Program > Keynote speakers

Bias Correction in Climate Studies 3rd workshop will feature key speakers who are experts in cutting-edge scientific topics, offering in-depth insights into the latest advancements in their fields.

List of confirmed keynote speakers :

• Faranak Tootoonchi, Swedish University of Agricultural Sciences - SLU (Sweden), Cornell University (USA), "Uni- and multivariate bias correction methods for hydrological simulations: Trade-offs between complexity and performance"

Faranak is a postdoc at the Swedish University of Agricultural Sciences (SLU - Sweden), currently visiting the department of earth and atmospheric sciences at Cornell University (USA). She works with statistical methods with different levels of complexity to understand climate change impacts on various processes and to forecast future impacts. Currently, she looks into changing winter climate conditions in high-latitudes and explore how these changes cascade into other seasons and impact the agricultural sector. She received her PhD in 2022 from Uppsala University (Sweden), with the thesis focusing on comparison of different bias correction methods for hydrological applications in the Nordic region.

• Gerhard Krinner, Institute of Environmental Geosciences - CNRS (France), "Empirical run-time bias corrections for global climate projections"

Gerhard Krinner is a CNRS senior scientist at IGE Grenoble. He has been mainly working with atmospheric and surface model on questions related to high-latitude climate (ice-sheet - climate interactions, seasonal snow cover, permafrost carbon feedback, etc.). More recently, he became interested in run-time bias corrections in atmospheric models, particularly for climate projections. He was an IPCC lead author in the 5th and 6th assessment cycles and coordinated in particular the long-term change section in the AR6 Synthesis Report (2023).

• Zhong Yi Wan, Google Research (United States of America), "Bridging the Gap: Correcting Simulation Biases via Generative Distribution Matching"

Zhong Yi Wan is a Research Scientist at Google Research whose work bridges the gap between advanced AI models and complex physical systems, with a particular emphasis on climate downscaling. His research aims to significantly improve the efficiency and accuracy of risk assessments for high-impact weather events like heat waves and cyclones. Rooted in the intersection of machine learning and dynamical systems, he received his PhD in Mechanical Engineering and Computations from the Massachusetts Institute of Technology (MIT) in 2020.

• Ashish Sharma, University of New South Wales (Australia), "Boundary Corrected Regional Climate Modelling – Can corrections address the Curse of Dimensionality?"

Ashish Sharma is a Professor of Hydrology and Water Resources at the University of New South Wales, Sydney. Ashish’s research focuses on uncertainty in natural systems, with a focus on the problems of sustained drought and flood anomalies, both worsening as we head to warmer and warmer climates. Ashish is a also a proud supervisor to 43 completed PhDs, 5 of whom are respected academics in Go8 Australian Universities, many others in equally respected universities and organisations worldwide, with 3 awarded competitive fellowships indicative of the research standing they have developed. Ashish also leads UNSW’s Water Resources program, ranked 9th internationally and 1st in Australia.