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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: Aerospace
  • Keywords: AI, Machine Learning, Python, UI/UX
  • Tools: Artificial Intelligence, Data Engineering, Python, Radar Data, UX
  • Citizenship: U.S. Citizens Required
Summary

Develop and test detection algorithms for the 3.5 GHz CBRS (5G) or similar bands where the primary users of the band are federal incumbent radar systems.

  • Lecture time: Friday: 15:30:00 - 16:20:00 ET
  • Lab time: Monday: 15:30:00 - 17:20:00 ET
  • Domain: Aerospace
  • Keywords: Aerospace, Machine Learning, Prediction, Predictive Modeling, Trajectory Analytics
  • Tools: Git, Jupyter Notebooks, Machine Learning, Python, Tracktable (Sandia Python library)
  • Citizenship: U.S. Citizens Required
Summary

This project will focus on trajectory prediction and analysis. Observing trajectories that have crossed an area or recovering lost segments. Predicting where the trajectory will be after a certain amount of time and where the vehicle will be.

  • Lecture time: Tuesday: 09:30:00 - 10:20:00 ET
  • Lab time: Thursday: 09:30:00 - 11:20:00 ET
  • Domain: Government
  • Keywords: Data Visualization, Visualizations, Web Based Graphics
  • Tools: D3, NLP, Python, R
  • Citizenship: Open to all students
Summary

Three student teams will work together to determine whether congressional rhetoric has become more polarized over time. Team #1: Natural Language Processing: R, Python Team #2: Data Visualization Team #3: Web-Based Graphics: D3 programming

  • Lecture time: Tuesday: 09:30:00 - 10:20:00 ET
  • Lab time: Thursday: 09:30:00 - 11:20:00 ET
  • Domain: Research and Development
  • Keywords: Data Analysis, Feature Engineering, Python
  • Tools: Data Analytics, Feature Engineering, Python
  • Citizenship: Open to all students
Summary

This project primarily aims to categorize vehicles based on these usage metrics and the geographic areas where they operate.

Elevance Health - Detection of Digital Fraud
Closed for Registration INDY
  • Lecture time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Lab time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Domain: Insurance
  • Keywords: Data Engineering, Fraud, Imbalanced Classification, Parameter Selection, Security
  • Tools: Jupyter, Machine Learning, Python, SQL
  • Citizenship: Open to all students
Summary

Using security-oriented telemetry, find actionable instances of fraud in near real-time. Determine the probability that a transaction constitutes fraud and begin workflow.

  • Lecture time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Lab time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Domain: Insurance
  • Keywords: abnormality, Security, Unsupervised, Visualizations
  • Tools: Machine Learning, Pandas, Python, SQL
  • Citizenship: Open to all students
Summary

In the normal course of business, the security programs amount a staggering sum of data. Sifting through this data to discover irregular issues for devices, users, and logs is difficult and unwieldy. Author a framework capable of making these discoveries and detections.

  • Lecture time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Lab time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Domain: Insurance
  • Keywords: Machine Learning, Python
  • Tools: Pattern Identification
  • Citizenship: Open to all students
Summary

When healthcare providers change reimbursement contracts, billed procedure codes may change in an attempt to maximize the provider’s revenue. Early identification through claims data analytics will help keep healthcare costs affordable for our members.

  • Lecture time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Lab time: To-be-determined: 00:00:00 - 00:00:00 ET
  • Domain: Insurance
  • Keywords: Data Manipulation
  • Tools: Machine Learning, Python, Snowflake, SQL
  • Citizenship: Open to all students
Summary

Some high-cost healthcare services require pre-authorization to ensure members are receiving appropriate, medically necessary care. Pre-authorization data patterns can provide early insight into healthcare patterns before paid claims data is available.

  • Lecture time: Tuesday: 15:30:00 - 16:20:00 ET
  • Lab time: Thursday: 15:30:00 - 17:20:00 ET
  • Domain: Biomedical Research
  • Keywords: biology, Biomedical Science, Clustering, SPAC, Spatial Analysis, Transformation, Visualizations
  • Tools: GitHub, Python, R
  • Citizenship: Open to all students
Summary

To accelerate the pace of delivering tools to analyze spatial single-cell datasets by leveraging the contributions of students and to contribute to the advancement of scientific knowledge and understanding in the field of single-cell biology and spatial analysis.

  • Lecture time: Tuesday: 16:30:00 - 17:20:00 ET
  • Lab time: Thursday: 15:30:00 - 17:20:00 ET
  • Domain: Manufacturing
  • Keywords: Automation, Chemicals, Corrosion, Data Analytics, Materials, Pharmaceutical
  • Tools: Data Analytics, Power BI, Python, UX, Web-scraping
  • Citizenship: Open to all students
Summary

This project will work with Evonik Engineers to create a dynamic program that will generate Materials of Construction Matrices to determine compatibility using corrosion rates, temperatures, and concentrations.