Homepage of Aneta Neumann

Aneta Neumann Optimisation and Logistics School of Computer Science Ingkarni Wardli, Office 4.56 The University of Adelaide Adelaide, SA 5005, Australia Phone: +61 8 8313 66377 email: aneta.neumann@adelaide.edu.au Researcher Profile LinkedIn Researcher at Optimisation and Logistics

  Research Interests

• artificial intelligence
• evolutionary diversity optimization
• evolutionary computation
• optimization
• defense and cybersecurity
• mining, energy and ressources
• computational creativity

  Current and Recent Activities

• 4 Papers accepted at PPSN 2022.
• Paper accepted at Theoretical Computer Science.
• Best Paper Nomination for the work On the Use of Quality Diversity Algorithms for the Traveling Thief Problem, A. Nikfarjam, A, Neumann, F. Neumann at the GECCO 2022 (Track Evolutionary Combinatorial Optimization and Metaheuristics).
• 5 Papers accepted at GECCO 2022.
• Paper accepted at AAAI 2022.
• Tutorial "Evolutionary Submodular Optimisation" at GECCO 2022.
• Tutorial "Evolutionary Diversity Optimisation for Combinatorial Optimisation" at GECCO 2022.
• 6 Papers accepted at GECCO 2021.
• Paper accepted at Artificial Intelligence Journal (AIJ).
• Papers accepted at LION 2021 and FOGA 2021.
• Best Paper Nomination for the work Analysis of Evolutionary Diversity Optimisation for Permutation Problems, A.V Do, M. Guo, A, Neumann, F. Neumann at the GECCO 2021 (Track Genetic Algorithms).
• Tutorial "Evolutionary Submodular Optimisation" at GECCO 2021.
• Tutorials "Evolutionary Computation for Digital Art" and "Evolutionary Diversity Optimisation" at IEEE CEC 2021.
• Chair of the "Real World Applications Track" at GECCO 2021 (with Richard Allmendinger).
• Co-organiser of Special Issue of Theoretical Computer Science "Theoretical Foundations of Evolutionary Computation" (with Per Kristian Lehre and Chao Qian), Submission Deadline: December 31, 2021.
• The 2020 Lorentz Center Workshop: Benchmarked: Optimization meets Machine Learning, 9-13 November 2020.
• Co-organiser of Special Session at WCCI 2020 - Theoretical Foundations of Bio-inspired Computation (with Per Kristian Lehre and Chao Qian).
• Tutorial "Evolutionary Diversity Optimisation" at PPSN 2020.
• Tutorial "Evolutionary Computation for Digital Art" at GECCO 2020.

  Teaching

• Evolutionary Computation, Lecturer and Course Coordinator, University of Adelaide, Australia
• Working with Big Data, Pearson Online Master of Data Science, University of Adelaide, Australia
• Big Data Fundamentals MOOC's course, University of Adelaide, Australia
• Mining Big Data, Lecturer, School of Computer Science, University of Adelaide, Australia
• Master of Computing and Innovation, Lecturer, School of Computer Science, University of Adelaide, Australia

  Publications

• List of Publications
• DBLP, Google Scholar, ORCID, Scopus

  Current Honours, Masters, and PhD Student's Projects 2022/2023

• Project title: Evolutionary Diversity Optimisation: Project description: Diversity optimisation is beneficial to many industrial application areas as it provides a large variety of high quality and innovative design choices. Diversity can drive innovation and deliver promising results in complex problems and optimisation. You will design and analyse algorithms for computing a diverse set of solutions that all meet given quality criteria, and explore the impact of different diversity strategies. The project is suitable for a student interested both in a career in research or in industry.


• Project title: Artificial Intelligence - Innovative approaches for increasing the productivity of South Australia’s copper and gold production. Project description: Artificial Intelligence is currently used in various ways to solve significant industry challenges. The students will develop advanced technologies to help boost South Australia’s copper and gold production. The topic spans from experimental investigations of algorithms to data analysis using machine learning methods. The projects can be carried out dependent on the background and interest of the students.


• Project title: Advanced Ore Mine Optimisation under Uncertainty. Project description: Mining processes involve a lot of uncertainties due to the lack of information about ore grades within the ore body. Using an average model or an average gold/copper price leads to weakness/limitation of models that does not take into account the effect of potentially large losses due to deviations from the expected value. In order to improve the estimate of a mining project’s value you will model the uncertainty and establish confidence intervals for optimised solutions. The topic spans from experimental investigations of algorithms for ore grade estimation and optimisation of mine design and scheduling to data analysis based on machine learning (e.g. deep neural networks). The project is suitable for a student interested both in a career in research or in industry.


• Project title: AI-based Computational Creativity. Project description: Project description: Can computer be capable of human-level creativity? Is artificial intelligence set to become next the great art/music movement? Artificial intelligence is substantially changing the nature of creative processes. The students will explore the interface between art, music and artificial intelligence. For example, evolutionary image transition can be utilised as inspiration for creating original digital art and videos. The focus will be on developing new tools using machine learning, neural networks and optimisation. The projects can be carried out dependent on the background and interest of the students.


• Students who are interested in this research topics are very welcome to contact me: aneta.neumann@adelaide.edu.au.
  非常欢迎对我的研究主题感兴趣的学生与我联系

Page last modified: Januar 13, 2023.