Data/information fusion for MDA - QC-107

Preferred Disciplines: Information Technology; Applied Mathematics; Artificial Intelligence, Statistics and Probability (PhD, Post-Doc)
Company: OODA Technologies Inc. (OODA)
Project Length: 16 to 24 months
Desired start date: May, 2017
Location: Montreal, Quebec
No. of Positions: 2
Preferences: Must qualify typical “country of origin” restrictions within export control projects. No preferences for language.

About Company:

OODA stands for Observe, Orient, Decide, and Act; an intuitive way of describing a rational decision making process. It is a Montreal based research and development company, founded in 2008. OODA helps organizations handle vast amounts of data and accelerate operations; understanding the requirements and developing appropriate technology solutions for analysing the diverse data and providing decision support in large distributed systems.

Project Description:

OODA technologies Inc. is involved in three projects which require development and implementation of data/information fusion algorithms, methods and capabilities to establish Maritime Domain Awareness (MDA)

In these projects there are a number of information sources/sensors which provide observations about various aspects of entities on the ocean (location, velocity, acoustic, electromagnetic, etc.) as well as textual information from open sources and other documents. The information sources in each project are not the same and the anticipated results and application of the results from fusion of the information is different.

The research in these projects involves using and developing technologies, algorithms and methods for analysing, extracting pertinent information and combining data to refine state estimates and predictions. The aim is :

  • For the final picture to provide more meaningful information than the sum of its parts
  • Provide a better understanding of the meaning and evolution of this picture in the context of the goals of the application

Background and required skills

Research Objectives/Sub-Objectives:

Research objectives in OODA projects include :

  • Information extraction and georeferencing
  • Information quality assessment
  • Information cleaning (removing inconsistencies) and semantic alignment
  • Assessment of pre-existing algorithms for fusion of extracted information
  • Selection and development of fusion algorithms
  • Implementation of a fusion system integrating pre-existing and new methods


While most of the technologies and methods for performing research in these projects are part of university science and engineering curricula, very few educational institutions discuss data/information fusion as a discipline, and even  less likely topic is fusion of disparate information as sensor and text data. The research will be performed in close partnership with OODA staff reviewing and analysing algotithms and code for existing fusion capabilities applying past lessons learned. The interns will also have an opportunity to review extensive fusion literature pertinent for the specific types of fusion applications in these projects.

Expertise and Skills Needed:

The interns require background expertise in a number of sub-topics of Information Technology; Applied Mathematics; Artificial Intelligence; Statistics and Probability.  Most pertinent subtopics include: Software engineering, Information systems design, Database management, Natural language and speech understanding, Knowledge representation, Mathematics, Numerical analysis, Applied statistics, Probability theory.

The specific expertise required are :

  • Excellent knowledge of Java
  • Knowledge of C++, Databases, Linux

Desirable additional knowledge includes :

  •  Python
  • Technologies Java EE
  • Web services: SOAP, REST, Tomcat, etc.
  • HTML/CSS, JavaScript/jQuery, etc.

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

  1. Check your eligibility and find more information about open projects.
  2. Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed!
  3. 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 or directly to Jesse Vincent-Herscovici  at, jvh(a)