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Using Blockchain To Securely Transfer And Verify Files

July 30, 2019 Jul 30, 2019 07/30/19

Lilian Kasem (she/her)

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.

Using uPort For Authentication On Blockchain To Improve Standards On The Food Logistics Chain

March 29, 2019 Mar 29, 2019 03/29/19

Zach Miller

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.

Assessing the Severity of Acne via Cell Phone Selfie Images Using A Deep Learning Model

February 5, 2019 Feb 5, 2019 02/5/19

Hang Zhang

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.

Developing and Deploying a Churn Prediction Model with Azure Machine Learning Services

January 10, 2019 Jan 10, 2019 01/10/19

Patty Ryan

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.

Improving Safety and Efficiency in BMW Manufacturing Plants with an Open Source Platform for Managing Inventory Delivery

December 19, 2018 Dec 19, 2018 12/19/18

Ryan Pedersen

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.

Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

December 12, 2018 Dec 12, 2018 12/12/18

Mor Shemesh

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.

Active Learning for Object Detection in Partnership with Conservation Metrics

November 6, 2018 Nov 6, 2018 11/6/18

Olga Liakhovich

CSE teamed up with Conservation Metrics to use Active Learning to allow for more efficient data labeling for object detection projects.

Infrastructure as Code – On demand GPU clusters with Terraform & Jenkins

August 9, 2018 Aug 9, 2018 08/9/18

Tomer Rosenthal

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 simulations.

Unsupervised driver safety estimation at scale, a collaboration with Pointer Telocation

July 30, 2018 Jul 30, 2018 07/30/18

Omri Mendels

A scalable unsupervised approach for driver safety estimation on Pointer Telocation's dataset

Deploying a Batch AI Cluster for Distributed Deep Learning Model Training

July 9, 2018 Jul 9, 2018 07/9/18

Stephanie Marker

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 team deployed a highly scalable Batch AI cluster on Azure and then performed distributed deep learning model training with Horovod.

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