Midwest Big Data Summer School

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2021 Midwest Big Data Summer School

The Midwest Big Data Summer School for Early Career Researchers was designed as an intensive curriculum aimed at practitioners and researchers to get them started in data-driven research and development. The school included full day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context.

The last day of the summer school consisted of tracks where each individual track focuses on a subarea of big data analysis. Tracks included: Foundations of Data Science, Machine Learning and Data Mining, and Data Science for Public Good. Each track consisted of tutorials and invited lectures that highlighted current research methodologies and challenges.

Invited Speakers:

Alli Torban, Torban Design Studio
Matt Good, Kingland
Dr. Susan VanderPlas, Unviersity of Nebraska-Lincoln, Department of Statistics

Tracks

Foundations of Data Science
Data Science for Public Good
Digital Agriculture
Data Mining and Machine Learning

2020 Midwest Big Data Summer School

The Midwest Big Data Summer School for Early Career Researchers designed as an intensive curriculum aimed at practitioners and researchers to get them started in data-driven research and development. The school will include full day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context. The last day of the summer school consists of tracks where each individual track focuses on a subarea of big data analysis. Past tracks included: Foundations of Data Science, Machine Learning and Data Mining, Digital Agriculture, Data Science for Public Good, and SAS. Each track consist of tutorials and invited lectures that highlight current research methodologies and challenges.

Cancellation of the 2020 Midwest Big Data Summer School

In these uncertain times, we want to do our part to inhibit the spread of COVID-19. Therefore the Midwest Big Data Summer School, originally scheduled for May 18-21, 2020 in Ames, Iowa is now cancelled. It may be scheduled for an online web event at a later date. More information will be provided.

We will be issuing full refunds of registration fees soon. You will receive a full refund by the method with which you originally paid. If paid by check, you’ll receive a refund by check mailed from Iowa State University to the address used to register. Those who paid via credit card will receive a refund back to that card. Please be patient in awaiting your refund, as our registrations department is working diligently to process cancellations for many events. If you don’t know the status of your refund by the end of March, you may reach out to registrations@iastate.edu and reference your confirmation number.

We hope to see you in 2021!

2019 Midwest Big Data Summer School

The 2019 Midwest Big Data Summer School for Early Career Researchers will be held from May 20-23, 2019 in Ames, Iowa. This summer school is designed as an intensive curriculum aimed at practitioners and researchers to get them started in data-driven research and development. The school will include full-day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context.

The last day of the summer school consists of tracks where each individual track focuses on a subarea of big data analysis. This year's tracks include Foundations of Data Science, Software Analytics, Digital Agriculture, Big Data Applications, and Data Science for Public Good. Each track consists of tutorials and invited lectures that highlight current research methodologies and challenges.

Invited Speakers:

Rajesh Parekh, Engineering Director, Google
Julia Wolfe, Visual journalist, FiveThirtyEight
Thomas Zimmermann, Senior Researcher, Microsoft research
Srinivas Sridharan, Data Scientist, Corteva
Adam Hecktman, Director of Technology & Civic Innovation Chicago, Microsoft

2018 Midwest Big Data Summer School

The 2018 Midwest Big Data Summer School for Early Career Researchers was held from May 14-17, 2018 in Ames, Iowa. The school included full-day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context.

The last day of the summer school consists of tracks where each individual track focuses on a subarea of big data analysis. Foundations of Data Science, Software Analytics, Digital Agriculture, and Big Data Applications were different tracks in the 2018 Summer School.

Invited Speakers:

Chid Apte, Director: Mathematical Sciences & Blockchain Solutions, IBM Research
Tom Schenk, Chief Data Officer, City of Chicago
Jacek Czerwonka, Microsoft Research
Will Snipes, ABB Research
Ganesha Upadhaya, Huawei Research

2017 Midwest Big Data Summer School

The 2017 Midwest Big Data Summer School for Early Career Researchers was held from July 10-14, 2017 in Ames, Iowa. This summer school was designed as a one week, intensive curriculum aimed at early career researchers to get them started in data-driven research. The school included full-day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context.

The last two days of the summer school consists of tracks where each individual track focuses on a subarea of big data analysis. The Summer School years tracks included Foundations of Data Science, Software Analytics, and Digital Agriculture. Each track consists of tutorials and invited lectures that highlight current research methodologies and challenges. Participants can choose a track that they wish to attend.

Invited Speakers:

Dr. Beth Plale, Indiana University
Jennifer Freeman Smith, Center of Open Science

2016 Midwest Big Data Summer School

The first Midwest Big Data Summer School for Early Career Researchers was held from June 20-24, 2016 in Ames, Iowa. This summer school was designed as a one week, intensive curriculum aimed at early career researchers to get them started in data-driven research. The school included full-day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context.

Invited Speakers: