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 and grads under the guidance of an experienced mentor to take on your company's projects.
Our mission is to connect engineering undergraduate and graduate students with real projects where they can learn, make meaningful contributions, and develop relationships with potential future employers.
In this project, the ETK team will collaborate with an Accenture data team on a cloud platform to be used in addressing structural issues in the historically troubled Hayden’s Rectangle area of St. Louis. The team will build interface for social workers to submit data collected from residents. A dashboard will be created to compile collected data with other databases to generate insight in crime and poverty reduction efforts.
Preferred Experience: Full-stack software development, geospatial data analysis, database management
Principal Investigator(s): Dr. Mary Ruppert-Stroescu (WashU) and Dr. Minh Pham (Oklahoma State University)
Project: In this project, the ETK team will work with professor Mary Ruppert-Stroescu, in the Sam Fox School, helping develop a wearable EKG monitor. The garment is fabricated entirely from conductive textiles. With conductive fabric patches acting as EKG electrodes and conductive threads as wires. As engineers we aid in solving many of the technical challenges faced: materials testing, the interface between solid electronics and textiles, software development, 3D modeling, and circuit design. Additionally, we will be adding a respiratory monitor as well as an accelerometer for position monitoring.
Preferred experience: Sensor hardware, Matlab, Arduino, circuit design, materials testing
Client: Eaton Bussmann
In this project, the ETK team will work with engineers at Eaton Bussmann, a local electrical company, to implement a facial recognition system to control access to switchboards and control panels. Python scripts combined with machine learning models can be leveraged to achieve the goal of recognizing faces and safety equipment accurately to ensure security of the system.
Preferred Experience: Python, IoT hardware, Google Tensor Processing Unit, tensorflow, machine learning, database management
Client: Eaton Bussmann
In this project, the ETK team will work alongside engineers at Eaton Bussmann to design and develop a creative IoT solution to be included in their products. The team will work with hardware such as Arduinos and Raspberry Pi to monitor machine health and potentially aggregate data in the cloud for analysis to be used in preventative maintenance.
Preferred Experience: Familiarity with Arduino, Raspberry Pi, C/C++, general hardware, database management
Client: WUSM department of Radiation Oncology
In this project, had the opportunity to work with WUSM department of Radiation Oncology. The goal of this work was to use mm-wave imaging technology to localize radiation oncology patients consistently over a round of radiotherapy. Consistent localization is important for delivery of the radiation dose to the proper target while minimizing impact on surrounding organs. One of the components of this project will be designing a GUI that conveys information about the patient's position to the user.
Client: Joseph C. Sansone Company
Our ETK team had the opportunity to work with Joseph C. Sansone Company, a nationally recognized real estate firm. The ETK team worked to create an application that uses vision recognition services for document and text matching. Specifically, the team worked 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.
Client: Pirooz Eghtesady, MD, PhD
In this project, students will work with Pirooz Eghtesady, MD, PhD, the Cardiothoracic Surgeon-in-Chief at the Wash U School of Medicine and St. Louis Children's Hospital. The team will work to create a medical device to provide circulatory support in univentricular infants. Specifically, infants' hearts are put under significant strain during surgery and often times need functional support. This device will be inserted into one side of the heart, connect to an external pump, and then reconnect to the aorta on the other side of the heart. Ideally, this device will be able to reside within the patient for an extended period of time without causing any impairments.
Students will have the opportunity to work with Prattle Analytics, a startup that uses sentiment analysis to predict interest rate shifts. The ETK team will create an application that uses parallel computing for efficient data processing. 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, including PostgreSQL, MongoDB, and AWS Lambda. They will also come out with a professional grade project to list on their resumes.
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