We are delighted to congratulate Nicolas Lazaro on winning 3rd prize in the Swissmem Best Thesis Award - Environmental Technology, a national distinction celebrating outstanding Bachelor’s and Master’s theses for their innovative contributions in the field of environmental engineering.
Nicolas completed his Master’s thesis “Advancing Operational Hydrology Through Deep Transfer Learning: Multi-Day Streamflow Forecasting in Central Asian Mountains” at ETH Zurich, supervised by Prof. Peter Molnar (ETH) and Dr. Tobias Siegfried (hydrosolutions), while being hosted at hydrosolutions. His thesis explored how deep learning and transfer learning—including global pre-training on up to 6,690 catchments from the Caravan dataset—can enhance operational streamflow forecasting in data-scarce mountainous regions.
His research contributes to the rapidly evolving field of machine learning in hydrology and aligns closely with our ongoing efforts to deploy advanced digital water tools in the region.
At hydrosolutions, we are particularly proud that Nicolas’ thesis connects directly with our applied work on deep learning for operational discharge forecasting in Central Asia, part of the SAPPHIRE programme. Learn more about our work on deep learning for hydrology here.
We warmly congratulate Nicolas on this well-deserved recognition and are proud to have him on our team. His work exemplifies the combination of academic excellence at ETH Zurich and applied innovation fostered at hydrosolutions.
