PSE&G Demonstration Grant
With partners from the Department of Computer Science, the PSEG ISS received a $218,000 Demonstration Grant award to develop a Decision Support System (DSS) for improving energy usage at MSU’s Data Center. The overarching goal of the study is the creation of a DSS that supports business and organizational decision-making intended to streamline operations and save energy and operational costs. The DSS is an interactive software-based system intended to compile useful information from a combination of sources - raw data, documents, personal knowledge, or business models - to provide solutions to multi-faceted problems. Such systems extract data from a variety of sources such as energy measurements, application usage, network configurations, etc, and will use machine learning techniques to provide expected outcomes for various decisions that include application scheduling, hardware maintenance times, etc. A properly designed DSS can also assist in the decision making in the trade-offs on performance versus cost issues and contribute to sustainable operations of the data center.
The investigative team will also include Dr. Aparna Varde, an expert in data mining, database management and Artificial Intelligence who will supervise the graduate students on the project led by doctoral student Michael Pawlish. Dr. Weinstein is a project co-Principal Investigator and noted to the media that MSU’s “is leading the way in this important contribution to sustainable business practices in New Jersey”.
Hudson River Foundation Grant
Drs. Weinstein and Lohmann (University of Rhode Island), Co-Principal Investigators, have been awarded a $209,000 Hudson River Foundation Grant, The Availability and Bioaccumulation of Sedimentary 2,3,7,8-TCDD and Other Persistent Bioaccumulative Toxic Compounds in the Lower Passaic River. The main objectives of the proposed research are to better understand the availability, cycling and bioaccumulation of persistent organic pollutants, with a focus on 2,3,7,8-TCDD, in the lower Passaic River. Passive samplers will be deployed along the lower Passaic River to directly measure the freely dissolved pollutants in water, atmosphere and porewater. Various biota (blue crabs and fish) will also be sampled along a salinity gradient covering the lower Passaic River to determine bioaccumulation factors (BAFs) for PCBs, PCDD/Fs and emerging PBTs relative to dissolved concentrations in the water column. A trophodynamic and stable isotope approach will be adopted to predict concentrations in individual components of the food-web based on life history and feeding strategies.