2017 Program Description
Presentations: 45-minute general talk: 9:00 am - 9:45 am Location: 3321 Seamans Center (SC)
- Mon 6/12 — Sanvesh Srivastava (Statistics)
- Tue 6/13 — Tom Casavant (Center for Bioinformatics & Computational Biology)
- Wed 6/14 — Tong Wang (Tippie College of Business)
- Thu 6/15 — Amaury Lendasse (Industrial Engineering)
Practice: Guided Labs in interactive technology-enhanced room:
- Mon 6/12 — Introduction to Big Data and R - Kate Cowles (Statistics and Actuarial Science) - 1022 LIB (10 am-3 pm)
- Tue 6/13 — Probability & Statistics - David Stewart (Mathematics) - 1022 LIB (10 am-3 pm)
- Wed 6/14 — Learning from Data - Kate Cowles (Statistics and Actuarial Science) - 1022 LIB (10 am-3 pm)
- Thu 6/15 — Parallelism for Large Data - Suely Oliveira (Computer Science) - 350 VAN (10 am-3 pm)
- Fri 6/16 — Clustering for Data Analysis - Isabel Darcy (Mathematics) - 117 MLH (9am-noon)
These labs are prepared by Computer Science, Mathematics, and Statistics and Actuarial Science faculty members at the University of Iowa. We will provide hands-on experience using computers to classify data or gather information from diverse applications. We will introduce an easy programming language to handle the datasets and to process the data. Topics include probability, linear regression, and statistical inference and datasets may be from diverse problems in biology, chemistry, social studies, political science, even music. Similar techniques are used by Google, Amazon, Netflix, and other well-known companies.
Lunch: provided by organizers
Main organizer: Isabel Darcy, Mathematics
Co-organizers: Kate Cowles, Statistics and Actuarial Science; Suely Oliveira, Computer Science; David Stewart, Mathematics