WELCOME TO THE  WASSWA LAB FOR ENVIRONMENTAL CHEMOINFORMATICS

Nature contains an enormous amount of chemical information. When environmental systems are examined using modern analytical methods, whether natural waters, soils, sediments, or biological systems, they generate complex molecular datasets that capture only part of the chemistry occurring within them. The same is true for synthetic and engineered systems, including plastics, petroleum derived materials, industrial chemicals, and water and wastewater treatment processes, where complex mixtures, reactions, and transformation products can generate far more information than we routinely use. Advances in analytical chemistry have greatly expanded our ability to measure this complexity, while developments in machine learning (ML) and artificial intelligence (AI) provide new opportunities to extract knowledge from these measurements and connect observations that are difficult to interpret using conventional approaches alone.1,2

My research is motivated by the opportunity to unlock more of the scientific information contained in these complex systems. I combine experimental environmental science and analytical chemistry with molecular data science and AI to identify patterns within complex measurements, connect those patterns to underlying chemical and environmental processes, and use the resulting knowledge to guide subsequent experiments and scientific questions