Areas of Expertise
- Combinatorial Optimization
- Computational Economics
- Computational Models For Electronic Business Models
- Computational Models For Optimization
- Computational Sustainability
- Materials Discovery
- Mathematical Programming
- Resource Environment Economics
- Applied Economics and Management
- Computer Science
- Information Science
- Doctorate University of Edinburgh, 1993
- Master of Science University of Lisbon, 1987
- Bachelor of Science University of Lisbon, 1982
Carla Gomes is a Professor of Computer Science at Cornell University, with joint appointments in the Dept. of Computer Science, Dept. of Information Science, and the Dyson School of Applied Economics and Management. Gomes obtained a Ph.D. in computer science in the area of artificial intelligence and operations research from the University of Edinburgh. She also holds an M.Sc. in applied mathematics from the University of Lisbon. Her research has covered several areas in artificial intelligence and computer science, including the integration of constraint reasoning, operations research, and machine learning techniques for solving scale constraint reasoning and optimization problems, complete randomized search methods, and algorithm portfolios, planning and scheduling, and multi agent systems. Gomes’s central research themes are the integration of concepts from constraint and logical reasoning, mathematical programming, and machine learning, for large scale combinatorial problems; the study of the impact of structure on problem hardness; and the use of randomization techniques to improve the performance of exact (complete) search methods. More recently, Gomes has become deeply immersed in research in the new field of Computational Sustainability. Gomes is the Lead PI of an NSF Expeditions in Computing award on Computational Sustainability and the director of the newly established Institute for Computational Sustainability at Cornell University. Gomes is a Fellow of the Association for the Advancement of Artificial Intelligence.
My research area is Artificial Intelligence with a focus on large-scale constraint-based reasoning and optimization. I exploit connections between different research areas --- in particular artificial intelligence, operations research, and the theory of algorithms. Central themes of my research are: (1) the synthesis of formal and experimental research for understanding and exploiting problem structure, (2) the integration of concepts from constraint reasoning and mathematical programming, and (3) the use of randomization techniques to scale up the performance of complete (exact) search methods . I combine formal analysis with the study of applications such as planning, scheduling, combinatorial design, and multi-agent systems. Recently, I have become deeply immersed in the establishment of new field of Computational Sustainability.
Computational Sustainability is a new interdisciplinary research field, with the overarching goal of studying and providing solutions to computational problems for balancing environmental, economic, and societal needs for a sustainable future. Such problems are unique in scale, impact, complexity, and richness, often involving combinatorial decisions, in highly dynamic and uncertain environments, offering challenges but also opportunities for the advancement of the state-of-the-art of computer and information science. Work in Computational Sustainability integrates in a unique way various areas within computer science and applied mathematics, such as constraint reasoning, optimization, learning, and dynamical systems. The research necessarily entails a cross-fertilization of approaches and ideas from several research communities, bringing together computer scientists, biologists and environmental scientists, biological and environmental engineers, sociologists, and economists. Concrete examples of computational sustainability challenges range from to planning and optimization for wildlife preservation and biodiversity conservation, to poverty mapping, to the design of intelligent or ”smart” control systems for energy-efficient buildings, to balancing portfolios of renewable energy sources.
In 2008, under the NSF Expeditions in Computing program, we created the Institute for Computational Sustainability (ICS) to forge a highly interdisciplinary effort to nurture the field of Computational Sustainability. Our vision is that computer science can --- and should --- play a key role in increasing the efficiency and effectiveness of the way we manage and allocate our natural resources. The plethora of challenging computational research questions posed by sustainability problems, pushing the boundaries of current computational methods, also provides an exciting way to broaden and advance the state-of-the-art of computer science.
During 2013, I have continued my research around a series of computational themes driven by sustainability topics. In particular my research addresses questions concerning graph connectivity (e.g., to address questions concerning landscape connectivity for wildlife conservation), stochastic optimization (e.g., how to plan wildlife corridors over time and considering climate change), reasoning with hard and soft constraints (e.g., to identify phase diagrams of combinations of materials based on electromagnetic x-ray diffraction patterns that are very noisy), and how to use crowdsourcing and citizen science to boost combinatorial reasoning (e.g., crowdsourcing the identification of so-called backdoor variables by inspection of heat maps, that speed up solvers when identifying the phase diagrams for materials discovery). During this reporting period, with my students and collaborators, we produced 14 refereed publications which appeared in a variety of conference proceedings and journals (AAAI, IJCAI, NIPS, CP, CPAIOR, etc...).
Outreach and Extension Focus
A key component of ICS’s research agenda is to engage worldwide researchers in the new field of computational sustainability, building a vibrant research community far beyond the members of the NSF expedition. To that end I am involved in a multitude of community building activities. For example, I chaired the Special Track on Computational Sustainability at AAAI and the theme of IJCAI was AI and Computational Sustainability. I also chaired a special track at IJCAI-2013 on Computational Sustainability, organizing invited talks and giving a tutorial on computational sustainability. The special tracks at AAAI and IJCAI feature Computational Sustainability Awards for the best papers through a partnership with the Computing Community. I also co-chaired the 10th International Conference on CPAIOR at IBM Watson in May, 2013. This conference also includes a Master Class on Computational Sustainability. I’m also working on a joint project for an online book on computational sustainability, editing a special issue of the AI magazine on computational sustainability, and writing a review article for CACM on computational sustainability.
Awards and Honors
- Fellow (2014) American Academy for the Advancement of Science
- Chair Elect, Information, Computing, and Communication (2015) American Association for the Advancement of Science
- Co-chair of the 10th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) techniques in Constraint Programming (CPAIOR 2013) (2013)
- Joint External Advisory Board member, National Science Foundation Expeditions in Computing, SCoPe: Societal-scale Cognition through Pervasive Awareness (2013)
- Lead P.I., NSF Expeditions on Computing Award ($10M). Computational Sustainability: Computational Methods for a Sustainable Environment, Economy, and Society (2013)
- Ermon, S., Xue, Y., Toth, R., Dilkina, B., Bernstein, R., Clark, P., DeGloria, S. D., Mude, A., Barrett, C., & Gomes, C. P. (2015). Learning Large Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa. Proceedings of the Twenty-Ninth Conference on Artificial Intelligence, Special Track on Computational Sustainability. AAAI.
Presentations and Activities
- Spatially-balanced designs on autocorrelated fields. Joint Statistical Meetings. 2004.