Grounded solutions, genuine
value and qualified experts
About Daitum
Daitum is an Australian-based AI company a long time in the making. Born out of the vision to make decision analytics accessible to everyone, simplicity and usability are the cornerstones of everything we develop. With over 25 years combined experience designing and building enterprise AI solutions for complex business problems, we have the technical expertise and commercial nous to help a business realise the true value of data. No spin, just grounded solutions and genuine value backed by a team of world-renowned computer scientists with the pedigree and credentials in real AI.
Executive Team

PHILIPP ROHLFSHAGEN, PHD, CEO 
Dr. Philipp Rohlfshagen is a technical expert and problem solver. He holds a phd in computer science and is the author of over 30 peer-reviewed publications. His area of expertise spans artificial intelligence, optimisation and machine learning. He combines deep technical expertise with effective managerial skills to successfully lead teams of technical experts to deliver complex technology projects.
Overview of Experience
- Dr. Philipp Rohlfshagen is a technical expert and problem solver. He holds a PhD in Computer Science and is the author of over 30 peer-reviewed publications. He has received numerous awards for his work and has also been awarded a number of research grants. His expertise spans a number of areas in advanced analytics and machine learning.
- Philipp is an academically trained technical expert in advanced analytics with extensive experience working in commercial environments. He combines deep technical expertise with effective managerial skills to successfully lead teams of technical experts to deliver complex technology projects.
- Philipp has worked closely, and often on site, with a number of clients across a variety of different domains. He has extensive experience in mining, manufacturing, and logistics, and is well versed with the different requirements clients have.
Key Skills
- Real-world problem solving
- Cross-functional supervision and team management
- Client interactions and relations
- Project execution and delivery
- Hybrid optimisation frameworks
- Modelling and simulation
- Data analysis
Past Roles
- Lead Optimisation Scientist, Paradyn Systems
- Chief Scientist (Supply & Demand Optimisation), Schneider Electric
- Capability Lead Principal Science, Schneider Electric
- Principal Scientist, SolveIT Software
- Senior Research Officer, University of Essex
- Research Fellow, University of Birmingham
- Research Officer, University of Bath
Education and Qualifications
- PhD (Computer Science), University of Birmingham
- MSc Natural Computation (Distinction), University of Birmingham
- BSc Computer Science and Artificial Intelligence (First Class Honours), University of Birmingham
Awards and Recognitions
- Schneider Electric Software Australia 2014 Annual Awards – Winner for Outstanding Performance
- Best paper awards at two leading academic conferences
- Recipient of the University of Birmingham School of Computer Science prestigious Ramsay PhD scholarship
- EPSRC scholarship at the University of Birmingham
- SearchSpace Price for best BSc Artificial Intelligence Research Project
Clients and Projects
- Coal blend optimisation, BHP Billiton
- Supply chain capacity planning, Rio Tinto Iron Ore Canada
- Material flow scheduling and planning, Peabody
- Port operations activity scheduling, BHP Billiton
- Fertiliser manufacturing scheduling, Incitec Pivot
- Supply chain activity scheduling and planning, Roy Hill Iron Ore
- Product distribution optimisation, Treasury Wine Estates
- Rail scheduling and maintenance planning, Aurizon
Publications
- P. Rohlfshagen and X. Yao, “Evolutionary dynamic optimisation: challenges and perspectives”, Evolutionary Computation for Dynamic Optimization Problems, Vol. 490, 2013
- D. Perez, P. Rohlfshagen and S. Lucas, “Monte Carlo tree search: long-term versus short-term planning”. In the IEEE Conference on Computational Intelligence & Games, 2012
- P. Rohlfshagen and J. Bullinaria, “Nature inspired genetic algorithms for hard bin packing problems”, Annals of Operations Research, Vol. 179, No. 1, 2010
- P. Rohlfshagen and X. Yao, “Attributes of dynamic combinatorial optimisation”, Lecture Notes in Computer Science, Vol. 5361, 2008
- P. Rohlfshagen and E. Paolo, “The circular topology of rhythm in asynchronous random boolean networks”, BioSystems, Vol. 73, 2004

LUIGI BARONE, PHD 
Dr. Luigi Barone is a senior analytics executive and internationally-recognised expert in artificial intelligence. He is the author of over 50 peer-reviewed research papers, and is the recipient of numerous awards and grants from different academic, government, and industry bodies. Luigi has previously worked in academia, large industrial software houses, small tech start-ups, IT consultancies, and non-profit organisations. He is passionate about science, problem-solving, and getting computers to do cool things.
Overview of Experience
- Dr. Luigi Barone is an internationally-recognised technical expert in the field of prescriptive analytics and artificial intelligence. He is the author of over 50 peer-reviewed research papers, and is the recipient of numerous awards and research grants from a variety of academic, government, and industry sources.
- Luigi has over 20 years experience managing innovative R&D projects across a number of different domains. A problem-solver, leader, and innovator at heart with extensive consulting and business development practice, he has an accomplished record of delivering high-quality outcomes for complex problems and vast experience in guiding stakeholders through all stages of designing and deploying analytics-related solutions.
- Combining thought leadership and considerable experience in senior management positions, Luigi has the proven ability to direct strategy and drive change to an organisation’s value proposition, vision, and processes. Luigi has past experiences building and leading high-performing teams, working in large cross-matrix organisations, and P&L management of independent business units.
Key Skills
- Multi-objective optimisation
- Agent-based modelling and simulation
- Adaptive learning and opponent modelling
- Supply chain modelling and optimisation
- Variability and robustness simulation and optimisation
- Anomaly detection and pattern recognition
- Emergent behaviour and system dynamics
Past Roles
- WA Enterprise Analytics and Performance Practice Manager, ASG Group
- Senior Manager, EY
- Chief Scientist (Supply & Demand Optimisation), Schneider Electric
- Director Simulation & Optimisation, SolveIT Software
- Academic, The University of Western Australia
Education and Qualifications
- PhD (Computer Science), The University of Western Australia
- Bachelor of Science (First Class Honours), The University of Western Australia
Awards and Recognitions
- Early Career STEM Professional, South Australian Science Excellence Awards
- Leadership Excellence Acceleration Program, Schneider Electric
- Senior Edison Technical Expert, Schneider Electric
- Outstanding Contribution to Student Learning, Faculty Teaching Awards, The University of Western Australia
- Michael Lennon Award for Outstanding Service, ACM International Collegiate Programming Competition
- Tang Computer Science Prize (Best Final Year Student in Computer Science), The University of Western Australia
Clients and Projects
- Supply chain activity scheduling, Roy Hill Iron Ore
- Port operations activity scheduling, BHP Billiton
- Supply and outage variability simulation, Roy Hill Iron Ore
- Crew rostering, Pacific National Coal
- Manufacturing plant activity scheduling, Nufarm Australia
- Maintenance planning, ElectraNet
- Wheat blend optimisation, CBH Group
- Life-of-mine asset planning, Rio Tinto Pilbara Iron
Publications
- M. Wittkamp, L. Barone, P. Hingston, and L. While, “Noise tolerance for real-time evolutionary learning of cooperative predator-prey strategies”. In the IEEE Conference on Computational Intelligence & Games, 2012
- M. Behdad, L. Barone, M. Bennamoun, and T. French, “Nature-inspired techniques in the context of fraud detection”, IEEE Transactions on Systems, Man, and Cybernetics – Part C: Applications and Reviews, Vol. 42, No. 6, 2012
- P. Hingston, L. Barone, and Z. Michalewicz (eds), Design by Evolution, Springer, 2008
- P. Hingston, D. Dyer, L. Barone, T. French, and G. Kendall, “Opponent modelling, evolution, and the iterated prisoners’ dilemma”, The Iterated Prisoner’s Dilemma: 20 Years On, World Scientific, 2007
- S. Huband, D. Tuppurainen, L. While, L. Barone, P. Hingston, and R. Bearman, “Maximising overall value in plant design”, Minerals Engineering, Vol. 19, No. 15, 2006

IAN SCRIVEN, PHD, CTO 
Dr. Ian Scriven has a PHD in computer science and electrical engineering and significant commercial and academic experience
in the modelling, simulation, and optimisation of complex systems.
Ian has experience in a wide variety of domains, including defence, manufacturing, food & beverage, mining, power & utilities, logistics, health, and transport. He has a proven track record in consulting, product delivery, people management, and systems engineering.
Overview of Experience
- Dr. Ian Scriven has a PhD in computer science and electrical engineering and significant commercial and academic experience in the modelling, simulation, and optimisation of complex systems.
- Ian has experience in a wide variety of domains, including defence, manufacturing, food & beverage, mining, power & utilities, logistics, health, and transport. He has a proven track record in consulting, product delivery, people management, and systems engineering.
- Ian has a unique ability to combine business and domain knowledge with technical understanding to deliver quality business outcomes.
Key Skills
- Computational and mathematical optimisation
- Supply chain modelling and simulation
- Behavioural/cognitive modelling and simulation
- Management consulting and business analysis
- Distributed computing and software architecture
- Project management and agile software development
- Systems engineering
Past Roles
- Manager, EY
- Principal Scientist, Schneider Electric
- Senior Optimisation Engineer, SolveIT Software
- Design Engineer, Laserdyne Technologies
- Software Engineer, Sferic
Education and Qualifications
- PhD (Simulation & Optimisation), Griffith University
- Bachelor of Engineering (First Class Honours), Griffith University
- Bachelor of Information Technology, Griffith University
Awards and Recognitions
- Edison Technical Expert, Schneider Electric
- Australian Postgraduate Award (APA) Postgraduate Research Scholarship, 2006-2009
- Australian Research Council (ARC) Top-Up Scholarship, 2008-2009
- Best Electronic Engineering Project, Griffith Industrial Affiliates Program, 2006
Clients and Projects
- Mobile resource scheduling, Home Support Services
- Inventory optimisation, SA Power Networks
- Nurse rostering, Burnside War Memorial Hospital
- Geospatial analysis & optimisation, Land Services SA
- Supply chain activity scheduling, Roy Hill Iron Ore
- Product distribution optimisation, Treasury Wine Estate
- Maintenance planning, ElectraNet
- Supply chain activity scheduling, Fortescue Metals Group
- Modelling the impact of disruptive technologies on public health, EY
Publications
- I. Scriven, J. Lu and A. Lewis, “Electronic enclosure design using distributed particle swarm optimisation”, Engineering Optimization, Vol. 45, No. 2, 2013
- I. Scriven, J. Lu and A. Lewis, “Electromagnetic noise source approximation for finite-difference time-domain modeling using near-field scanning and particle swarm optimization”, IEEE Transactions on Electromagnetic Compatibility, Vol. 52, No. 1, 2010
- A. Lewis, S. Mostighim, and I. Scriven, “Asynchronous multi-objective optimisation in unreliable distributed environments”, Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications, Springer, 2009
- I. Scriven, A. Lewis and S. Mostighim, ”Multi-objective optimisation in peer-to-peer networks”. In the IEEE Congress on Evolutionary Computation, 2009
- I. Scriven, J. Lu, and A. Lewis, “An efficient peer-to-peer particle swarm optimiser for EMC enclosure design”. In the IEEE Conference on Electromagnetic Field Computation, 2008
Advisory Committee Members
Academic Advisory Board
Asst. Prof. Adam Ghandar
Southern University
of Science & Technology
Prof. Graham Kendall
The University of Nottingham
Dr. Per Kristian Lehre
University of Birmingham
Dr. Lyndon While
The University of Western
Australia
Prof. Xin Yao
University of Birmingham
Prof. Frank Neumann
Queen Mary University
of London
Prof. Simon Lucas
Queen Mary University
of London
Discover
more about
our location
Daitum moved into Lot Fourteen in late 2018. Backed by the South Australian government as well as federal and local governments, Lot Fourteen is one of the most exciting urban renewal projects in Australia.
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