As a founder and CTO of DataPond, I lead the development of AI-based water quality sensors to monitor e fecal coliforms and other pollutants in drinking water sources. DataPond's sensors use a novel method that applies a deep neural network model to give a binary answer for the presence or absence of fecal coliforms, using a minimum of water quality and geographical parameters that can be measured in real time with low-cost and in-situ equipment. This method can reduce the time gaps between routine lab testing and improve drinking water quality and safety, addressing the SDG 6 targets.I am also a Ph.D. candidate in Environmental Engineering at Tel Aviv University, where I conduct research on water quality modeling and analysis under the supervision of Prof. Hadas Mamane. I have a strong background in data science, machine learning, and deep neural networks, as well as a double major in Mechanical Engineering and Earth Sciences, with an emphasis on Environmental Studies. My goal is to find, develop, and test innovative ways to better and quickly understand what is in the water, except for H2O.