Engineering Test Kitchen is a non-profit consulting firm founded and operated by Washington University in St. Louis undergraduate, multidisciplinary, engineering students. We provide a team of skilled engineering undergrads under the guidance of an experienced mentor to take on your company’s projects
Our mission is to connect engineering undergraduates with real projects where they can learn, make meaningful contributions, and develop relationships with potential future employers.
Students will have the opportunity to work with Sansone Group, a nationally recognized real estate firm in St. Louis. The ETK team will create an application that uses vision recognition services for document and text matching. Specifically, the team will work with image and document classification, pattern recognition, image analysis, Optical Character Recognition (OCR), Optical Word Recognition (OWR), Intelligent Character Recognition (ICR), 3D and 2D Code recognition (Bar codes, QR, etc.) content based image retrieval (CBIR) and Query by Image (QBI). Students will be able to work closely with industry professionals to develop this solution. Additionally, they will develop valuable experience in cutting-edge, industry technologies. They will also come out with a professional grade project to list on their resumes. Preferred qualifications include experience with a scripting language such as Python and experience working with databases (MySQL, MongoDB, etc. Experience with vision recognition services is also a huge plus.
Team members will be working for the WashU Office of Technology Management (OTM), testing the viability of a patent for biofoam sheets for water purification. Members will build a solar still device and conduct field testing to further understand the engineering demands of the product. Qualifications: Lab experience is a plus. Chemical Engineering and MEMS majors are encouraged to apply
The group will work on a machine learning module for Clever Analytics. This application will use supervised machine learning algorithms to train a model and then label text, allowing users to glean insights from large sets of unstructured data. Qualifications: Object-Oriented programming experience is required. Experience with Python and MongoDB is preferred, but not required. Prior experience with machine learning and natural language processing is a big plus, but students will have the opportunity to learn during the project