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  • 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.

  • Lecture time: Thursday: 13:30:00 - 14:20:00 ET
  • Lab time: Tuesday: 13:30:00 - 15:20:00 ET
  • Domain: Aerospace
  • Keywords: Aerospace, Data Analytics, Predictive Analysis
  • Tools: Python, R, SAS
  • Citizenship: Open to all students
Summary

In the investment casting process, the casting mold is often referred to as shell. Environmental conditions are closely monitored and controlled. Howmet would like the students to find correlations between shell properties and environmental conditions.

  • Lecture time: Monday: 13:30:00 - 14:20:00 ET
  • Lab time: Friday: 13:30:00 - 15:20:00 ET
  • Domain: Aerospace
  • Keywords: Automation, Generative Design
  • Tools: CREO
  • Citizenship: U.S. Citizens Required
Summary

Lockheed Martin Space hosts a generative design competition in order to drive adoption of generative design and give inspiration for future designs.

  • Lecture time: Monday: 13:30:00 - 14:20:00 ET
  • Lab time: Friday: 13:30:00 - 15:20:00 ET
  • Domain: Communication
  • Keywords: Computer Vision, Limited Labeled Data, Linear Algebra, Machine Learning, Self-Supervised Learning
  • Tools: Machine Learning
  • Citizenship: Open to all students
Summary

This project will invite research-oriented students to explore state of the art methods to train models with limited labeled data, specifically in the domain of computer vision applications.

  • Lecture time: Tuesday: 12:30:00 - 13:20:00 ET
  • Lab time: Thursday: 11:30:00 - 13:20:00 ET
  • Domain: Research and Development
  • Keywords: Cheminformatics, Drug Research and Development, Machine Learning, Molecular biology
  • Tools: Machine Learning, Python
  • Citizenship: U.S. citizens and permanent residents preferred
Summary

***No freshmen unless prior experience*** Health Threats Emerge Faster Than Our Ability to Address Them. Goal: identify new virtual compounds with important drug-like properties

Merck - Lab Logistics
Closed for Registration
  • Lecture time: Tuesday: 15:30:00 - 16:20:00 ET
  • Lab time: Thursday: 15:30:00 - 17:20:00 ET
  • Domain: Health
  • Keywords: API, Drug Research and Development
  • Tools: Postman, SQL
  • Citizenship: Open to all students
Summary

The goal of this project is to build a data pipeline that populates a centralized database with sample submission and dynamic location information on which to perform statistical analysis.