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  • Lecture time: Monday: 09:30:00 - 10:20:00 ET
  • Lab time: Friday: 09:30:00 - 11:20:00 ET
  • Domain: University
  • Keywords: Data Structures, Machine Learning, Predictive Analysis, sports analytics
  • Tools: Azure, Power BI, Statistical Modeling
  • Citizenship: Open to all students
Summary

The Ray Ewry Sports Engineering Center closely partners with industry, academia, and athletics to create the solutions that will help bring sports into the future. Students will build a predictive tool to aid with olympic games execution.

  • Lecture time: Monday: 15:30:00 - 16:20:00 ET
  • Lab time: Friday: 15:30:00 - 17:20:00 ET
  • Domain: Energy
  • Keywords: ArcGIS Pro, Geographic Information Science, Optimization, Renewable Energy, Spatial Data Science, Suitability Modeling, Vector and Raster Data
  • Tools: Azure, Python
  • Citizenship: U.S. citizens and permanent residents preferred
Summary

At the intersection of Operations Engineering and Planning, there lies three broad, mutually-beneficial categories for data scientists to explore: next-day forecasting, determining and aggregating a robust seasonal average temperature for an area, and siting.

  • Lecture time: Tuesday: 12:30:00 - 13:20:00 ET
  • Lab time: Thursday: 11:30:00 - 13:20:00 ET
  • Domain: Biomedical Engineering
  • Keywords: Data Analysis
  • Tools: Python, R
  • Citizenship: Open to all students
Summary

This is a Purdue research opportunity with Dr. Marshall Porterfield, Professor of Agricultural & Biological Engineering during the 2022-23 academic year. Specifically, this research will involve computational and data mining approaches for NASA Space Biology and Medicine.

Renzoe Box - Renzoe Match
Closed for Registration
  • Lecture time: Friday: 13:30:00 - 14:20:00 ET
  • Lab time: Monday: 13:30:00 - 15:20:00 ET
  • Domain: Cosmetic
  • Keywords: NLP, Product Tags, Web Scraping
  • Tools: AWS, Cron, Docker, GitHub, Python
  • Citizenship: Open to all students
Summary

The Renzoe Match (RZM) project can be broken down into the following components: RZM Color Correction Algorithm and RZM SmarTags

  • Lecture time: Monday: 15:30:00 - 16:20:00 ET
  • Lab time: Friday: 15:30:00 - 17:20:00 ET
  • Domain: University
  • Keywords: Database, Project Management, User Experience
  • Tools: HTML, JavaScript, SQL
  • Citizenship: Open to all students
Summary

The team will focus both on helping to more efficiently collect, store, and visualize data from service-learning grant project, and create a new grant management database. This will include user interface, workflow, and database analysis.

  • Lecture time: Tuesday: 13:30:00 - 14:20:00 ET
  • Lab time: Thursday: 13:30:00 - 15:20:00 ET
  • Domain: Agriculture
  • Keywords: Agriculture, App development, Computer Vision, Geospatial Analysis
  • Tools: ArcGIS, JavaScript, Python, R
  • Citizenship: Open to all students
Summary

Use imagery collected from drones to count corn plants in research plots.

  • Lecture time: Tuesday: 13:30:00 - 14:20:00 ET
  • Lab time: Thursday: 13:30:00 - 15:20:00 ET
  • Domain: University
  • Keywords: Database, Data Scraping, Satellite Imagery, Statistics, Visualizations
  • Tools: Python, R, SQL
  • Citizenship: Open to all students
Summary

Almost all this data is disaggregated and difficult to parse, collate, reduce, and visualize. The goals of this project are to scrape and aggregate existing data, and design visualization tools for this aggregated data.

  • Lecture time: Monday: 15:30:00 - 16:20:00 ET
  • Lab time: Friday: 15:30:00 - 17:20:00 ET
  • Domain: Manufacturing
  • Keywords: Logistics and Supply Chain, Maintenance, Manufacturing
  • Tools: ANOVA, Monte Carlo, Power BI, Python, R
  • Citizenship: Open to all students
Summary

YPPI’s Greenfield, IN modern investment casting foundry was built using a plant-wide system for managing numerous Key Performance Variables. YPPI is using this data to try and improve factory efficiency, reduce scrap rates as well as reduce equipment downtime.

  • Lecture time: Friday: 09:30:00 - 10:20:00 ET
  • Lab time: Monday: 09:30:00 - 11:20:00 ET
  • Domain: Aerospace
  • Keywords: Anomaly Identification, Image Processing, Machine Learning
  • Tools: Machine Learning, Python
  • Citizenship: Open to all students
Summary

Turbine blades and vanes are analyzed via X-Ray imaging methods to detect internal non-metallic anomalies. Howmet would like the students to develop a machine learning algorithm and image process system that can automatically and correctly identify anomalies in these X-Ray images

  • Lecture time: Monday: 15:30:00 - 16:20:00 ET
  • Lab time: Friday: 15:30:00 - 17:20:00 ET
  • Domain: Research and Development
  • Keywords: Biological detection, Machine Learning, Sensor networks, Simulation modeling
  • Tools: Applied Mathematics, Git, Jupyter Notebooks, Machine Learning, .NET, Python, Statistics
  • Citizenship: U.S. citizens and permanent residents preferred
Summary

Battelle is developing a simulated environment for evaluating the capability of arbitrary sensor networks to detect biological events.