Business Analytics and AI Research Group

Ontario Tech University (University of Ontario Institute of Technology), Oshawa, Ontario
What the facility does

Research on developing business decision systems and analytics tools.

Areas of expertise

The Business Analytics and AI Laboratory is a dedicated research group that specializes in leveraging data to generate valuable insights, ultimately enhancing decision-making processes within business organizations. Researchers and students at the lab employ cutting-edge computational and statistical techniques to delve into challenges and opportunities in the realms of marketing and operations management. Through their work, they aim to advance the scientific understanding of these fields and drive practical applications for improved business outcomes.

Research services

The facility offers a range of services to users in the private, public, and non-profit sectors. These services include:

  • Data analysis and insights: Our team of experts provides comprehensive data analysis using advanced techniques and tools to extract meaningful insights. We assist organizations in understanding their data, identifying patterns and trends, and translating them into actionable recommendations.
  • Predictive modeling and forecasting: Leveraging sophisticated predictive modeling techniques, we help organizations forecast future trends, demand, and customer behavior. This enables proactive decision-making and effective planning in various business domains.
  • Optimization and decision support: We offer optimization services that help organizations optimize their operations, resources, and processes. By applying mathematical modeling and algorithms, we assist in finding the best solutions to complex problems, enhancing efficiency and maximizing outcomes.
  • Market research and customer insights: We conduct market research studies to gain deep insights into consumer behavior, preferences, and market dynamics. Our expertise in analyzing consumer data enables organizations to develop effective marketing strategies and targeted campaigns.
  • Machine learning and artificial intelligence: Our facility specializes in utilizing machine learning and artificial intelligence techniques to solve business challenges. We develop custom algorithms, predictive models, and intelligent systems to automate processes, improve decision-making, and drive innovation.
  • Data visualization and reporting: We provide data visualization services that transform complex data into visually appealing and easily understandable formats. Our reports and dashboards enable organizations to grasp key insights quickly and make informed decisions.
  • Training and workshops: We offer training programs and workshops to equip students with the knowledge and skills required to harness the power of data analytics and AI. These sessions cover various topics, including data analysis, machine learning, and decision support systems.
  • Consulting and custom solutions: Our team provides personalized consulting services to address specific business challenges and develop tailored solutions. We collaborate closely with organizations to understand their unique needs and deliver practical, data-driven strategies.
Sectors of application
  • Consumer durables
  • Consumer non-durables
  • Financial services and insurance
  • Healthcare and social services
  • Information and communication technologies and media
  • Management and business related services



Video Wall

Very large screens for data visualization.

Maple software

Math software for numerical analysis, data processing and optimization.

GAMS (General Algebraic Modeling Language) software

Modeling system for mathematical optimization, numerical analysis, and data processing.

Python open-source software

Programming languages for system integration.

R open-source software

Programming languages for system integration.




Applying hybrid machine learning algorithms to assess customer risk-adjusted revenue in the financial industry.

Price and quality competition while envisioning a quality-related product recall.

Risk-averse supplier selection and order allocation in the centralized supply chains under disruption risks.

Investigating the level and quality of the information in the environmental disclosure report of a corporation considering government intervention.

Scientific evidence production and specialty drug diffusion.

The dual impact of product line length on consumer choice.

Open innovation in services? A conceptual model of barriers to service innovation adoption.

A service architecture using machine learning to contextualize anomaly detection.…

Modeling Yellow and Red Alert durations for ambulance systems.

Algorithms for queueing systems with reneging and priorities modeled as quasi-birth-death processes.