Computational Sustainability | CSE 8803 CompSust

Nonexhaustive list of papers for the course

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Dynamic Conservation Planning

Dynamic Reserve Site Selection


A scenario optimization model for dynamic reserve site selection


2015 Incorporating dynamic distributions into spatial prioritization


2015 Sequential Decision Making in Computational Sustainability via Adaptive Submodularity


Dynamic Reserve Selection: Optimal Land Retention with Land-Price Feedbacks


Does conservation planning matter in a dynamic and uncertain world?


Building a Regionally Connected Reserve Network in a Changing and Uncertain World


Conservation planning with dynamic threats: The role of spatial design and priority setting for species’ persistence


General rules for managing and surveying networks of pests, diseases, and endangered species



Biodiversity Conservation

[Biodiversity|Optimization] Wildlife Corridors as a Connected Subgraph Problem. Jon Conrad, Carla P. Gomes, Willem-Jan van Hoeve, Ashish Sabharwal, Jordan F. Suter, JEEM: Journal of Environmental Economics and Management. Volume 63, Issue 1, January 2012


[Biodiversity|Optimization] A new method to solve the fully connected Reserve Network Design Problem. Nahid Jafari, John Hearne, European Journal of Operational Research, Volume 231, Issue 1, 16 November 2013, Pages 202-209, ISSN 0377-2217,


[Biodiversity|Optimization| Optimization] Robust Network Design for Multispecies Conservation. Ronan Le Bras, Bistra Dilkina, Yexiang Xue, Carla P. Gomes, Kevin S. McKelvey, Claire Montgomery and Michael K. Schwartz.  AAAI-13: AAAI Conference on Artificial Intelligence, 2013


[Biodiversity|SAA] Maximizing Spread of Cascades Using Network Design.  Daniel Sheldon, Bistra Dilkina, Adam Elmachtoub, Ryan Finseth, Ashish Sabharwal, Jon Conrad, Carla Gomes, David Shmoys, Will Allen, Ole Amundsen, William Vaughan.  UAI: Conference on Uncertainty in Artificial Intelligence, 2010. PDF


[Biodiversity|SAA] Stochastic Network Design for River Networks. X. Wu, D. Sheldon, and S. Zilberstein. NIPS Workshop on Machine Learning for Sustainability, 2013. 


[Biodiversity|POMDP] MOMDPs: a solution for modeling adaptive management problems. Chadčs I, Carwardine J, Martin TG, Nicol S, Sabbadin R, Buffet O. 2012. AAAI Conference on Artificial Intelligence (AAAI-12). Won the AAAI Computational sustainability best paper award.






Planetary boundaries: exploring the safe operating space for humanityRockström, J. et. al. 2009. Ecology and Society 14(2): 32. URL:

Computational Sustainability: Computational Methods for a Sustainable Environment, Economy, and Society.  Carla Gomes.  The Bridge, National Academy of Engineering, Volume 39, Number 4, Winter 2009. PDF

Machine Learning for Computational Sustainability. Dietterich, T. G., Dereszynski, E., Hutchinson, R. A., Sheldon, D. (2012). International Conference on Green Computing (IGCC-2012). PDF



Other Topics


[Urban Growth] "Spatial optimization as a generative technique for sustainable multiobjective land‐use allocation." Ligmann‐Zielinska, Arika, Richard L. Church, and Piotr Jankowski. International Journal of Geographical Information Science 22.6 (2008): 601-622.


[Climate | Clustering] Discovery of climate indices using clustering. Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Steven Klooster, and Christopher Potter. KDD: ACM SIGKDD international conference on Knowledge discovery and data mining, pages 446–455, 2003.


[Climate] “Global Climate Model Tracking using Geospatial Neighborhoods,” S. McQuade and C. Monteleoni,  AAAI Conference on Artificial Intelligence, Computational Sustainability and AI Special Track, 2012.


[Climate|Networks]  Multivariate and Multiscale Dependence in the Global Climate System Revealed Through Complex Networks. K. Steinhaeuser, A. R. Ganguly and Nitesh V. Chawla (2012) Climate Dynamics, 39, 889-895.


[Climate|Clustering | Network Science] Spatio-temporal network analysis for studying climate patterns. I. Fountalis, A.Bracco, C. Dovrolis . Climate Dynamics journal, Springer, 2013.



[Environment|Clustering] “Representativeness-based Sampling Network Design for the State of Alaska.” Hoffman, Forrest M., Jitendra Kumar, Richard T. Mills, and William W. Hargrove. 2013. Landscape Ecology, 28(8):1567–1586.


[Environment, Land Cover|PCA,HPC] Identification and Visualization of Dominant Patterns and Anomalies in Remotely Sensed Vegetation Phenology Using a Parallel Tool for Principal Components Analysis.” Mills, Richard Tran, Jitendra Kumar, Forrest M. Hoffman, William W. Hargrove, Joseph P. Spruce, and Steven P. Norman. 2013.  Procedia Comput. Sci., 18(0):2396–2405. doi:10.1016/j.procs.2013.05.411


[Environment, Land Cover|HMM] Change Detection from Temporal Sequences of Class Labels: Application to Land Cover Change Mapping . V. Mithal, A. Khandelwal, S. Boriah, K. Steinhaeuser, and V. Kumar. In SDM: SIAM International Conference on Data Mining, pages 650--658, 2013.


[Environment, Water | Submodular Maximization] Cost-effective Outbreak Detection in Networks by J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, N. Glance. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2007.



[Building Design] "A Multi-objective Approach to Balance Buildings Construction Cost and Energy Efficiency."Fialho, Álvaro, Youssef Hamadi, and Marc Schoenauer.  ECAI. 2012.


[Building energy] A Large-Scale Study on Predicting and Contextualizing Building Energy Usage. J. Zico Kolter, Joseph Ferreira.  AAAI 2011


[Building] "The value of design strategies applied to energy efficiency", Caroline M. Clevenger, John R. Haymaker (2012)  Smart and Sustainable Built Environment, Vol. 1 Iss: 3, pp.222 - 240


[Building Design] Opportunities for AI to improve sustainable building design processesHaymaker, J. 2011. AAAI Spring Symposium on Artificial Intelligence and Sustainable Design.


[Building Design] A review of computational optimisation methods applied to sustainable building design, Ralph Evins, Renewable and Sustainable Energy Reviews, Volume 22, June 2013, Pages 230-245, ISSN 1364-0321,



[Energy disaggregation] Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation. J. Zico KolterTommi Jaakkola. AISTATS 2012: 1472-1482


[Energy disaggregation] Non-intrusive load monitoring using prior models of general appliance types. Parson, Oliver, Ghosh, Siddhartha, Weal, Mark and Rogers, Alex. AAAI 2012.


[Energy]Placement of Wind Turbines Using Genetic Algorithms



 [Transportation] "Balancing bicycle sharing systems: A variable neighborhood search approach." Rainer-Harbach, Marian, et al. Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2013. 121-132.


[Transportation] Walk Route: A new methodology to find the optimal walking route in the city of Atlanta. Guhathakurta, S., Zhang, G., Pangaluru, M., & Sivakumar R. (2013)  In Chapter 18: Planning Support Systems for Sustainable Urban Development (edited by S. Geertman). Heidelberg: Springer.




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