User:Janemacfarlane: Difference between revisions
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Jane Macfarlane is the Director of Smart Cities and Sustainable Mobility at the University of California at Berkeley and an affiliate scientist at Lawrence Berkeley National Laboratory. Dr. Macfarlane has over 30 years of experience in high performance computing, data analytics and geospatial mapping. For a large part of her career, she has been responsible for directing industry research. Including: Chief Scientist and Head of Research for HERE – a leader in geospatial mapping and Director of Advanced Technology Planning for OnStar at General Motors – the first at-scale, telematics solution in the US. Her research focus is on semantic analytics, big data analytics and visualization, contextualization of data streams and spatially distributed computing. Her thesis work focused on Dynamic Systems Understanding using an assumption-based truth maintenance system and symbolic analysis. She has authored over 26 patents, primarily in the domain of geospatial data analytics. She holds a Ph.D. in Mechanical Engineering from the University of Minnesota. Currently she is leading a DOE National Laboratory effort across three national labs focused on the use of High Performance Computing and big data in transportation systems. | Jane Macfarlane is the Director of Smart Cities and Sustainable Mobility at the University of California at Berkeley and an affiliate scientist at Lawrence Berkeley National Laboratory. Dr. Macfarlane has over 30 years of experience in high performance computing, data analytics and geospatial mapping. For a large part of her career, she has been responsible for directing industry research. Including: Chief Scientist and Head of Research for HERE – a leader in geospatial mapping and Director of Advanced Technology Planning for OnStar at General Motors – the first at-scale, telematics solution in the US. Her research focus is on semantic analytics, big data analytics and visualization, contextualization of data streams and spatially distributed computing. Her thesis work focused on Dynamic Systems Understanding using an assumption-based truth maintenance system and symbolic analysis. She has authored over 26 patents, primarily in the domain of geospatial data analytics. She holds a Ph.D. in Mechanical Engineering from the University of Minnesota. Currently she is leading a DOE National Laboratory effort across three national labs focused on the use of High Performance Computing and big data in transportation systems. | ||
Latest revision as of 18:55, March 11, 2022
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User Name | Janemacfarlane |
| Name | Jane Macfarlane | |
| Company | Lawrence Berkeley National Laboratory | |
| Company Position | Director of Smart Cities Research Center | |
| City, State | Berkeley CA | |
| Country | United States | |
| Sectors | Data | |
| Membership Level | Member |
- Activities
Jane Macfarlane is the Director of Smart Cities and Sustainable Mobility at the University of California at Berkeley and an affiliate scientist at Lawrence Berkeley National Laboratory. Dr. Macfarlane has over 30 years of experience in high performance computing, data analytics and geospatial mapping. For a large part of her career, she has been responsible for directing industry research. Including: Chief Scientist and Head of Research for HERE – a leader in geospatial mapping and Director of Advanced Technology Planning for OnStar at General Motors – the first at-scale, telematics solution in the US. Her research focus is on semantic analytics, big data analytics and visualization, contextualization of data streams and spatially distributed computing. Her thesis work focused on Dynamic Systems Understanding using an assumption-based truth maintenance system and symbolic analysis. She has authored over 26 patents, primarily in the domain of geospatial data analytics. She holds a Ph.D. in Mechanical Engineering from the University of Minnesota. Currently she is leading a DOE National Laboratory effort across three national labs focused on the use of High Performance Computing and big data in transportation systems.