Paul Barton is the Lammot du Pont Professor of Chemical Engineering and Director of the Process Systems Engineering Laboratory at MIT, where he has been since 1992. He received his Ph.D. from the Centre for Process Systems Engineering at Imperial College, London University in 1992. He has held Visiting Professor appointments at CNRS-ENSIC, Nancy, France and EPFL, Lausanne, Switzerland. He has industrial experience with BP and Air Products, and has consulted for major corporations including Dow Chemical, Alstom Power and Aspen Technology. He has received a number of awards, including the Outstanding Young Researcher Award in 2004 and the Computing in Chemical Engineering Award in 2011, both from AIChE's CAST Division. Paul's research interests include hybrid discrete/continuous dynamic systems; numerical analysis of ordinary differential, differential-algebraic and partial differential-algebraic equations; sensitivity analysis and automatic differentiation; global, mixed-integer and dynamic optimization theory and algorithms; and open process modeling software. Some of the applications his group is currently focusing on include energy systems engineering, continuous pharmaceutical manufacturing, and quantitative engineering of microbial consortia. He served as Director for AIChE's CAST Division from 2001-2004 and is currently an associate editor for Journal of Global Optimization and Journal of Optimization Theory and Applications. He is author or co-author of over 150 articles in refereed journals. He has been very active in the design and the development of process modeling software, having been the original author of gPROMS, and having led the development of ABACUSS/JACOBIAN and DAEPACK at MIT, all of which are now commercial products widely used in industry.
Jacques du Toit studied Actuarial Science, Financial Mathematics and Statistics at the University of the Witwatersrand before completing a PhD in Probability Theory at the Univeristy of Manchester. Since 2010 he has been working at the Numerical Algorithms Group Ltd as part of their High Performance Computing Team, with a particular emphasis on GPU computing and computational finance. Jacques got involved in AD through collaborations with Prof Uwe Naumann's research group at RWTH Aachen. His work in this area involves helping to develop flexible and robust AD tools which can make efficient use of accelerators (GPU, Intel Xeon Phi).
Patrick received his BSc from the National University of Ireland in 2006, and his PhD from Imperial College London in 2010. In 2013 he was awarded an EPSRC Early Career Research Fellowship, and moved to the Mathematical Institute of the University of Oxford. In 2015 he was shortlisted for the IMA Leslie Fox prize in Numerical Analysis, and was awarded the Wilkinson prize for Numerical Software for the development of dolfin-adjoint.
Daniel Goldberg received his BSc in Chemical Engineering from the University of Pennsylvania, and attended the doctoral program in Atmosphere and Ocean Science and Mathematics in the Courant Institute of Mathematics at New York University. He received his PhD in 2009, with his dissertation focusing on the representation of grounding line migration and its impact on continental ice sheet stability through the use of adaptive meshing methods. He worked as a postdoctoral scientist for 2 years at the Geophysical Fluid Dynamics Laboratory (Princeton, NJ) and was an NSF postdoctoral fellow at MIT before beginning a Lectureship in Glaciology in the Unversity of Edinburgh School of GeoSciences. His foremost areas of interest are the dynamics of interaction between ocean circulation and ice sheet flow, and the quantification of uncertainty in ice sheet model simulation through adjoint-based methods.
Siegfried M. Rump was born in 1955 and studied Mathematics, Physics and Computer Science at the University of Kaiserslautern in Germany. His main area of interest was methods for Computer Algebra. He changed to the University of Karlsruhe were he finished his Ph.D. in 1980 and Doctor of Science in 1983 on so-called verification methods. A common theme with Computer Algebra is that all computed results are mathematically correct. While Computer Algebra is mostly based on exact arithmetic, verification methods intentionally use floating-point arithmetic to produce fast algorithms with provably bounded errors.
In 1983 Siegfried joined the IBM Research and Development center in Böblingen when the company became interested in his verification methods. Under his guidance his methods were incorporated into the IBM product ACRITH. In parallel, Siemens became also interested and produced ARITHMOS, also based on the methods published in Siegfried's thesis.
In 1987 Siegfried became head of the Institute of Reliable Computing at Hamburg University of Technology, his current position. He became interested in other fields, in particular in matrix theory. Since 1998 he has been developing INTLAB, the Matlab/Octave toolbox for reliable computing, currently distributed in version 9. INTLAB has several thousand users in more than 50 countries. Since 2002 he has a second position as visiting professor at Waseda University in Tokyo.
After having studied Mathematics and Economics at the University of Bayreuth from 1991 to 1996, Andrea Walther received her PhD from the Technical University of Dresden in 1999 and her Habilitation in mathematics at the same university in 2008. In 2009, Andrea was appointed Professor of Mathematics at the University of Paderborn.
Andrea's main research interests are the further development of Algorithmic Differentiation and methods for structure-exploiting nonlinear optimization including the nonsmooth case. She continues to be a programme committee member for many international conferences on Algorithmic Differentiation and optimization. Andrea has co-authored one book and co-edited one conference proceedings book on the subject of Algorithmic Differentiation. She has published more than 75 papers in peer-reviewed journals and conference proceedings which have received more than 3200 citations. She is one of three Representatives elected by the Working Group in Computational Science and Engineering of the German Association of Mathematics and Mechanics (GAMM).
This page was last updated by Shaun Forth on 2015-10-06