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  • Lecture time: Monday: 11:30:00 - 12:20:00 ET
  • Lab time: Friday: 11:30:00 - 13:20:00 ET
  • Domain: Research and Development
  • Keywords: Data Integration across Studies, Data Processing, Product Comparison, Statistical Analysis
  • Tools: Programming, R, R Shiny, SAS, Statistical Network Meta-Analysis
  • Citizenship: Open to all students
Summary

P&G uses performance tests to compare new prototypes with products on the market. It is of interest to compare all product pairs accounting for study-to-study variability, and pooling information across products repeated in multiple studies.

  • Lecture time: Thursday: 15:30:00 - 16:20:00 ET
  • Lab time: Tuesday: 15:30:00 - 17:20:00 ET
  • Domain: Supply Chain
  • Keywords: Business, Market Trends, Predictive Analysis
  • Tools: Anomaly Identification, Data Analytics
  • Citizenship: Open to all students
Summary

1) Improving the stream selection & ensemble algorithm 2) Developing a forecast calibration approach to ensure a stream selected based on historical performance is creating a forecast consistent with the history of the data and streams prior predictions.

  • Lecture time: Thursday: 09:30:00 - 10:20:00 ET
  • Lab time: Tuesday: 09:30:00 - 11:20:00 ET
  • Domain: Energy
  • Keywords: LangChain, Large Language Models, Machine Learning, Neural Networks, NLP, Nuclear Energy
  • Tools: GitHub, Hugging Face, Python
  • Citizenship: Open to all students
Summary

We intend to develop a chatbot using open source LangChain components. The tool will interact conversationally and generate proposals based on natural language prompts from the from the user. The model will be fine-tuned with nuclear energy domain know

  • Lecture time: Friday: 09:30:00 - 10:20:00 ET
  • Lab time: Monday: 09:30:00 - 11:20:00 ET
  • Domain: Pharmaceutical
  • Keywords: Agile, Lean Framework, Pharmaceutical, PowerBI, Tulip
  • Tools: App Creation & Design, Data Analytics, Power BI, Tulip
  • Citizenship: Open to all students
Summary

AstraZeneca currently has business need to advance digital tools within Tulip and PowerBi. Students will be expected to build Tulip/PowerBi apps from creation to implementation and enhance the current standard work instructions for creating apps.

  • 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: Linked Open Data, Open Source
  • Tools: Data Analytics, Python, RDF, SQL
  • Citizenship: Open to all students
Summary

Work with Wikimedia on data accuracy by checking Wikidata’s data against external sources. Execute and document ways of identifying and addressing disparities between Wikidata and other databases and websites in order to feed the Wikidata Mismatch Store.

  • Lecture time: Thursday: 13:30:00 - 14:20:00 ET
  • Lab time: Tuesday: 13:30:00 - 15:20:00 ET
  • Domain: Insurance
  • Keywords: Impact Estimation, Insurance, Predictive Analysis, Quanitative Communication, Strategy
  • Tools: Git, GitHub, Python, R
  • Citizenship: Open to all students
Summary

The project will rigorously clarify and quantify the link between our research models and the strategic success metrics at which they are targeted. The goal is to develop a suite of predictive models to estimate the impact of a proposed model improvement on that overall ecosystem

  • Lecture time: Thursday: 15:30:00 - 16:20:00 ET
  • Lab time: Tuesday: 15:30:00 - 17:20:00 ET
  • Domain: Aerospace
  • Keywords: cyber security, Digital Twin, Intrusion Detection, Security Analysis, Virtual Machines
  • Tools: C, Python, VMWare
  • Citizenship: U.S. citizens and permanent residents preferred
Summary

Given a model of an avionics network, construct a VM-based digital twin of that model. Conduct a security analysis to identify potential points and methods a malicious adversary might use to attack that model, and propose/implement a modification or custom defense solution.

  • Lecture time: Tuesday: 09:30:00 - 10:20:00 ET
  • Lab time: Thursday: 09:30:00 - 11:20:00 ET
  • Domain: University
  • Keywords: Data Exploration, Machine Learning, Optimization, User Analytics
  • Tools: Data Exploration, Machine Learning, R, R Shiny
  • Citizenship: Open to all students
Summary

Data Mine students will help guide MFRI in targeted outreach efforts through the analysis of Measuring Communities user application data.

USAA - Determining Customer Intent
Closed for Registration
  • Lecture time: Friday: 13:30:00 - 14:20:00 ET
  • Lab time: Monday: 12:30:00 - 14:20:00 ET
  • Domain: Insurance
  • Keywords: Insurance, Machine Learning, Predictive Analysis
  • Tools: Python, R, SQL
  • Citizenship: U.S. citizens and permanent residents preferred
Summary

Use data science to improve USAA call centers! Students will perform analyses and develop machine learning models to understand customer intent and phone representative performance. Supplementary topics include competitive analysis and customer patience.

  • Lecture time: Tuesday: 12:30:00 - 13:20:00 ET
  • Lab time: Thursday: 11:30:00 - 13:20:00 ET
  • Domain: Chemical Informatics
  • Keywords: Chemical Safety, Informatics Platform
  • Tools: AWS, Python, SQL
  • Citizenship: Open to all students
Summary

To grow the CSL Data Collection with hazardous information and improve accessibility