ISE Developer Blog

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.

Preventing Rhino Poaching With Microsoft Azure

May 7, 2019 May 7, 2019 05/7/19

Olga Liakhovich

In the last eight years, poaching in Africa has been happening at an alarming rate. Currently, the continent loses three rhinos a day. As part of our team’s mission to find new ways that technology can positively impact our world, we’ve been collaborating with the Combating Wildlife Crime team Peace Parks Foundation (PPF), in partnership with

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.

Real-time Streaming Of 3D Enterprise Applications From The Cloud To Low-powered Devices

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

Andrei Ermilov

Microsoft recently partnered with AVEVA, an engineering, design and management software provider to the Power, Oil & Gas and Marine industries. AVEVA’s challenge is one that is becoming more and more common in the construction visualization space: ever increasing complexity of 3D data that needs to be highly interactive to a customer ...

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.

Running Parallel Apache Spark Notebook Workloads On Azure Databricks

January 18, 2019 Jan 18, 2019 01/18/19

Clemens Wolff

This article walks through the development of a technique for running Spark jobs in parallel on Azure Databricks. The technique enabled us to reduce the processing times for JetBlue's reporting threefold while keeping the business logic implementation straight forward. The technique can be re-used for any notebooks-based Spark workload on Azure Databricks.

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.

Real-Time Time Series Analysis at Scale for Trending Topics Detection

January 2, 2019 Jan 2, 2019 01/2/19

Omri Mendels

This code story describes a collaboration with ZenCity around detecting trending topics at scale. We discuss the datasets, data preparation, models used and the deployment story for this scenario.

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.