IJCAI 2016 TUTORIAL: Research Challenges in Computational Sustainability


Monday July 11th, 1:45pm-3:30pm
Organizers: Stefano Ermon (Stanford); Bistra Dilkina (Georgia Tech) 

The goal of computational sustainability research is to develop computational approaches to help balancing environmental, economic, and societal needs for sustainable development. Research in computational sustainability is interdisciplinary, bringing together computational sciences and other fields such as environmental sciences, economics, and sociology. AI techniques and methodologies can be instrumental in addressing sustainability questions in these domains, for example to increase the efficiency and effectiveness of the way we manage and allocate our natural and societal resources.


This tutorial will provide an overview of the field of computational sustainability. We will introduce the key research questions by discussing a number of recent results. These will include problems in biodiversity and conservation, natural resource management, renewable energy, and poverty mitigation in developing countries. Through these examples, we will highlight some of the key computational challenges at the core of computational sustainability, as well as new concepts and methods to address them, drawing from optimization, decision making under uncertainty, and machine learning.


Outline:

1) Overview of Computational Sustainability (Bistra Dilkina)

2) Machine Learning techniques for Sustainability Applications (Stefano Ermon)

3) Optimization and Decision Making for Sustainability Applications (Bistra Dilkina)




Assistant Professor of Computational Science and Engineering

Fellow of the Brook Byers Institute for Sustainable Systems

Georgia Institute of Technology


Bistra Dilkina is an assistant professor in the College of Computing at the Georgia Institute of Technology. She received her PhD from Cornell University in 2012, and was a Post-Doctoral associate at the Institute for Computational Sustainability until 2013. Her research focuses on advancing the state of the art in combinatorial optimization techniques for solving real-world large-scale problems, particularly ones that arise in sustainability areas such as biodiversity conservation planning and urban planning. Her work spans discrete optimization, network design, stochastic optimization, satisfiability, and machine learning. Bistra has (co-)authored over 20 publications, and has won several awards, including Best Paper of the 2011 INFORMS ENRE Section, Lockheed Inspirational Young Faculty Award, Raytheon Faculty Fellowship, and Georgia Power Professor of Excellence Award. She is also the co-director of the Atlanta Data Science for Social Good (DSSG) program, which partners multi-disciplinary student teams with local, government, and non-profit organizations to solve some of their most difficult problems using data science techniques such as analytics, modeling, and prediction. She has co-chaired the AAAI 2015 Workshop on Computational Sustainability, co-organized the 2016 Computational Sustainability Conference, and is a co-chair for the upcoming AAAI 2017 Special Track on Computational Sustainability.



Stefano Ermon

Assistant Professor of Computer Science

Fellow of the Woods Institute for the Environment

Stanford University


Stefano Ermon is currently an Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory. He completed his PhD in computer science at Cornell in 2015. His research interests include techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. Stefano has (co-)authored over 20 publications, and has won several awards, including two Best Student Paper Awards, one Runner-Up Prize, and a McMullen Fellowship.