USA - 2021
For establishing and nurturing the field of Computational Sustainability and for foundational contributions to Artificial Intelligence
Carla Gomes is a leader in AI, particularly in reasoning, optimization, and the integration of learning and reasoning. She is the driving force behind the new subfield of Computational Sustainability, embodying the values of multidisciplinary research and social impact. Her research advances core computer science and AI while establishing rich connections to other disciplines.
Carla Gomes has played a key role in advancing the integration of methods from AI and Operations Research. With collaborators, she pioneered randomized restarts and algorithm portfolios for combinatorial solvers. This work has had a tremendous practical impact on solvers for satisfiability (SAT), mixed integer programming (MIP), and satisfiability modulo theories (SMT). Gomes discovered and characterized heavy-tailed runtime distributions and backdoor variables in combinatorial search, explaining the large runtime variations of combinatorial solvers. She also introduced XOR-streamlining, a novel strategy for model counting that was a key step to further advances in efficient probabilistic inference.
Inspired by her early work on experiment design for nitrogen management and wildlife-corridor design, Gomes conceived an ambitious vision for Computational Sustainability: a highly interdisciplinary research area injecting computational thinking to solve critical sustainability challenges while advancing the field of computer science. As the lead PI of two NSF Expeditions awards, Carla Gomes has grown Computational Sustainability into a robust and vibrant subfield. She has shown that addressing challenges in sustainability often leads to transformative research in computer science, in addition to having a significant practical impact. Gomes and her collaborators developed a framework for computing the high-dimensional Pareto frontier of ecological and socio-economic tradeoffs of hydro dam expansion in the Amazon. Gomes also pioneered the use of AI in Materials Discovery. Together with her team, she developed Deep Reasoning Networks, a novel computational paradigm integrating deep learning with constraint reasoning over rich prior knowledge. This framework was used to solve the crystal-structures phase-mapping problem, which led to the discovery of new solar fuel materials for sustainable energy storage.
USA - 2017
For establishing the field of computational sustainability, and for foundational contributions to artificial intelligencePress Release