CS/INFO 6702 Topics in Computational Sustainability


Computer Science and Information Science

Spring 2010

Cornell University


Instructor: Carla Gomes


Faculty Team: Jon Conrad,  Steve Ellner, Carla Gomes, and  Mary Lou Zeeman


Teaching Assistants: Bistra Dilkina and Georgios Piliouras


Time: WF 1:25-2:40 pm.


Location:   1120 Snee Hall


Grade options and credits: Letter or S/U; 4 credits


Prerequisites: Graduate standing or permission of instructor


Web page: http://www.cs.cornell.edu/Courses/cs6702/2010sp/


Office hours:



By email or regular office hours:


Carla Gomes – Wednesday 3:15-4:30 PM (5133 Upson Hall)

Jon Conrad – Thursday 10:00-11:00 AM (455 Warren Hall)

Bistra Dilkina – Friday 3:00-4:00PM (5151 Upson Hall)

Georgios Piliouras – Wednesday 12:00-1:15 PM (4143 Upson Hall)




Computational Sustainability is an emerging  field  that aims to apply techniques from computer science and related disciplines (e.g., information science, operations research, applied mathematics, and statistics)   to help manage the balance of environmental, economic, and societal needs for sustainable development. The focus of Computational Sustainability is on developing computational and mathematical models, methods, and tools for a broad range of sustainability related applications: from decision making and policy analysis concerning the management and allocation of resources to the design of new sustainable techniques, practices and products.  The range of problems that fall under Computational Sustainability is therefore rather wide, encompassing computational challenges in disciplines as diverse as environmental sciences, economics, sociology, and biological and environmental engineering.

The scope and definition of Computational Sustainability are still fluid and in progress. The main goal of the course is to identify interesting computational research questions concerning sustainability problems and more generally we hope the course will provide additional insights towards the understanding of the boundaries and central methodologies in Computational Sustainability.

The course is meant to provide a high-level perspective on different topics. Computational and mathematical topics include constraint satisfaction and optimization problems, probabilistic reasoning and inference, machine learning methods, game theory, agent-based models, and dynamical models. The course will include examples of sustainability topics concerning:

·       Natural Resource Protection



·       Economics and Human Behavior



·       Energy Resources


o   Smart Grid and Electric Cars

o   Wind

o   Biofuels

o   Material Discovery


·       Human-Built Systems and Land Use


o   Agriculture

o   Sustainable Cities

o   Energy efficiency - Sustainable Management of Data Centers

o   Life cycle analysis



Given the multi-disciplinary nature of the material, the course will include several guest lecturers representing various disciplines.

Non-Cornell Guest Speakers (confirmed)


o   Ole Amundsen (The Conservation Fund)

o   Andreas Krause (Computer Science, Caltech)

o   Steve Phillips (Computer Science, ATT Labs)

o   Warren Powell (Operations Research, Princeton)

o   Brian Williams (Computer Science, MIT)

o   Mary Lou Zeeman (Bowdoin)


Cornell Guest Speakers (confirmed)


o   Antonio Bento, Jon Conrad, Tim Mount (Applied Economics)

o   Daniel Fink, Steve Kelling, Ken Rosenberg  (Lab of Ornithology)

o   Yrjo Grohn (Population Medicine and Diagnostic Sciences)

o   Laurie Drinkwater  (Horticulture)

o   Robert Howarth (Ecologicy and Environment Biology)


Course Work


The course work consists of three components:


1.    Attendance and participation in the lectures

2.    A reaction paper identifying one or two computational questions concerning sustainability problems, a presentation of a research problem in class, or a good annotated bibliography. (List of reaction papers.)

3.    A final project, including an initial project proposal. (List of projects.)

Students are encouraged to work in interdisciplinary groups.  

Course Schedule

The course will cover computational topics in constraint satisfaction and optimization problems, probabilistic reasoning and inference, machine learning methods, game theory, agent-based models, and dynamical models. The course will include examples of computational problems concerning the following sustainability topics: natural resource protection, economics and human behavior, human-built systems and land use, and energy.

Here is an approximate schedule. The schedule will be expanded and updated as we go along. A general list of suggested readings is provided below. Specific readings and notes for the lectures are added to the schedule as we go along.







Intro to Computational Sustainability


Computational Sustainability

Carla Gomes

The Bridge, National Academy of Engineering

Volume 39, Number 4 - Winter 2009




Computational Intro: Wildlife Corridor Design


Connections in networks: Hardness of feasibility versus optimality. Conrad, J., C. Gomes, W.-J. van Hoeve, A. Sabharwal, and J. Suter. Proc. CPAIOR 07, 2007 pages 16–28.


Connections in Networks: A Hybrid Approach  Carla Gomes, Willem van Hoeve and Ashish Sabharwal.  CPAIOR08., May 2008. PDF


Optimal Corridor Design for Grizzly Bear in the U.S. Northern Rockies, Jon Conrad, Carla P. Gomes,  Willem Jan Van Hoeve,  Ashish Sabharwal.





Intro to Resource Economics


Resource Economics. Conrad, J. 1999.

(selected pages)





4:30-5:30 PM,

233 Plant Science

Sustainable Economic Development


Nature’s Role in Sustaining Economic Development, Dasgupta, 2010


*Note different day, time, and location.



Computational Intro: Wildlife Corridor Design (continued)





Real-world conservation planning problems


Ole Amundsen, The Conservation Fund




Citizen Science/ Data Intensive Science


Lab. Of Ornithology


Kelling, S., W. M. Hochachka, D. Fink, M. Riedewald, R. Caruana, G. Ballard, and G. Hooker. 2009. Data Intensive Science: A New Paradigm for Biodiversity Studies. BioScience 59:613-620.





Intro to Dynamical Systems


Mary Lou Zeeman


Bowdoin College



Wind Energy and Bird Conservation:

Assessing risks and establishing guidelines for location and operation of turbines


Andrew Farnsworth and Ken Rosenberg

Slides1, Slides2


Infectious Diseases


Steve Ellner

Ecology and Evolutionary Biology




12:00 PM,

117 Upson Hall

Optimal Sensing from Water to the Web

Krause, A., and C. Guestrin.  2009.  Optimizing sensing from water to the Web.  IEEE Computer Magazine 42(8): 38–45.


*Note different time and location.


Rescheduled due to the weather ---- new date: Mar 19th.




Laurie Drinkwater

Department of Horticulture


Wackernagel, Schulz, Deumling, Callejas Linares, Jenkins, Kapos, Monfreda, Loh, Myers, Norgaard, and Randers, 2002. Tracking the ecological overshoot of the human economy. PNAS. 99 (14).


Robertson and Swinton. 2005. Reconciling agricultural productivity and environmental integrity: a grand challenge

for agriculture. Front Ecol Environ  3(1): 38–46




Opportunities for Machine Learning in Stochastic Optimization, with Applications in Energy Resource Planning


Warren Powell

Princeton University




Human acceleration of the nitrogen cycle at regional to global scales


Bob Howarth

Ecology & Environmental Biology


Howarth. 2008. Coastal nitrogen pollution: A review of sources and trends globally and regionally. Harmful Algae 8, 14–20


Townsend and Howarth. 2010. Fixing the Global Nitrogen Problem. Scientific American. February Issue.




Optimal Interventions in Animal Systems

Yrjo Grohn

Population Medicine and Diagnostic Sciences

College of Veterinary Medicine
Cornell University




Examining the effects of Biofuels Policies: Lifecycle analysis models versus Equilibrium Models

Antonio Bento

Applied Economics and Management

Cornell University








Optimal Sensing from Water to the Web

Krause, A., and C. Guestrin.  2009.  Optimizing sensing from water to the Web.  IEEE Computer Magazine 42(8): 38–45.


*Note different time and location.





Intro to Climate Models


Mary Lou Zeeman


Bowdoin College



Intro Climate Models


Natalie Mahowald

Earth and Atmospheric Sciences

Cornell University




Continuous Optimization with Response Surfaces for Computationally Expensive Simulation Models for  Environmental Applications

Chris Shoemaker

Earth and Atmospheric Sciences

Cornell University




12:00 PM,

5130 Upson Hall

Game-theory applied to conservation prioritization

Voting Power and Site Prioritization


Steve Phillips, ATT Labs


*Note different time and location.





Bob Thomas

Electrical and Computer Engineering

Cornell University





Max Zhang

Mechanical and Aerospace Engineering

Cornell University



Sustainable Building Systems: Challenges Ahead and New Directions

Brandon Hencey

Mechanical and Aerospace Engineering

Cornell University







Student Project Presentations






Suggested Readings


·       Background Info on the State of the Planet


·       Natural Resource Protection


·       Economics and Human Behavior


·       Energy Resources


·       Human-Built Systems and Land Use


·       Books