Dr Ludmilla Werbos holds a PhD degree in Computational Chemistry and a M. S. in Computer Science and Automated Control Systems. She worked as Research Associate, Physics Department, University of Maryland, Baltimore County on Modeling of photon entanglement (2002); was Visiting Professor of 1st class at CNRS (Engineering School of Lille University), France (1996-97) conducting research on IR spectra interpretation of various organic and inorganic materials; and was Deputy Director of the Laboratory of Computer-Aided Molecular Design, Russian Academy of Sciences (1994-1997)
As a Partner at Adaptive Logic Inc. (2006-2009), Dr. Werbos lead the effort to optimize the control and battery management system to provide longest possible battery life under residential and retail conditions. She represented the company at industry and regulatory meetings (EEI, NARUC, etc.) and worked with IEEE USA and US Senate to promote new approaches to standardization, price signal based control of energy flow, and establishment of learning centers.
IntControl LLC, with Dr. Werbos as a Principal Investigator was a partner in a MURI Program on the Science and Technology of Chemicals and Biological Sensing at Terahertz Frequencies (FY2001-2002). The objective of this research program is to discover and understand the fundamental physical principles governing the interaction of biological and chemical molecules with electromagnetic radiation in the terahertz region of the spectrum. In addition, a critical focus of this program is to develop the technology needed to study these interactions and to apply this technology to the design and realization of instrumentation for detecting and identifying biological and chemical) molecules, and their agents.
Presently, Dr. Werbos is an adjunct Professor at ECE Department of University of Memphis, TN, and a Partner at CLION (Center for Large-Scale Intelligent Optimization and Networks), FedEx Institute of Technology.
Dr. Paul Werbos is an elected member of the Governing Board of the International Neural Network Society (INNS), for which he was one of the original three two-year Presidents. He has also served as an elected member of the Administrative Committee (AdCom) of the IEEE Computational Intelligence Society (CIS), which he continues to represent on the IEEE-USA Energy Policy Committee. For IEEE-USA and as chair of the CIS Task Force on Alternative Energy, he has given a number of major talks to Congressional staff on energy policy, and helped to organize the IEEE-USA workshop on plug-in hybrid cars. He also serves on the AdCom of the IEEE Industrial Electronics Society. He is a Fellow of the IEEE, and has won its Neural Network Pioneer Award, for the discovery of the "backpropagation algorithm" and other basic neural network learning designs such as Adaptive Dynamic Programming. He also serves on the Planning Committee of the ACUNU Millennium Project (see www.stateofthefuture.org), whose annual report on the future tends to lead global lists of respected reports on the long-term future. In 2002, he and John Mankins of NASA initiated and ran the NASA-NSF-EPRI initiative on enabling technologies for space solar power (search on "JIETSSP" at www.nsf.gov). In 2003, he participated on the interagency working group for the Climate Change Technology Program. He has a paper in press at Futures on a rational strategy for the economic development of space, and has been nominated for the Governing Board of the National Space Society.
In addition to his core interests as Program Director at National Science Foundation (NSF), Dr. Werbos has interest in larger questions relating to consciousness, the foundations of physics, and human potential; search on "Werbos" at arxiv.org or go to his personal web page www.werbos.com for details. His 1974 Harvard Ph.D. thesis has been reprinted in its entirety, along with related papers, in his book The Roots of Backpropagation: From Ordered Derivatives to Neural Networks and Political Forecasting, Wiley, 1994. Some of work on high performance computing is described in P. Werbos, Backwards differentiation in AD and Neural Nets: Past Links and New Opportunities. In Martin Bucker, George Corliss, Paul Hovland, Uwe Naumann & Boyana Norris (eds), Automatic Differentiation: Applications, Theory and Implementations, Springer (LNCS), New York, 2005.
Prior to arriving full-time at NSF in 1989, Dr. Werbos worked since 1979 at the Energy Information Administration (EIA) of the Department of Energy. He initially worked in the evaluation of energy models, forecasts and analyses; this required spanning the gamut from decoding undocumented FORTRAN to evaluating the implications for the future of humanity. He later became lead analyst for long-term energy futures, and developed the econometric models used in EIA's Annual Energy Outlook for industrial and transportation energy demand and for oil and gas production. He served on Carters Global 2000 Phase II interagency task force. His model of industrial energy demand played a major role in the Stanford Energy Modeling Forum study of industrial demand, and resulted in several papers, including two in Energy: The International Journal, March/April 1990. Before that he spent a year as an IPA at the Census Use Research center as a mathematical statistician, and taught for 3 and a half years at the University of Maryland in the public policy area. Before teaching, he spent two years at the MIT Cambridge Project adding new capabilities for data mining and modeling to a user-oriented software package written in FORTRAN and PL/1 for the Multics operating system.
He holds four degrees from Harvard and the London School of Economics in: (1) economics; (2) international political systems, emphasizing European economic institutions; (3) applied mathematics, with a major in quantum physics and a minor in decision and control; (4) applied mathematics for an interdisciplinary PhD.