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Data science, artificial intelligence, information systems, and high-performance computing have significant potential to support a reliable, lowest-cost energy transition, sustainable development goals, climate resiliency, and climate, environmental, and energy equity. The Center for E3 seeks to apply these tools in solutions-oriented, policy-relevant research and scholarship in these critically important areas.

With Harrisburg University’s strengths and Ph.D. programs in data science, computer science, and information systems, engineering, and management, the Center is uniquely positioned to focus on interdisciplinary research that translates science into pragmatic, actionable policy solutions, business practice improvements, and the development of evidence-based decision support tools and systems.

Translating Science to Policy

Located at HU’s main campus in the center of Pennsylvania’s policy-making process, E3 acts as an important conduit for applying the latest scientific advances in the development of high-level policy and business practice solutions to energy, environmental, sustainability, equity, and climate resilience challenges.

Combining the depth of rigorous scientific research with the power of cutting-edge data analytics, information systems, artificial intelligence, and high-performance computing and the development of evidence-based decision support tools and systems, HU’s Center for E3 stands out in the crowded energy and sustainability space. It is difficult to translate valuable scientific insights into smart policy or business practice because regulators and businesses typically lack easy-to-use analytical tools to understand and implement the science. By focusing on this key science-policy ‘translation gap’ and a solutions-oriented approach, the Center for E3 is well positioned geographically and academically to fill this gap, and influence energy and environmental policy in Pennsylvania and beyond.

Center for E3 Initiatives

Farm Monitoring Technologies

The Center for E3 and Leena Pattarkine, Ph.D., Professor of Biotechnology are collaborating with TeamAg to develop and demonstrate low-cost tools for monitoring of water quality on farms in Pennsylvania to improve their economic and environmental performance.

Virtual Environmental Monitoring Network

The Center for E3 is focusing initially on building a proof-of concept network in partnerships involving water quality in the Susquehanna River.  Initial project activities include building the network prototype by accessing available data sets.

Environmental Research
Investigative Unit

Harrisburg University’s High Performance Computing Research Laboratory (HPCRL), under the direction of Majid Shaalan, Ph.D., Professor of Computer Science & Program Lead for the Computer Science Graduate Program, is collaborating with the Center for E3 to launch an Environmental Research Investigative Unit (ERIU).  ERIU will provide computational and cloud services to support the Center’s projects.

The collaboration will support undergraduate and graduate students in computational sciences and faculty who conduct environmental-related research.

Smart and Connected Communities Lab

This laboratory is led by Iheb Abdellatif, Ph.D., Assistant Professor of Information Technology & Management. The lab focuses on using computer-aided planning to develop customized, integrated local solutions for disaster management (including COVID), resilience for Small/Medium Businesses and Towns, and services underserved populations in the US. The research currently includes:

  • Developing a LEAN Smart Community Platform to reduce pollution, climate footprint, and impacts on public health. The platform will collect, process, and analyze satellite imagery using Artificial Intelligence and combine resulting data with additional data from other sources like city sensors, crowdsourcing, governmental databases, etc. in order to create methodologies, tools, and systems to identify and minimize waste sources (in electricity, transportation, water, etc.).
  • Developing applications to predict wildfires and prevent vehicle-animal collisions on highways.

Susquehanna River Basin Commission Partnership

Faculty and students from Information Systems Engineering and Management, Environmental Science and Sustainability, Data Science, and Computational Science are involved in a multidisciplinary collaboration with the Susquehanna River Basin Commission pursuing various research projects:

  • Using machine learning to identify key environmental indicators that influence water quality in the watershed, and to determine the effects of environmental indicators on the watershed’s biotic community.
  • Combine data mining, deep learning techniques, and data visualization techniques to identify relationships among various environmental parameters/indicators in a Predictive Analytics Dashboard
  • Develop data science tools to predict and manage Harmful Algal Blooms
  • Develop data science tools to identify, predict, and manage the impacts of climate change.
  • Update/modernize analytical tools that are used to respond to water pollution incidents and protect public health and drinking water quality.

Predicting spatial/temporal trends in COVID-19 using wastewater surveillance

Sewage systems across USA are being sampled to provide estimates of the total number of COVID cases on a city or regional basis. This testing can be expensive, and results based on proprietary methodology provide only gross estimate of cases.

The Center for E3 is collaborating with HU’s Analytics Institute and data science professors Kevin Purcell, Ph.D. and Alan Hitch, Ph.D., who seek to demonstrate the effectiveness of a combination of less expensive laboratory analysis and carefully planned, wider scale geographic testing at regular time intervals.

The resulting data would be used to model virus presence and estimate case counts within communities over time – at a much greater level of detail than currently available.

This more detailed modelling would allow government and public health officials to design more targeted, limited policy interventions e.g. lockdowns, enable better public health responses, and minimize the economic impact of the virus.

This work could provide a model for an effective statewide public health surveillance system.



A series of nine public lectures featuring thought leaders on a variety of topics related to energy, climate disruption, and sustainable development.


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