From Algorithms to AI: Partnering with Universities to Shape the Future of Timetabling

EventMAP’s solutions have always been built on intelligent automation.

From our earliest scheduling engines to today’s powerful optimisation tools, algorithms and advanced operational research have been at the heart of our solutions. Long before AI became a buzzword, we were applying advanced modelling and optimisation techniques to solve complex timetabling challenges for universities.

As part of our continued commitment to innovation, we are pleased to be engaging with the University of Edinburgh through a guest online session for their MSc and final-year undergraduate course, “Topics in Applied Operational Research.”

Students on the course are working on realistic timetabling problems using real-world style data and constraints. Our session will give them insight into:

• The optimisation and algorithmic techniques underpinning modern timetabling systems
• Translating mathematical models into scalable, usable software
• The practical challenges of modelling real institutional constraints
• How automation in higher education is evolving with emerging AI technologies

While this is a one-off lecture and discussion, it represents something important to us.

Why It Matters

Universities are not only our clients, they are centres of research, experimentation and fresh thinking. Engaging with students and researchers’ helps us stay connected to emerging ideas and evolving methodologies.

As we look to introduce the latest AI technologies into our solutions, dialogue with academia becomes increasingly valuable. We see significant opportunity at the intersection of:

• Operational research
• Machine learning
• Explainable and responsible AI
• Human-centred system design

EventMAP already has a strong foundation in algorithmic automation. The next phase is about enhancing that foundation with modern AI techniques in ways that are practical, transparent, and genuinely useful for institutions.

A Call for Collaboration

This session with the University of Edinburgh is an early step in what we hope will become broader engagement with the academic community.

If you are:

• A researcher working in optimisation, AI, or decision-support systems
• A PhD student seeking real-world problem contexts
• An academic interested in industry engagement
• Or a university exploring innovation partnerships

We would be very interested in starting a conversation.

The future of timetabling will combine deep optimisation expertise with the responsible application of AI. We are actively exploring that future and we welcome collaborators who would like to explore it with us.

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