AMEMR 2017 Keynote presenters

 We are pleased to announce the exciting line up of keynote speakers for AMEMR 2017. Keynotes will open each theme throughout the conference.

Beth Fulton

Beth obtained her BSc (with first class Honours jointly in Mathematics and Marine Biology) from James Cook University in Townsville in 1997 and her PhD on ‘The effects of the structure and formulation of ecosystem models on model performance’ at the University of Tasmania in 2000.

She joined CSIRO in 2001 as a postdoctoral Fellow, looking into robust indicators of the ecological effects of fishing. It was at this time she applied the lessons learnt in her PhD to begin the serious development of the ecosystem model Atlantis and to begin co-developing InVitro. She was appointed to CSIRO as a research scientist in 2004, eventually taking up leadership of the ecosystem modelling and development team.

Kevin Flynn
From Sublime Simplicity to Enigmatic Mega Models; sharing knowledge and responsibilities

Kevin is a plankton researcher who divides his efforts 50:50 between experimental work and modelling of systems dynamics (though shifting more to the latter!). Both avenues have explored different plankton types, from autecology through to ecology (HABs, ocean acidification etc.), with applied work on algal biofuels. Emphasis in modelling is placed on replicating the essence of the dynamics of physiology and biochemistry, exploring hitherto under-represented facets, questioning simplifications and proposing alternatives. More can be found here - https://www.researchgate.net/profile/Kevin_Flynn4. Kevin Flynn is a Professor at Swansea University in the UK.

Stephanie Dutkiewicz

Stephanie is a principal research scientist at the Massachusetts Institute of Technology. She received a BSc (physics) from University of Miami and a PhD (oceanography) from the University of Rhode Island. Her research interests lie at the intersection of the marine ecosystem and the physical and biogeochemical environment. She is involved in developing and using complex numerical models as part of the MIT Darwin Project (http://darwinproject.mit.edu). Much of her recent work has been in understanding the patterns of, and controls on the diversity of phytoplankton. This has led model development to include the representation of diverse phytoplankton communities, guided by laboratory, field and satellite observations and theoretical frameworks. Additionally she is interested in understanding how phytoplankton communities might change in a warming world, as part of her affiliation with the MIT Center for Global Changes Science.

Manuel Barange (TBC)

Professor Manuel Barange is the Director of the Fisheries and Aquaculture Policy and Resources Division at the Food and Agriculture Organisation, Rome, Italy.  Manuel's expertise includes physical/biological interactions, climate and anthropogenic impacts on marine ecosystems, fish ecology, behaviour and trophodynamics, and fisheries assessment and management. In recent years, he has increasingly focused his research on the impacts of climate change and economic globalization on marine-based commodities, and on the interactions between natural and social sciences in fisheries, ecosystems and climate change, in the developed and developing world. Manuel was awarded the 2010 UNESCO-IOC Roger Revelle Medal for his accomplishments and contributions to ocean science.

Thomas Kiørboe

Thomas is a Professor at the National Institute for Aquatic Resources, Technical University of Denmark.

Further information will be coming soon.

Ketil Malde

Machine intelligence and the data-driven future of marine science

Dr Malde works as a bioinformatician at the Institute of Marine Research in Norway, where he has struggled with big data challenges related to molecular biology, functional genomics, and population genetics for more than a decade.  He is also an associate professor in informatics at the University of Bergen, where he teaches artificial intelligence and machine learning algorithms.  He is currently working to apply technologies from the field of machine learning to meet current and future big data challenges in the marine sciences.