Muhammad Rizwan Saeed

Muhammad Rizwan Saeed
University of Southern California | USC · Department of Electrical Engineering

About

11
Publications
961
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43
Citations
Citations since 2016
6 Research Items
40 Citations
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201620172018201920202021202202468
201620172018201920202021202202468
201620172018201920202021202202468

Publications

Publications (11)
Article
Full-text available
Knowledge Graphs (KGs) are becoming essential to information systems that require access to structured data. Several approaches have been recently proposed, for obtaining vector representations of KGs suitable for Machine Learning tasks, based on identifying and extracting relevant graph substructures using uniform and biased random walks. However,...
Conference Paper
In smart oilfields, a large volume of data is being generated related to assets, personnel, environment, and other production and business-related processes on a daily basis. Storing vast amounts of data is only justifiable if it leads to the discovery of actionable insights which can then be translated into improvements in operational efficiency a...
Chapter
Enormous amount of data from physical objects, such as devices comprising Internet of Things (IoT), is being made available through Web APIs on a daily basis. Manual discovery and integration of relevant data sources can be cumbersome. A unified view of relevant data sources is desirable for creating applications for monitoring and decision making....
Article
The combination of data, semantics, and the Web has led to an ever growing and increasingly complex body of semantic data. Accessing such structured data requires learning formal query languages, such as SPARQL, which poses significant difficulties for non-expert users. To date, many interfaces for querying Ontologies have been developed. However,...
Conference Paper
Full-text available
Accurate estimation and evaluation of consumption reduction achieved by participants during Demand Response is critical to Smart Grids. We perform an in-depth study of popular estimation methods used to determine the extent of consumption shedding during DR, using a real-world Smart Grid dataset from the University of Southern California campus mic...
Conference Paper
Full-text available
Demand response (DR) is a technique used in smart grids to shape customer load during peak hours. Automated DR offers utilities a fine grained control and a high degree of confidence in the outcome. However the impact on the customer's comfort means this technique is more suited for industrial and commercial settings than for residential homes. In...
Conference Paper
Full-text available
Growing demand is straining our existing electricity generation facilities and requires active participation of the utility and the consumers to achieve energy sustainability. One of the most effective and widely used ways to achieve this goal in the smart grid is demand response (DR), whereby consumers reduce their electricity consumption in respo...
Conference Paper
The Oil & Gas industry always seeks to prevent loss of containment (LOC). To prevent such incidents, engineers rely on inputs from various asset databases and software tools to make important safety-related assessments and decisions on a daily basis. One cause of LOC in offshore platforms is external corrosion. The state of corroding assets is exte...
Conference Paper
Full-text available
Regulating the power consumption to avoid peaks in demand is a known method. Demand Response is used as tool by utility providers to minimize costs and avoid network overload during peaks in demand. Although it has been used extensively there is a shortage of solutions dealing with real-time scheduling of DR events. Past attempts focus on minimizin...

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Projects (2)