AI for Advanced Supply Chain Management within Emerging Event-Driven Platforms - ON-189

Preferred Disciplines: Artificial Intelligence, Data analytics, Data science (Masters, PhD or Post-Doc)
Company: Anonymous
Project Length: 8-12 months (2 units)
Desired start date: March/April 2019
Location: Richmond Hill, ON
No. of Positions: 3
Preferences: None

About the Company: 

A Toronto based software company and early innovator in the emerging event-driven platform category which is currently a top 10 Gartner strategic priority. The company provides the An-ser© platform enabling organizations to sense, analyse and intelligently respond to critical business events occurring within their customer, supplier and partner ecosystems.

Our solutions helps customers eliminate process risk by developing a digital mindset to respond proactively to problems, often before impacting customers, products or services.  Intelligently resolving issues and increasingly without human interaction.

Project Description:

Event driven platforms are an emerging category of applications critical to successful digital transformation.  Less than 20% of Canadian businesses are ready for digital with over 50% investing poorly in technologies.  While event-processing is not new, it is far from mainstream.  However, it is projected by 2020 that 60% of business transactions will be driven by event based triggers in new digital business solutions.

The team will build upon an existing event driven product that has an aggressive roadmap incorporating PaaS, AI and a modern design-time UI.  This project will investigate and develop a PaaS approach to event driven services supported by a design-time UI for designing reuasble business event chains. 

The primary goal of the project is to enhance existing conceptual roadmaps and to move from concept to a working prototype.  Core areas of research will involve:

  • Performing a data study to develop knowledge maps for ERP applications in the area of Sales, Finance and Operations.
  • Enhancing procedural rules engines in existing event driven platforms to leverage applied AI models, assesing use of AI for complex event streams.
  • Conducting a trade-off of semantic approaches to event processing, assessing BPML vs EPC vs Blockchain in business event processing use cases.
  • Implementing recommendations from the above areas of research into a demonstrable prototype that incorprates a cloud based PaaS backend and a frontend design-time UI for building and reusing business event chains.

Research Objectives:

  • Identify ML opportunities for advanced supply chain management in global supply chains
  • Build and train AI learning models for ERP data sets
  • Investigate and recommend approaches to business event chain semantics for a design-time UI
  • Develop a working prototype to demonstrates the above concepts

Methodology:

  • Research methods will be developed by interns to support each development phase of the project.

Expertise and Skills Needed:

  • Interns 1 & 2
    • Experience with design thinking and agile software development methodology
    • Experience with leading mobile and PaaS development tools
    • Knowledge of business process semantics (EPC and/or BPML/BPEL)
    • Exposure to Blockchain is an asset
  • Intern 3
    • Knowledgable in data science and analysis is a must
    • A basic understanding of ERP business applications is preferred but not essential

For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects
  2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform.
Program: