ORC IAP Seminar 2022

1/25/22 | 10:00am-4:00pm | Online

Sustainability and Climate Change

Description: Operations Research is a powerful area for applications involving energy process design, waste minimization, climate change mitigation, scarce resources management, and other problems related to creating more sustainable and environmentally responsible operations. In this seminar, we will engage with a wide range of researchers and practitioners tackling these and other topics via data science, optimization, and other contemporary OR methods.

Date: Tuesday, January 25th

Place: Online (via Zoom) https://mit.zoom.us/j/97136654081

 

Schedule 

Talk 1 – 10:00am-11:00am

Andy Sun

Iberdrola-Avangrid Professor in Electric Power Systems and Associate Professor in Operations Research and Statistics, MIT

Title
Electric Power System Operations and Planning in Transition to a Net-Zero Emissions System

Abstract

To combat global warming, the electric power system must go through a rapid and complete decarbonization to reach a net-zero emissions system by mid-century. In this talk, we will present recent research progress on the decarbonization of electric energy systems and discuss their impacts on industry practices. We will also share his vision in creating a more collaborative future for electric energy systems. In particular, we will present new decision-making frameworks for overcoming three key challenges in the future power grids: 1) deep renewable penetration, 2) distributed generation, and 3) the increasing risk of grid infrastructure failure. Then, we will discuss the implementations of these new decision tools in the power industry. Finally, we will briefly discuss some on-going research in multi-energy systems, such as gas-electricity coordination and electric transportation. 

 

Bio
Andy Sun is Associate Professor in Operations Research and Statistics in the Sloan School of Management and holds the inaugural Iberdrola-Avangrid Professorship in Electric Power Systems. Dr. Sun is interested in building new bridges between the theory of optimization under uncertainty, distributed optimization, convexification of nonconvex structures, and control of dynamical systems, and in developing fundamental understanding and new analytical tools for renewable energy integration, power grid optimization, and stability and resiliency of interconnected energy systems and transportation systems. Before joining MIT, Dr. Sun is an associate professor in the H. Milton Stewart School of Industrial and Systems Engineering in Georgia Tech. He obtained his PhD degree in Operations Research from MIT. 

 

Talk 2 – 11:00am-12:00pm

Sara Beery 

PhD Candidate in Computing and Mathematical Sciences, Caltech

Title
Computer Vision for Global-Scale Biodiversity Monitoring

Abstract

Biodiversity is declining globally at unprecedented rates. We need to monitor species in real time and in greater detail to quickly understand which conservation efforts are most effective and take corrective action. Current ecological monitoring systems generate data far faster than researchers can analyze it, making scaling up impossible without automated data processing. However, ecological data collected in the field presents a number of challenges that current methods, like deep learning, are not designed to tackle. Biodiversity data is correlated in time and space, resulting in overfitting and poor generalization to new sensor deployments. Environmental monitoring sensors have limited intelligence, resulting in objects of interest that are often too close/far, blurry, or in clutter. Further, the distribution of species is long-tailed, which results in highly-imbalanced datasets. These challenges are not unique to the natural world, advances in any one of these areas will have far-reaching impact across domains. To address these challenges, we take inspiration from domain experts, and seek to incorporate structure from ecological domains into computer vision systems. Incorporating species distributions and temporal signal at inference time can improve generalization to new sensors, and deploying these models in accessible human-AI systems enables us to speed up and scale up ecological data processing while maintaining high accuracy.

 

Bio

Sara Beery is a final-year PhD Candidate in Computing and Mathematical Sciences at Caltech, advised by Pietro Perona. She has always loved the natural world and has seen a growing need for technology-based approaches to conservation and sustainability challenges. Her research focuses on building computer vision methods that enable efficient, accessible, and equitable global-scale biodiversity monitoring. She was honored to be awarded both the PIMCO Data Science Fellowship and the Amazon AI4Science Fellowship, which recognize senior graduate students that have had a remarkable impact in machine learning and data science, and in their application to fields beyond computer science. Her work is funded in part by an NSF Graduate Research Fellowship and the Caltech Resnick Sustainability Institute. She seeks to break down knowledge barriers between fields: she founded the successful AI for Conservation slack community (with over 650 members), and she is the founding director of the Caltech Summer School on Computer Vision Methods for Ecology. She works closely with Microsoft AI for Earth, Google Research, and Wildlife Insights where she helps turn her research into usable tools for the ecological community. Sara’s experiences as a professional ballerina, a nontraditional student, and a queer woman have taught her the value of unique and diverse perspectives, both inside and outside of the research community. She is passionate about increasing diversity and inclusion in STEM through mentorship, teaching, and outreach.
 

Talk 3 – 1:30-2:30pm

Y. Karen Zheng

George M. Bunker Professor and Associate Professor of Operations Management, MIT

Title
Improving Farmers’ Welfare via Digital Agricultural Platforms

Abstract

In order to improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched digital agricultural platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and more generally how they can be leveraged to enable more efficient agricultural supply chains and markets. In this talk, we describe a body of work that provides the first rigorous impact analysis of such a platform and highlights several important supply chain and logistics parameters that can inform its design and optimization. The work is focused on the Unified Market Platform (UMP) that connects all the agriculture markets in the state of Karnataka, India. Leveraging both public data and detailed bidding data from the platform, a difference-in-differences analysis demonstrates that the launch of the UMP has significantly increased the modal prices of certain commodities (2.6%-6.5%), while prices for other commodities have not changed. Furthermore, the analysis provides evidence that logistical challenges, bidding efficiency, market concentration, and price discovery processes are important factors explaining the variable impact of UMP on prices. These insights led to the design and field implementation of a new two-stage auction mechanism. The auction design aims to intensify anticipated regret of the traders to increase the farmers’ revenue. To ensure implementability and protect farmers’ revenue, the design process is guided by theory-informed, semi-structured interviews with a majority of the traders in the field and carefully accounts for operational constraints. The interviews suggest that both anticipated regret and anchoring would likely affect the traders’ bidding strategies in a two-stage auction. A new behavioral auction model is thus developed to capture these factors and determine when the two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By March 2020, commodities worth more than $19 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 3.6% price increase with an impact on farmer profitability ranging 55%–94%, affecting over 20,000 farmers who traded in the treatment market. This talk is based on joint work with Retsef Levi (MIT), Somya Singhvi (USC), Manoj Rajan (ReMS) and his team in Karnataka, India.

 

Bio

Y. Karen Zheng is the George M. Bunker Professor and an Associate Professor of Operations Management at the MIT Sloan School of Management. Karen’s research studies operations and supply chain management problems with a behavior-centric, data-driven, field-based approach. Her recent research examines the design and impact of digital platforms to enable efficient physical supply chains in resource constrained environments. Karen collaborates with both public and private partners on the ground to ensure that her research leads to positive impacts in practice. Karen’s research is recognized by various awards, including the NSF CAREER Award, the Management Science Best Paper Award in Operations Management, the MSOM Responsible Research Award, and the INFORMS Doing Good with Good OR Award. Karen received her bachelor’s and master’s degrees from Tsinghua University, and her PhD from Stanford University.

 

Talk 4 – 3:00-4:00pm

David Rolnik

Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science, McGill University

Title
Tackling Climate Change with Machine Learning

Abstract

Machine learning can be a powerful tool in helping society reduce greenhouse gas emissions and adapt to a changing climate. In this talk, we will explore opportunities and challenges in AI-for-climate, from optimizing electrical grids to monitoring crop yield, and how methodological innovations in machine learning can be driven by impactful climate-relevant problems.

 

Bio

David Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and at Mila Quebec AI Institute. He is a Co-founder and Chair of Climate Change AI and serves as Scientific Co-director of Sustainability in the Digital Age. Dr. Rolnick is a former NSF Mathematical Sciences Postdoctoral Research Fellow, NSF Graduate Research Fellow, and Fulbright Scholar, and was named to the MIT Technology Review’s 2021 list of “35 Innovators Under 35”. He received his Ph.D. in Applied Mathematics from MIT.

 

Panel – 4:00-5:00pm

Sustainability and Climate Change Panel

Please submit any questions you would be interested in seeing the panelists discuss during the Q&A portion of the panel via this Google Form.

 

Joann de Zegher

Maurice F. Strong Career Development Professor and Assistant Professor of Operations Management, MIT

Bio

Joann de Zegher is the Maurice F. Strong Career Development Professor and an Assistant Professor of Operations Management at the MIT Sloan School of Management. Her research examines the design of technologies and processes to address supply chain challenges in developing and emerging markets, by combining methods from large-scale field work, optimization, econometrics, and action research. Her work with smallholder supply chains in Indonesia has recently won the Tropical Forest Commodities Challenge organized by the World Economic Forum and was recognized as a top innovation by the World Bank. Joann has a PhD in Earth Systems Analysis and Operations Management from Stanford University.

 

David Rolnik

Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science, McGill University

Bio

David Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and at Mila Quebec AI Institute. He is a Co-founder and Chair of Climate Change AI and serves as Scientific Co-director of Sustainability in the Digital Age. Dr. Rolnick is a former NSF Mathematical Sciences Postdoctoral Research Fellow, NSF Graduate Research Fellow, and Fulbright Scholar, and was named to the MIT Technology Review’s 2021 list of “35 Innovators Under 35”. He received his Ph.D. in Applied Mathematics from MIT.

 

Andy Sun

Iberdrola-Avangrid Professor in Electric Power Systems and Associate Professor in Operations Research and Statistics, MIT

Bio
Andy Sun is Associate Professor in Operations Research and Statistics in the Sloan School of Management and holds the inaugural Iberdrola-Avangrid Professorship in Electric Power Systems. Dr. Sun is interested in building new bridges between the theory of optimization under uncertainty, distributed optimization, convexification of nonconvex structures, and control of dynamical systems, and in developing fundamental understanding and new analytical tools for renewable energy integration, power grid optimization, and stability and resiliency of interconnected energy systems and transportation systems. Before joining MIT, Dr. Sun is an associate professor in the H. Milton Stewart School of Industrial and Systems Engineering in Georgia Tech. He obtained his PhD degree in Operations Research from MIT. 

 

Y. Karen Zheng

George M. Bunker Professor and Associate Professor of Operations Management, MIT

Bio

Y. Karen Zheng is the George M. Bunker Professor and an Associate Professor of Operations Management at the MIT Sloan School of Management. Karen’s research studies operations and supply chain management problems with a behavior-centric, data-driven, field-based approach. Her recent research examines the design and impact of digital platforms to enable efficient physical supply chains in resource constrained environments. Karen collaborates with both public and private partners on the ground to ensure that her research leads to positive impacts in practice. Karen’s research is recognized by various awards, including the NSF CAREER Award, the Management Science Best Paper Award in Operations Management, the MSOM Responsible Research Award, and the INFORMS Doing Good with Good OR Award. Karen received her bachelor’s and master’s degrees from Tsinghua University, and her PhD from Stanford University.

 

If you have any questions, please contact us via email: orc_iapcoordinators@mit.edu.

 

Event Time:
2022 – 10:00