MOOG came to CSE in hopes of building a technology solution that would prove the provenance and transfer of digital assets securely between parties. Working together, Microsoft and MOOG set out to develop a demo of this solution that leverages Azure and blockchain technology.
Food ingredients travel thousands of miles along logistics chains. One bad batch of produce can ruin a restaurant’s reputation, but it’s hard to identify who’s at fault. CSE has worked with Hitachi to build a sample infrastructure leveraging blockchain – thus achieving a new level of accountability for those producing, storing and serving food.
Nestlé Skin Health partnered with Microsoft to develop a deep learning model powered mobile app able to assess acne severity using only uploaded selfie images as a source.
Deep learning algorithms capable of learning and predicting customer behavior are allowing businesses to intervene with the right retention offers at the right time. CSE recently partnered with Majid Al Futtaim Ventures (MAF) to design and deploy a machine learning solution to predict attrition.
Over the course of twelve months Microsoft and BMW partnered three different times to help BMW with its vision for technical transformation. An open-source package called ROS-Industrial was used to help provide the building blocks for the robotics work.
This code story describes CSE's work with ZenCity to create a data pipeline on Azure Databricks supported by a CI/CD pipeline on TravisCI. The aim of the collaboration was to create a pipeline capable of processing a stream of social posts, analyzing them, and identifying trends.
CSE teamed up with Conservation Metrics to use Active Learning to allow for more efficient data labeling for object detection projects.
Developing robust algorithms for self-driving cars requires sourcing event data from over 10 billion hours of recorded driving time. CSE worked with Cognata, a startup developing simulation platforms for autonomous vehicles, to build a Jenkins pipeline and Terraform solution that enabled our partner to dynamically scale GPU resources for their simu...
A scalable unsupervised approach for driver safety estimation on Pointer Telocation's dataset
Microsoft and Land O'Lakes partnered to develop an automated solution to identify sustainable farming practices given thousands of satellite images of Iowan farms. Our primary goal was to reduce the reliance on manual interviewing of farmers and make it more profitable for farmers to follow sustainable farming practices. To tackle this issue our te...
