At Deakin Institute for Intelligent Systems, our strength lies in our people. In this profile series, we speak to our researchers who are dedicated to solving complex problems with intelligent systems. In this profile, we meet Dr Burhan Khan.
Joined IISRI: 2018
Areas of expertise: Modelling, simulation and optimisation. This includes algorithms for complex planning and scheduling problems, multi-objective optimisation and simulation, and artificial intelligence for real-time data acquisition and analysis.
Career highlights:
– Helping to develop the Australian Electoral Commission election scheduling system that is now used across Australia to plan federal elections, by-elections and referendums.
– Assisting local industry streamline operations and cut costs through better planning and simulation.
– Associate HDR Coordinator position, supervising graduate researchers, running the Three Minute Thesis (3MT) competition, and organising training to help students build skills in high-performance computing and research communication.
What are some of your key projects?
I have worked closely with the Australian Electoral Commission (AEC) and the New South Wales Electoral Commission to develop simulation models and centralised scheduling systems for federal elections.
These systems automate counting schedules using optimum resources and quick declaration of results, ensuring smooth elections nationwide. Insights from this modelling and simulation work have also contributed to legislative changes that improved election processes. I also support local manufacturers by applying modelling and optimisation to improve production processes, reduce waste and stay competitive. My goal is always to translate research into practical tools that deliver real benefits.
What are you currently working on?
I am further developing election scheduling tools to handle growing complexity and changing needs, including real-time updates and last-minute changes. I continue to work with local industry to integrate AI and data-driven methods into scheduling frameworks, helping businesses boost efficiency and make better decisions. I am also developing lightweight AI models that can run on resource-limited devices for tasks like real-time image detection and monitoring.
What led you to pursuing a career in research?
I started at IISRI in 2018, working on scheduling algorithms for the mining sector and industrial modelling projects. My PhD focused on multi-objective optimisation for complex engineering problems. Applying this research to real-world challenges like election planning and production processes showed me the value of turning theory into tools that solve practical problems.
What are you working on now?
A highlight in 2025 has been seeing our Divisional Planning and Scheduling Platform (DPSP) successfully used for the 2025 federal election. The system was integrated with AEC systems to receive live data and update schedules in real time, managing count scrutinies for polling places across the country and delivering reliable results despite tight timelines and changing requirements.
What do you enjoy most about your job?
I enjoy seeing research have a direct impact. Whether it is supporting democratic processes or helping a local business run more efficiently, it is rewarding to see ideas turned into real-world solutions. I also value the variety and collaboration in my work and the chance to help students develop skills and apply them in industry and government.
If there was a challenge you could solve, what would it be?
I want to make complex planning and scheduling simpler and more adaptable by combining AI with optimisation. My goal is to build tools that learn from data, adapt in real time and help planners make better decisions with less manual effort.
This article was originally published in the 2024 IISRI Annual Report.
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