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Dr Archie Chapman is an Associate Professor in Computer Science in the School of IT and Electrical Engineering.

Archie develops and applies principled artificial intelligence, game theory, optimisation and machine learning methods to solve large-scale and dynamic allocation, scheduling and queuing problems. His recent research has focused on applications of these techniques to problems in future power systems, such as integrating large amounts of renewable power generation and using batteries and flexible loads to provide power network and system services, while making best use of legacy network and generation infrastructure.

Prior to joining UQ, Archie was Research Fellow in Smart Grids at the University of Sydney (2011-2019), and a postdoc fellow at the University of Southampton (2009-2010), where he completed his PhD.

Jerzy Filar is Emeritus Professor of Applied Mathematics. Jerzy is a broadly trained applied mathematician with research interests spanning a spectrum of both theoretical and applied topics in Operations Research, Stochastic Modelling, Optimisation, Game Theory and Environmental Modelling. Professor Filar co-authored, or authored, five books or monographs and approximately 100 refereed research papers. He has a record of research grants/contracts with agencies and research institutes such as NSF, ARC, US EPA, World Resources Institute, DSTO, FRDC and the Sir Keith and Sir Ross Smith Foundation. He is editor-in-chief of Springer’s Environmental Modelling and Assessment and served on editorial boards of several other journals. He has supervised or co-supervised 29 PhD students. Jerzy's Erdos Number is 3.

Marcus Gallagher is an Associate Professor in the Artificial Intelligence Group in the School of Information Technology and Electrical Engineering. His research interests are in artificial intelligence, including optimisation and machine learning. He is particularly interested in understanding the relationship between algorithm performance and problem structure via benchmarking. My work includes cross-disciplinary collaborations and real-world applications of AI techniques.

Dr Gallagher received his BCompSc and GradDipSc from the University of New England, Australia in 1994 and 1995 respectively, and his PhD in 2000 from the University of Queensland, Australia. He also completed a GradCert (Higher Education) in 2010.

• since 2023: Honorary Associate Professor, School of Mathematics and Physics, The University of Queensland.
• 2017-2023: Associate Professor, School of Earth and Environmental Sciences, The University of Queensland.
• 2003-2017: Deputy Director (Software), Earth System Sciences Computational Center (ESSCC) & School of Earth Sciences, The University of Queensland.
• 2001-2003: Computational Scientist, CSIRO Mathematical and Information Sciences Division, Melbourne, Australia.
• 2000-2001: Lecturer, Institute of Information and Mathematical Sciences, Massey University at Albany, Auckland, New Zealand.
• 1996-1999: Research Fellow, Center for Mathematics and its Applications, School of Mathematical Sciences, Australian National University (ANU), Canberra.
• 1989-1996: Research Scientist, Computing Center, University of Karlsruhe/Germany.

Links:

• LinkedIn
• researchgate.net
• Editor: Geoscientific Model Development Journal (GMD), http://www.geoscientific-model-development.net & EGUsphere https://www.egusphere.net/
• Australian Mathematical Society, ANZIAM

I am a Senior Lecturer in Mathematical Data Science, at School of Mathematics and Physics, The University of Queensland. I obtained my BSc degree in Mathematics and Applied Mathematics, from Beijing Normal University in 2006. I obtained my MPhil and PhD degrees from City University of Hong Kong in 2008 and 2011 respectively, where I was working as a research fellow from Oct 2011 to Feb 2013. During Feb 2013 -- Aug 2014, I was working as a postdoctoral associate at Department of Statistical Science, Duke University. Before joining UQ in Jan 2022, I worked at Hong Kong Polytechnic University. My research interests cover statistical learning theory (kernel methods, stochastic gradient methods, support vector machine, pairwise learning, online learning, error analysis, sparsity analysis, and the implementation of algorithms), mathematical data science, and their applications to artificial intelligence, immunological bioinformatics, systems biology, and computational social science.

Dirk Kroese's research interests are in: Monte Carlo methods, rare-event simulation, the cross-entropy method, applied probability, and randomised optimisation.

Dirk Kroese is a professor of Mathematics and Statistics at the School of Mathematics and Physics of the University of Queensland. He has held teaching and research positions at The University of Texas at Austin, Princeton University, the University of Twente, the University of Melbourne, and the University of Adelaide. His research interests include Monte Carlo methods, adaptive importance sampling, randomized optimization, and rare-event simulation. He has over 120 peer-reviewed publications, including six monographs:

• Rubinstein, R.Y., Kroese, D.P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning, Springer, New York.
• Rubinstein, R. Y. , Kroese, D. P. (2007). Simulation and the Monte Carlo Method, 2nd edition, John Wiley & Sons.
• Kroese, D.P., Taimre, T., and Botev, Z.I. (2011). Handbook of Monte Carlo Methods, Wiley Series in Probability and Statistics, John Wiley & Sons, New York.
• Kroese, D.P. and Chan, J.C.C. (2014). Statistical Modeling and Computation, Springer, New York.
• Rubinstein, R. Y. , Kroese, D. P. (2017). Simulation and the Monte Carlo Method, 3rd edition, John Wiley & Sons.
• Kroese, D.P., Botev, Z.I., Taimre, T and Vaisman, R. (2019) Data Science and Machine Learning: Mathematical and Statistical Methods, Chapman & Hill/CRC.
• Kroese, D.P. and Botev, Z.I. (2023). An Advanced Course in Probability and Stochastic Processes, Chapman & Hill/CRC.

Professor Mobli is a structural biologist and a group leader at the University of Queensland's Australian Institute for Bioengineering and Nanotechnology (AIBN). He is well known internationally for his contributions to the basic theory of multidimensional nuclear magnetic resonance and its applications to resolving the molecular structure of peptides and proteins, as well as studying their physiochemical properties and function. Mehdi's contributions to the field has been recognised by being appointed an Executive Editor of the AMPERE society's journal "Magnetic Resonance", and to the advisory board of the international Biological Magnetic Resonance Data Bank (BMRB) as well as serving on the board of directors of the Australia and New Zealand Society for Magnetic Resonance (ANZMAG). He is a former ARC Future Fellow and recipient of the ASBMB MERCK medal, the Australia Peptide Society's Tregear Award, the ANZMAG Sir Paul Callaghan medal and the Lorne Proteins Young Investigator Award (now Robin Anders Award).

Prof. Mobli's research group focuses on characterising the structure and function of receptors involved in neuronal signalling, with a particular focus on developing new approaches for the discovery and characterisation of modulators of these receptors through innovations in bioinformatics, biochemistry and and biophysics. This work has led to publication of more than 100 research articles attracting over 6,000 citations.

Dr Evgenii Nekhoroshev is a Postdoctoral Research Fellow at the School of Chemical Engineering and a member of the Pyrometallurgy Innovation Centre led by Prof. Evgueni Jak.

He graduated with a Master in Chemistry (chemical thermodynamics) from Lomonosov's Moscow State University, Deparment of Chemistry in 2012. His Master's Thesis was "Thermodynamic optimization of the NaOH-Al(OH)3-Na2SiO3-H2O system for applications in Bayer's process of bauxite treatment" as part of a bigger project initiated in collaboration with Rusal company aimed at utilisation/valorisation of red mud residues accumulated during the production of aluminium oxide from bauxite ores.

In 2019, he completed a PhD in Metallurgical Engineering at Ecole Polytechnique of Montreal, Canada within The Centre For Research in Computational Thermodynamics (CRCT), where he acquired expertise in FactSage software, multicomponent database development, and was included in the list of official collaborators of FactSage. His PhD thesis was "Thermodynamic optimization of the Na2O-K2O-Al2O3-CaO-MgO-B2O3-SiO2 system" sponsored by Glass Consortium including Corning and SCHOTT glass producers. The purpose of the database he developed was to assist the industry in designing new glasses with special properties: chemically hardened glasses (smartphones), technical glasses with high thermal and chemical resilience (boron-containing glasses), chemically inert glasses, etc.

Short after receiving his PhD, Dr Evgenii Nekhoroshev accepted a position at The University of Queensland as part of the Pyrometallurgy Innovation Centre's team where he has an official title of Theme Leader in Thermodynamic Computations, combining his broad expertise in metallurgy, chemical engineering, applied mathematics, and programming.

Dr Evgenii Nekhoroshev has always been passionate about formalisation and automation of big research tasks. He started working on developing an automated solver for thermodynamic optimisation during his PhD thesis which was improved and finalised using the ideas of Prof. Evgueni Jak about real-time derivative matrix optimization and sensitivity analysis applicable to large multicomponent systems. His contribution to the Centre allowed to make transition to a continuous optimization approach when experimental and modelling streams of work in the Centre are efficiently combined together. It allows to include the most recent experimental datasets into a self-consistent database update with minimal time delays.

I studied Technical Mathematics at the Vienna University of Technology. I also earned a Master's degree in Law and I finished the first ("non-clinical") part of Medical Studies at the University of Vienna. I earned my PhD in Applied Mathematics at the University of Vienna in 2007. My PhD advisor was Christian Schmeiser, my co-advisor was Peter Markowich. I spent several months at the University of Buenos Aires working with C. Lederman and at the ENS-Paris rue d'Ulm in the group of B. Perthame.

Before coming to UQ, I held post-doc positions at the Wolfgang Pauli Insitute (Vienna), University of Vienna and the Austrian Academy of Sciences (RICAM). In 2013 I won an Erwin Schrödinger Fellowship of the Austrian Science Fund (FWF). I was a post-doc researcher in the group of Alex Mogilner first at UC Davis, then at the Courant Institute of Math. Sciences (New York University).

I research extrasolar planets - planets around other stars - and focus on developing and applying new data science approaches for detecting and characterizing them. I have taken nearly every approach to exoplanet and stellar observation, including transits, radial velocities, direct imaging, and asteroseismology.

As an ARC DECRA Fellow I'm mainly working on exoplanet direct imaging with the James Webb Space Telescope, and especially how we can use differentiable & probabilistic programming to enhance data analysis to detect faint objects in noisy data. I also work on radio astronomy to study planets' magnetic interactions with their host stars, and using radiocarbon in tree rings as a tracer of long term solar activity.

I grew up in Sydney, New South Wales, and studied for my Honours and Masters at the University of Sydney. I studied abroad at the University of California, Berkeley, and in 2017 I completed my DPhil in Astrophysics at Balliol College, Oxford. From 2017-20 was a NASA Sagan Fellow at the NYU Center for Cosmology and Particle Physics and Center for Data Science. I'm now a Lecturer in Astrophysics and DECRA Fellow at the University of Queensland.

I'm into open source, open science, and climate action. I was a member of the winning Balliol College team in the 2016-17 series of University Challenge on BBC2, with the wonderful Joey Goldman, Freddy Potts, and Jacob Lloyd. Sometimes I write: see my latest piece in The Monthly, about the possible discovery of phosphine on Venus.

Dr Zhenjiang You is a Senior Lecturer within the School of Chemical Engineering. He holds a PhD in Fluid Mechanics. He conducts research on mathematical modelling, numerical simulation and experimental study of flows in porous media, and their applications in petroleum/chemical/mechanical/mining/civil engineering, energy, environment and water resources. He develops new theories and models for colloidal/suspension transport in porous media, innovative technologies for enhanced gas/oil production, and applicable tools for reservoir engineering, production engineering and geothermal industry. He has received research funding support from ARC, NERA, DMITRE, ARENA and a range of Australian and international companies. He collaborates with researchers in Australia, Germany, Denmark, the Netherlands, China, Russia, USA, Brazil and Iran.

His teaching contributions include Reservoir Engineering, Well Test Analysis, Reservoir Simulation, Field Design Project, Mathematical Modelling and Fluid Mechanics for Petroleum Engineers, Formation Damage, Enhanced Oil and Gas Recovery, Unconventional Resources and Recovery, etc.