Science & Machine Learning
● Deep Learning
● Hardware & Devices
● High Performance Computing
● Human-Computer Interaction
● Networking
● Security & Privacy
2022 Cohort Project Profiles
→ Check out more at:
datascience.uchicago.edu/engage/summerlab
{
Cohort Community
2021 Cohort By the Numbers: 48 Students
● 11 High Schoolers
● 23 Undergraduates
● 14 Masters Students
● 52% Women
● 80% want to pursue a CS/DS
research after their Summer Lab experience
● 98% reported making meaningful connections with
peers in the 2022 cohort
Program Activities: Social Events
● Speaker Series
● Trivia
● Tea times
● Game nights
● Field trips
______________________________________________
Application
● Research Areas & Skills Evaluation
○ Keywords
○ Short answer explaining interests
○ Self-evaluate skill in various computational
and data science tools (rank 1-5)
● Short Answer
○ Personal statement
○ Internship goals
○ Describe a research project
■ Goal of the project
■ Tools used
■ One challenge faced
■ One achievement
■ Results or outcomes
→ the explanation matters more than the
technicality or impressiveness of the project
● Resume
○ 1 page max
○ Should include:
■ Background information
■ Academic progress (GPA, relevant
coursework)
■ Relevant experience (internships,
programs, certificates, clubs,
competitions)
■ Technical skills for computing and
data science (programming
languages, libraries, tools, softwares)
■ Links to any websites, portfolios,
GitHub, LinkedIn
Review Criteria
➔ Applications will be reviewed using the following criteria
Intellectual Curiosity: Evident interest about data science and the applied domain areas chosen.
Skills Baseline: Familiarity with at least one programming language, and translation of self-evaluated skills
ratings in CV/relevant coursework/other experiences.
Program Fit: Clear why this program is valuable to the student versus others (e.g. skills training camps).
Evident interest in being part of a cohort group.
Initiative + Teamwork: Student has acted upon interest by pursuing available options and opportunities for
computational and data science classes, training, and programs, and has successfully worked as part of a
team before.
Research Aptitude: Creativity and curiosity, self-direction, goal-oriented and adaptable work ethic, resilient
problem solving, time management and communication skills.
Program Eligibility
Grade Year + Age: High school applicants must be a current sophomore or Junior; Undergraduate
students must be enrolled in college in fall 2023 (graduating college seniors are not eligible)
International Students: International students are eligible to apply so long as they are able to provide
documentation to support their work authorization in the United States. See the program FAQ for more
details. If you have specific questions about your eligibility, contact your international student office.
Housing: We provide housing as part of this program; all successful applicants will be offered on-campus
housing at the University of Chicago.
Tech Environment: Access to a computer or laptop that has capacity to download software, libraries, and
other resources for your project. If you’re concerned about the resources you have available, we will work
with you to make sure you have the requisite tech required to participate.
➔ Applications will be reviewed using the following eligibility
Application Timeline +
Program Dates
● Application is due February 12th
● Decision notifications by early April
● Program June 12th, 2023 - August 18
Q&A
Jessica Sweeney
Director of Research Programs and
Strategy, DSI
Email: jrsweeney@uchicago.edu
Web: datascience.uchicago.edu/

More Related Content

Similar to Summer Lab Info Session 2023

Academic Day 2211.pptx
Academic Day 2211.pptxAcademic Day 2211.pptx
Academic Day 2211.pptxssuser75ce13
 
Information platform for students project
Information platform for students projectInformation platform for students project
Information platform for students projectDebHuwaldtportfolio
 
Technology Integration Unit Yunis
Technology Integration Unit YunisTechnology Integration Unit Yunis
Technology Integration Unit Yunisamytouro
 
Future of Data Analytics Education.pdf
Future of Data Analytics Education.pdfFuture of Data Analytics Education.pdf
Future of Data Analytics Education.pdfmohitreal1995
 
The New NETS (National Educational Te...
The New NETS (National Educational Te...The New NETS (National Educational Te...
The New NETS (National Educational Te...ehelfant
 
The Future of Data Analytics Education_ Trends and Innovations (2).pdf
The Future of Data Analytics Education_ Trends and Innovations (2).pdfThe Future of Data Analytics Education_ Trends and Innovations (2).pdf
The Future of Data Analytics Education_ Trends and Innovations (2).pdfUncodemy
 
How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...
How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...
How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...Msilikale Msilanga
 
Technology Unit Outline
Technology Unit OutlineTechnology Unit Outline
Technology Unit Outlinemegerdts
 
Edu 741 tech outline
Edu 741 tech outlineEdu 741 tech outline
Edu 741 tech outlinemegerdts
 
La construcción colaborativa de proyectos como metodología para adquirir comp...
La construcción colaborativa de proyectos como metodología para adquirir comp...La construcción colaborativa de proyectos como metodología para adquirir comp...
La construcción colaborativa de proyectos como metodología para adquirir comp...UOC Universitat Oberta de Catalunya
 
Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...
Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...
Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...IL Group (CILIP Information Literacy Group)
 
Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...
Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...
Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...CONUL Teaching & Learning
 
Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...ldore1
 
Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...UCD Library
 
SGCI at Advanced Research Computing on Campuses
SGCI at Advanced Research Computing on CampusesSGCI at Advanced Research Computing on Campuses
SGCI at Advanced Research Computing on CampusesNancy Wilkins-Diehr
 
IT Capstone Report Fall 2022.pptx
IT Capstone Report Fall 2022.pptxIT Capstone Report Fall 2022.pptx
IT Capstone Report Fall 2022.pptxJack Zheng
 
Leveraging data driven decision making to drive student success, retention, a...
Leveraging data driven decision making to drive student success, retention, a...Leveraging data driven decision making to drive student success, retention, a...
Leveraging data driven decision making to drive student success, retention, a...ekunnen
 
Sevenstar digital_learningwebinar_speakup_jevans_021716
Sevenstar  digital_learningwebinar_speakup_jevans_021716Sevenstar  digital_learningwebinar_speakup_jevans_021716
Sevenstar digital_learningwebinar_speakup_jevans_021716Julie Evans
 
Jpc era5 sketchup pres
Jpc era5 sketchup presJpc era5 sketchup pres
Jpc era5 sketchup presJohn Parker
 

Similar to Summer Lab Info Session 2023 (20)

Academic Day 2211.pptx
Academic Day 2211.pptxAcademic Day 2211.pptx
Academic Day 2211.pptx
 
Information platform for students project
Information platform for students projectInformation platform for students project
Information platform for students project
 
Technology Integration Unit Yunis
Technology Integration Unit YunisTechnology Integration Unit Yunis
Technology Integration Unit Yunis
 
Building Blocks for College Readiness
Building Blocks for College ReadinessBuilding Blocks for College Readiness
Building Blocks for College Readiness
 
Future of Data Analytics Education.pdf
Future of Data Analytics Education.pdfFuture of Data Analytics Education.pdf
Future of Data Analytics Education.pdf
 
The New NETS (National Educational Te...
The New NETS (National Educational Te...The New NETS (National Educational Te...
The New NETS (National Educational Te...
 
The Future of Data Analytics Education_ Trends and Innovations (2).pdf
The Future of Data Analytics Education_ Trends and Innovations (2).pdfThe Future of Data Analytics Education_ Trends and Innovations (2).pdf
The Future of Data Analytics Education_ Trends and Innovations (2).pdf
 
How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...
How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...
How Resilience Academy and GeoICT4e project uses DigiCampus to deliver 21st C...
 
Technology Unit Outline
Technology Unit OutlineTechnology Unit Outline
Technology Unit Outline
 
Edu 741 tech outline
Edu 741 tech outlineEdu 741 tech outline
Edu 741 tech outline
 
La construcción colaborativa de proyectos como metodología para adquirir comp...
La construcción colaborativa de proyectos como metodología para adquirir comp...La construcción colaborativa de proyectos como metodología para adquirir comp...
La construcción colaborativa de proyectos como metodología para adquirir comp...
 
Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...
Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...
Teaching Data Literacy and Data Visualization as One-Credit Course - Tatiana ...
 
Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...
Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...
Re-using OER's in UCD's Research Acclerator for the Social Sciences Online Mo...
 
Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences online mo...
 
Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...
Re-using OERs in UCD’s Research Accelerator for the Social Sciences Online Mo...
 
SGCI at Advanced Research Computing on Campuses
SGCI at Advanced Research Computing on CampusesSGCI at Advanced Research Computing on Campuses
SGCI at Advanced Research Computing on Campuses
 
IT Capstone Report Fall 2022.pptx
IT Capstone Report Fall 2022.pptxIT Capstone Report Fall 2022.pptx
IT Capstone Report Fall 2022.pptx
 
Leveraging data driven decision making to drive student success, retention, a...
Leveraging data driven decision making to drive student success, retention, a...Leveraging data driven decision making to drive student success, retention, a...
Leveraging data driven decision making to drive student success, retention, a...
 
Sevenstar digital_learningwebinar_speakup_jevans_021716
Sevenstar  digital_learningwebinar_speakup_jevans_021716Sevenstar  digital_learningwebinar_speakup_jevans_021716
Sevenstar digital_learningwebinar_speakup_jevans_021716
 
Jpc era5 sketchup pres
Jpc era5 sketchup presJpc era5 sketchup pres
Jpc era5 sketchup pres
 

Recently uploaded

TOPIC 8 Temperature and Heat.pdf physics
TOPIC 8 Temperature and Heat.pdf physicsTOPIC 8 Temperature and Heat.pdf physics
TOPIC 8 Temperature and Heat.pdf physicsssuserddc89b
 
Recombinant DNA technology( Transgenic plant and animal)
Recombinant DNA technology( Transgenic plant and animal)Recombinant DNA technology( Transgenic plant and animal)
Recombinant DNA technology( Transgenic plant and animal)DHURKADEVIBASKAR
 
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...lizamodels9
 
STOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptx
STOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptxSTOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptx
STOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptxMurugaveni B
 
Environmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial BiosensorEnvironmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial Biosensorsonawaneprad
 
BREEDING FOR RESISTANCE TO BIOTIC STRESS.pptx
BREEDING FOR RESISTANCE TO BIOTIC STRESS.pptxBREEDING FOR RESISTANCE TO BIOTIC STRESS.pptx
BREEDING FOR RESISTANCE TO BIOTIC STRESS.pptxPABOLU TEJASREE
 
FREE NURSING BUNDLE FOR NURSES.PDF by na
FREE NURSING BUNDLE FOR NURSES.PDF by naFREE NURSING BUNDLE FOR NURSES.PDF by na
FREE NURSING BUNDLE FOR NURSES.PDF by naJASISJULIANOELYNV
 
Analytical Profile of Coleus Forskohlii | Forskolin .pdf
Analytical Profile of Coleus Forskohlii | Forskolin .pdfAnalytical Profile of Coleus Forskohlii | Forskolin .pdf
Analytical Profile of Coleus Forskohlii | Forskolin .pdfSwapnil Therkar
 
‏‏VIRUS - 123455555555555555555555555555555555555555
‏‏VIRUS -  123455555555555555555555555555555555555555‏‏VIRUS -  123455555555555555555555555555555555555555
‏‏VIRUS - 123455555555555555555555555555555555555555kikilily0909
 
Pests of jatropha_Bionomics_identification_Dr.UPR.pdf
Pests of jatropha_Bionomics_identification_Dr.UPR.pdfPests of jatropha_Bionomics_identification_Dr.UPR.pdf
Pests of jatropha_Bionomics_identification_Dr.UPR.pdfPirithiRaju
 
Speech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptxSpeech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptxpriyankatabhane
 
SOLUBLE PATTERN RECOGNITION RECEPTORS.pptx
SOLUBLE PATTERN RECOGNITION RECEPTORS.pptxSOLUBLE PATTERN RECOGNITION RECEPTORS.pptx
SOLUBLE PATTERN RECOGNITION RECEPTORS.pptxkessiyaTpeter
 
Solution chemistry, Moral and Normal solutions
Solution chemistry, Moral and Normal solutionsSolution chemistry, Moral and Normal solutions
Solution chemistry, Moral and Normal solutionsHajira Mahmood
 
Scheme-of-Work-Science-Stage-4 cambridge science.docx
Scheme-of-Work-Science-Stage-4 cambridge science.docxScheme-of-Work-Science-Stage-4 cambridge science.docx
Scheme-of-Work-Science-Stage-4 cambridge science.docxyaramohamed343013
 
Analytical Profile of Coleus Forskohlii | Forskolin .pptx
Analytical Profile of Coleus Forskohlii | Forskolin .pptxAnalytical Profile of Coleus Forskohlii | Forskolin .pptx
Analytical Profile of Coleus Forskohlii | Forskolin .pptxSwapnil Therkar
 
Transposable elements in prokaryotes.ppt
Transposable elements in prokaryotes.pptTransposable elements in prokaryotes.ppt
Transposable elements in prokaryotes.pptArshadWarsi13
 
Artificial Intelligence In Microbiology by Dr. Prince C P
Artificial Intelligence In Microbiology by Dr. Prince C PArtificial Intelligence In Microbiology by Dr. Prince C P
Artificial Intelligence In Microbiology by Dr. Prince C PPRINCE C P
 
Is RISC-V ready for HPC workload? Maybe?
Is RISC-V ready for HPC workload? Maybe?Is RISC-V ready for HPC workload? Maybe?
Is RISC-V ready for HPC workload? Maybe?Patrick Diehl
 
BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.
BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.
BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.PraveenaKalaiselvan1
 

Recently uploaded (20)

TOPIC 8 Temperature and Heat.pdf physics
TOPIC 8 Temperature and Heat.pdf physicsTOPIC 8 Temperature and Heat.pdf physics
TOPIC 8 Temperature and Heat.pdf physics
 
Recombinant DNA technology( Transgenic plant and animal)
Recombinant DNA technology( Transgenic plant and animal)Recombinant DNA technology( Transgenic plant and animal)
Recombinant DNA technology( Transgenic plant and animal)
 
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
 
Hot Sexy call girls in Moti Nagar,🔝 9953056974 🔝 escort Service
Hot Sexy call girls in  Moti Nagar,🔝 9953056974 🔝 escort ServiceHot Sexy call girls in  Moti Nagar,🔝 9953056974 🔝 escort Service
Hot Sexy call girls in Moti Nagar,🔝 9953056974 🔝 escort Service
 
STOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptx
STOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptxSTOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptx
STOPPED FLOW METHOD & APPLICATION MURUGAVENI B.pptx
 
Environmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial BiosensorEnvironmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial Biosensor
 
BREEDING FOR RESISTANCE TO BIOTIC STRESS.pptx
BREEDING FOR RESISTANCE TO BIOTIC STRESS.pptxBREEDING FOR RESISTANCE TO BIOTIC STRESS.pptx
BREEDING FOR RESISTANCE TO BIOTIC STRESS.pptx
 
FREE NURSING BUNDLE FOR NURSES.PDF by na
FREE NURSING BUNDLE FOR NURSES.PDF by naFREE NURSING BUNDLE FOR NURSES.PDF by na
FREE NURSING BUNDLE FOR NURSES.PDF by na
 
Analytical Profile of Coleus Forskohlii | Forskolin .pdf
Analytical Profile of Coleus Forskohlii | Forskolin .pdfAnalytical Profile of Coleus Forskohlii | Forskolin .pdf
Analytical Profile of Coleus Forskohlii | Forskolin .pdf
 
‏‏VIRUS - 123455555555555555555555555555555555555555
‏‏VIRUS -  123455555555555555555555555555555555555555‏‏VIRUS -  123455555555555555555555555555555555555555
‏‏VIRUS - 123455555555555555555555555555555555555555
 
Pests of jatropha_Bionomics_identification_Dr.UPR.pdf
Pests of jatropha_Bionomics_identification_Dr.UPR.pdfPests of jatropha_Bionomics_identification_Dr.UPR.pdf
Pests of jatropha_Bionomics_identification_Dr.UPR.pdf
 
Speech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptxSpeech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptx
 
SOLUBLE PATTERN RECOGNITION RECEPTORS.pptx
SOLUBLE PATTERN RECOGNITION RECEPTORS.pptxSOLUBLE PATTERN RECOGNITION RECEPTORS.pptx
SOLUBLE PATTERN RECOGNITION RECEPTORS.pptx
 
Solution chemistry, Moral and Normal solutions
Solution chemistry, Moral and Normal solutionsSolution chemistry, Moral and Normal solutions
Solution chemistry, Moral and Normal solutions
 
Scheme-of-Work-Science-Stage-4 cambridge science.docx
Scheme-of-Work-Science-Stage-4 cambridge science.docxScheme-of-Work-Science-Stage-4 cambridge science.docx
Scheme-of-Work-Science-Stage-4 cambridge science.docx
 
Analytical Profile of Coleus Forskohlii | Forskolin .pptx
Analytical Profile of Coleus Forskohlii | Forskolin .pptxAnalytical Profile of Coleus Forskohlii | Forskolin .pptx
Analytical Profile of Coleus Forskohlii | Forskolin .pptx
 
Transposable elements in prokaryotes.ppt
Transposable elements in prokaryotes.pptTransposable elements in prokaryotes.ppt
Transposable elements in prokaryotes.ppt
 
Artificial Intelligence In Microbiology by Dr. Prince C P
Artificial Intelligence In Microbiology by Dr. Prince C PArtificial Intelligence In Microbiology by Dr. Prince C P
Artificial Intelligence In Microbiology by Dr. Prince C P
 
Is RISC-V ready for HPC workload? Maybe?
Is RISC-V ready for HPC workload? Maybe?Is RISC-V ready for HPC workload? Maybe?
Is RISC-V ready for HPC workload? Maybe?
 
BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.
BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.
BIOETHICS IN RECOMBINANT DNA TECHNOLOGY.
 

Summer Lab Info Session 2023

  • 2. DSI Summer Lab 10-week, paid internship. Students paired with interdisciplinary and CS faculty to conduct research or engineering project. Cohort experience of ~30 HS and UG students.. A 10-week, paid summer research program, where high school, undergraduate, and Masters students work on data science research projects in a variety of fields.
  • 3. UChicago Data Science Institute (DSI) The Data Science Institute (DSI) at the University of Chicago is a new unit that executes the University’s bold, innovative vision of Data Science. Originally launched in 2018 as the Center for Data and Computing, DSI builds on the success of CDAC and now expands its activities to include: ● seeding research on the interdisciplinary frontiers of this emerging field; ● forming partnerships with industry, government, and social impact organizations; ● supporting holistic data science education.
  • 4. Summer Lab Program Goals Inspiring and training students to become the next generation of data scientists. ● Provide students first-hand research experiences and access to cutting-edge research in data science ● Build a cohort of students centered around positive peer interactions ● Equip students for sustained futures in data science and computing
  • 5. Program Structure Full-time Schedule 37.5 hours/week (In Person) Stipends $5,500 Direct Embedding in Research Groups Final Symposium, Poster Session and Lightning Talks Inclusive Cohort Environment
  • 6. Research Project Topics Engage in data science research projects from a wide range of applied, interdisciplinary topics, including but not limited to: DOMAIN AREAS ● Biology & Medicine ● Communications & Internet ● Economics & Business ● Energy ● Environmental Sciences ● Food & Agriculture ● Human Rights ● Policy ● Physics & Astronomy TECHNICAL AREAS ● Computer Systems & Architecture ● Data Science & Machine Learning ● Deep Learning ● Hardware & Devices ● High Performance Computing ● Human-Computer Interaction ● Networking ● Security & Privacy
  • 7. 2022 Cohort Project Profiles → Check out more at: datascience.uchicago.edu/engage/summerlab {
  • 9. 2021 Cohort By the Numbers: 48 Students ● 11 High Schoolers ● 23 Undergraduates ● 14 Masters Students ● 52% Women ● 80% want to pursue a CS/DS research after their Summer Lab experience ● 98% reported making meaningful connections with peers in the 2022 cohort
  • 10. Program Activities: Social Events ● Speaker Series ● Trivia ● Tea times ● Game nights ● Field trips
  • 11. ______________________________________________ Application ● Research Areas & Skills Evaluation ○ Keywords ○ Short answer explaining interests ○ Self-evaluate skill in various computational and data science tools (rank 1-5) ● Short Answer ○ Personal statement ○ Internship goals ○ Describe a research project ■ Goal of the project ■ Tools used ■ One challenge faced ■ One achievement ■ Results or outcomes → the explanation matters more than the technicality or impressiveness of the project ● Resume ○ 1 page max ○ Should include: ■ Background information ■ Academic progress (GPA, relevant coursework) ■ Relevant experience (internships, programs, certificates, clubs, competitions) ■ Technical skills for computing and data science (programming languages, libraries, tools, softwares) ■ Links to any websites, portfolios, GitHub, LinkedIn
  • 12. Review Criteria ➔ Applications will be reviewed using the following criteria Intellectual Curiosity: Evident interest about data science and the applied domain areas chosen. Skills Baseline: Familiarity with at least one programming language, and translation of self-evaluated skills ratings in CV/relevant coursework/other experiences. Program Fit: Clear why this program is valuable to the student versus others (e.g. skills training camps). Evident interest in being part of a cohort group. Initiative + Teamwork: Student has acted upon interest by pursuing available options and opportunities for computational and data science classes, training, and programs, and has successfully worked as part of a team before. Research Aptitude: Creativity and curiosity, self-direction, goal-oriented and adaptable work ethic, resilient problem solving, time management and communication skills.
  • 13. Program Eligibility Grade Year + Age: High school applicants must be a current sophomore or Junior; Undergraduate students must be enrolled in college in fall 2023 (graduating college seniors are not eligible) International Students: International students are eligible to apply so long as they are able to provide documentation to support their work authorization in the United States. See the program FAQ for more details. If you have specific questions about your eligibility, contact your international student office. Housing: We provide housing as part of this program; all successful applicants will be offered on-campus housing at the University of Chicago. Tech Environment: Access to a computer or laptop that has capacity to download software, libraries, and other resources for your project. If you’re concerned about the resources you have available, we will work with you to make sure you have the requisite tech required to participate. ➔ Applications will be reviewed using the following eligibility
  • 14. Application Timeline + Program Dates ● Application is due February 12th ● Decision notifications by early April ● Program June 12th, 2023 - August 18
  • 15. Q&A
  • 16. Jessica Sweeney Director of Research Programs and Strategy, DSI Email: jrsweeney@uchicago.edu Web: datascience.uchicago.edu/