Research Groups

Focusing on the development of a comprehensive understanding of the exchange rates of mass (e.g. water, CO2, pollutants), energy, and momentum between the land and atmosphere. Primary applications  in hydrometeorology and air quality, particularly focused on the fusion of measurements and models for optimal prediction.

Daziano Research Group combines technical contributions in the search for more flexible choice models for engineering decision making – such as the derivation and analysis of estimators of advanced statistical models with less stringent assumptions over taste shocks – with empirical applications that necessitate a more flexible approach for providing more accurate predictions. The goal is to better understand the interplay of consumer behavior with engineering, investment, and policy choices for energy-efficient technologies.

The primary objective is to investigate, using numerical simulations, the physics of the interplay between turbulence and internal gravity waves in both mid-water and near the bottom/top and lateral boundaries of the ocean and lakes.

Earls Group focuses primarily on developing novel mathematical and computational approaches that enable deep understanding of natural and engineered systems. Practical challenges involving the principled treatment of uncertainty, sparse sensing, and intrinsic complexity are motivational to our work.

Advancing Fundamental Science and Transformative Technologies at the Climate-Environment-Energy Nexus for a Sustainable Energy and Resource Recovery Future. Developing cross-scale science to connect molecular- and meso-scale studies for pore-to-field and process-scale applications to advance sustainable energy and environmental technologies.

CIS Lab works on the interaction between critical
infrastructures and the natural environment. Members characterize climate risk on interconnected infrastructure systems and provide adaptive, robust, and scalable management solutions that balance reliability, resilience, and sustainability. Combining and leveraging elements of process-based modeling, climatology, statistical learning, control theory, and optimization.

Dr. Gao’s research focuses on transportation systems, environment (especially air quality and climate change), energy, and sustainable development. He also studies sustainable food systems, quantifying and mitigating green-house gas emissions from food supply chains.

We seek to understand how ecological and evolutionary processes play out in spatially extended populations. We use quantitative models inspired by statistical and nonlinear physics, experiments with microbial populations, and genetic engineering to investigate the spatiotemporal dynamics of biological invasions, how biological interactions such as cooperation, conflict and competition for resources affect ecological dynamics, and how adaptive evolution transforms these processes.

Gu Environmental Biotechnology Laboratory focuses on environmental biotechnology for water health, resources recovery, sustainable phosphorus, and development of AI-powered multi-omics tools.

Our research focuses on the inextricable link between human social mobility and technological development and the quality of freshwater resources. We are particularly interested in the occurrence and fate of organic chemicals in natural and engineered water systems. The emerging paradigm of sustainable human development recognizes that the distribution of novel chemical entities in the environment is a significant threat to global health and productivity.

Our research lab studies the exchange of momentum, energy, and mass between the Earth’s surfaces and the lower atmosphere. These exchanges are crucial parts of improving our predictive understanding of the Earth system under climate change. Our overarching research goal is to better understand the mechanisms and processes of flows and transfer of various scalars in the atmospheric boundary layer, as well as how land-atmosphere interactions affect the hydrologic cycle.

The overarching goal of the Information and Decision Science Lab is to develop data-driven system approaches at the intersection of learning and control to make large-scale, complex cyber-physical systems with nonclassical information structures able to realize how to improve their performance over time while interacting with their environment. The emphasis is on applications related to emerging mobility systems, sociotechnical systems, social media, and smart cities.

Our research draws on tools from operations research to inform the design of markets and financial systems able to support an efficient transition to clean resources.

Our research uses the analysis of ground motions and deformations in order to study the mechanics of earthquakes and other processes such as friction, impact, fracture, and damage processes.

The main focus of Dr. Nair’s group is to develop novel cementitious materials and testing techniques. The vision for the lab is to probe properties from the micro to the macro scale to accelerate the use of sustainable cementitious materials.

The Reed Research Group’s primary research interests relate to sustainable water management given conflicting demands from renewable energy systems, ecosystem services, expanding populations, and climate change.

Our laboratory is focused on investigating the applications of environmental biogeochemistry and ecosystem engineering to water quality problems.  Our group seeks to understand and innovate the use of nature-based technologies as sustainable tools to ensure the quality of water resources for societal needs and ecosystem health.

The Richardson group studies microbial communities of relevance to important environmental engineering problems. Application areas include bioremediation, bioenergy, sustainable wastewater treatment, nutrient and greenhouse gas cycling, and pathogen detection.

The Cornell Fracture Group conducts both scientific and engineering research aimed at understanding and predicting the deformation and failure of structures. A primary scientific goal of the group is to illuminate and model the underlying physical mechanisms that control the failure of structural materials.