2018

  • INFORMS Annual Meeting 2018, Phoenix, AZ, November 2018.
    • “Effective Scenarios in Multistage Distributionally Robust Stochastic Programs with Total Variation Distance” [Gu¨zin Bayraksan]
    • “Learning Solutions to Optimal Power Flow: An Active Set Approach” [Line Roald]
    • “A Scalable Global Optimization Algorithm for Nonlinear Programs” [Victor Zavala]
    • “A Sigmoidal Approximation for Chance-Constrained Nonlinear Programs” [Victor Zavala]
  • International Symposium in Mathematical Programming, Bordeaux France, July 2018.
    • “Exponentially convergent receding horizon constrained optimal control” [Mihai Anitescu]
    • “Effective Scenarios in Multistage Distributionally Robust Stochastic Programs with Total Variation Distance” [Gu¨zin Bayraksan]
    • “Dynamic Risked Equilibria” [Michael Ferris]
    • “Branching Strategies on Decomposition Methods for Mixed-Integer Programming” [Kibaek Kim]
    • “Perspectives on Integer Programming for Sparse Optimization” [Jeff Linderoth]
    • “Lagrangian dual decision rules for multistage stochastic integer programs” [Jim Luedtke]
  • “New bilevel formulations for optimizing flux bounds in metabolic engineering” [Jim Luedtke]
  • Keynote “Scalable Stochastic Programming for Energy Systems”, 7th International Conference on High Performance Scientific Computing, Hanoi, Vietnam, April 2018. [Mihai Anitescu]
  • Keynote “Mathematical Challenges of Energy Mathematical Challenges of Energy Sys- tems; Long Horizon Dynamic Programming”, The 9th Annual Graduate Student Mini- Conference in Computational Mathematics, Columbia, SC, February 17-18, 2018. [Mihai Anitescu]
  • “Stochastic Simulation of Predictive Space-Time Scenarios of Wind Speed Using Observations and Physical Models”, IMA “Forecasting from Complexity” Workshop, Minneapolis April 2018. [Mihai Anitescu]
  • “Characteristic-based flux partitioning for atmospheric flows and a posteriori error estima- tion”, “Integrating the Integrators for Nonlinear Evolution Equations” Workshop, Banff, Canada, December 2018. [Emil Constantinescu]
  • “Optimization of Infrastructure Systems”, NAE Frontiers in Engineering, Boston, MA, September 2018. [Victor Zavala]
  • Identifying Effective Scenarios in Distributionally Robust Stochastic Programming,” Department of Management, Economics and Quantitative Methods, University of Bergamo, Italy, July 2018. [Gu¨zin Bayraksan]
  • “Effective Scenarios in Distributionally Robust Optimization with Total Variation Dis- tance,” INFORMS Optimization Society Meeting 2018, Denver, CO, March 2018. [Gu¨zin Bayraksan]
  • “Effective Scenarios in Distributionally Robust Optimization,” BIRS Workshop on Distributionally Robust Optimization, Banff, Alberta, Canada, March 2018. [Gu¨zin Bayrak- san]
  • “Keeping the Lights on”, Soundwaves lecture series, Wisconsin Institutes for Discovery, Madison, December 2018. [Michael Ferris]
  • “Modelling 100 percent renewable electricity”, Energy System and Optimization Work- shop, Georgia Tech, November 2018. [Michael Ferris]
  • “Solving Stochastic Equilibria: Emp, Selkie, and Optimal Value Functions”, Mathematisches Forschungsinstitut, Oberwolfach, Germany, August 2018; GAMS Corporation, Braunchweig, Germany, June 2018. [Michael Ferris]
  • “Modelling 100 percent renewable electricity”, Weierstrass Institute for Applied Analysis and Stochastics, Berlin, June 20, 2018; Technische Universitat, Munich, Germany, June 2018. [Michael Ferris]
  • “Optimization, equilibria, energy and risk”, Energy and Operations Research Work- shop, Operations Research Society of New Zealand Workshop, Wellington, March 2018. [Michael Ferris]
  • High Performance Analytics for Grid Reliability and Resilience”, Visit to Washington State University, Pullman, WA. October 2018. [Zhenyu Huang]
  • “Big Data Access Analytics and Sense-Making”, IEEE PES AMPS Big Data Subcommitee Webinar. October 2018. [Zhenyu Huang]
  • “High Performance Analytics for Grid Reliability and Resilience, Panel: Modeling and Simulation for Complex Power Systems”, POWERCON 2018. Guangzhou, China. November 2018. [Zhenyu Huang]
  • “Analytics and Analytical Platforms for Maximizing Grid Flexibility and Resiliency”, Visit to University of Tennessee at Chattanooga, Chattanooga, TN. March 2018. [Zhenyu Huang]
  • “MACSER at PNNL: Multifaceted Mathematics for Rare High Impact Events in Complex Energy and Environment Systems”, ASCR visit at PNNL, Richland, WA, April 2018. [Zhenyu Huang]
  • “An Asynchronous Dual Decomposition Algorithm for Security Constrained Unit Commitment under Contingency Events”, Power Systems Computation Conference 2018, Dublin, Ireland, June 2018. [Kibaek Kim]
  • “Asynchronous Dual Decomposition for Stochastic Mixed-Integer Programming”, SIAM Parallel Processing 2018, Tokyo, Japan. [Kibaek Kim]
  • Keynote “Mixed-Integer Nonlinear Optimization”, ISM-ZIB-IMI Workshop on Optimization an HPC, Tokyo, Japan, 2017. [Sven Leyffer]
  • Plenary “Industrial-Strength Optimization in the Department of Energy”, Industrial and Applied Mathematics Workshop 2017, Seoul, South Korea, 2017. [Sven Leyffer]
  • Lecturer ALOP Summer School on Mixed-Integer Nonlinear Programming, Germany, 2018. [Sven Leyffer, Jeff Linderoth]
  • Keynote “Perspectives on Integer Programming for Sparse Optimization”, Workshop on Optimization, Machine Learning, and Data Science, Braunschweig, Germany, 2018. [Jeff Linderoth]
  • “Solving Symmetric Integer Programs”, Workshop on Symmetry in Integer Linear Pro- gramming, Enumeration Algorithms and Design of Experiments, KU Leuven, Belgium, March 2018. [Jeff Linderoth]
  • “Perspectives on Integer Programming for Sparse Optimization”, University of Iowa, November 2018. [Jeff Linderoth]
  • “Perspectives on Integer Programming for Sparse Optimization”, University of Houston, November 2018. [Jeff Linderoth]
  • “Perspectives on Integer Programming for Sparse Optimization”, University of Tennessee, October 2018. [Jeff Linderoth]
  • “Perspectives on Integer Programming for Sparse Optimization”, Carnegie Mellon University, April 2018. [Jeff Linderoth]
  • “Lagrangian dual decision rules for multistage stochastic integer programs”, New Directions in Stochastic Optimization Workshop, Oberwolfach, Germany, August 2018. [Jim Luedtke]
  • “Combining progressive hedging with a Frank-Wolfe Method to compute Lagrangian dual bounds in stochastic mixed-integer programming”, DIMACS Workshop on ADMM and Proximal Splitting Methods in Optimization, Rutgers, June 2018. [Jim Luedtke]
  • “External intersection cuts”, Workshop on Designing and Implementing Algorithms for Mixed-Integer Nonlinear Optimization, Schloss Dagstuhl, Germany, February 2018. [Jim Luedtke]
  • “New approximate solution approaches for multi-stage stochastic optimization”, 22nd Aussois Combinatorial Optimization Workshop, Aussois, France, January 2018. [Jim Luedtke]
  • “Climate model emulation and future climate simulation”, Colorado State University, April 2018. [Michael Stein]
  • “Climate model emulation and future climate simulation”, Charles Edison Lecture at Notre Dame University, April 2018. [Michael Stein]
  • “Statistical Modeling of Environmental Time Series”, Rutgers University, Department of Environmental Sciences, October 2018. [Michael Stein]
  • “Statistical Modeling of Environmental Time Series”, Harvard University, Harvard Data Science Initiative, November 2018. [Michael Stein]
  • “Mesh refinement and coarse-graining for complex systems”, University of Chicago, Sci- entific and Statistical Computing Seminar. Chicago, IL. April 2018. [Panos Stinis]
  • “The effect of renewable energy generation on the power grid stability”, SSEC Symposium, 51nd Hawaii International Conference on System Sciences, HICSS 2018, Hawaii, USA, January 2018. [Alexandre Tartakovsky]
  • Data Science Leadership Summit, Columbia University, March 2018 [Steve Wright]
  • Plenary Symposium on Data, Modeling, and Optimization, Cornell Tech, NYC, April 2018. [Steve Wright]
  • Workshop on Optimization, Machine Learning, and Data Science, Technical University of Braunschweig, Germany, April 2018. [Steve Wright]
  • Princeton Workshop “Bridging Mathematical Optimization, Information Theory, and Data Science”, May, 2018. [Steve Wright]
  • University of Queensland, Australia, colloquium, June 2018. [Steve Wright]
  • Alan Turing Institute, London, colloquium, June 2018. [Steve Wright]
  • Plenary, Turing Lecturer 6th IMA Conference on Numerical Linear Algebra and Optimization, Birmingham, June 2018. [Steve Wright]
  • Lecturer Summer School on Mathematics of Data Science, lecturer, Harbin Institute of Technology, Harbin, August 2018. [Steve Wright]
  • Plenary DIMACS / TRIPODS / MOPTA Conference, Lehigh University, August 2018. [Steve Wright]
  • Plenary Conference on Nonlinear Model Predictive Control, Madison, August 2018. [Steve Wright]
  • Lecturer IWR School on Advances in Mathematical Optimization, Heidelberg, October 2018. [Steve Wright]
  • UC-Irvine, colloquium, October 2018. [Steve Wright]
  • Optimization Reunion Conference, Simons Institute, Berkeley, December 2018. [Steve Wright]
  • Plenary Vienna Workshop on Computational Optimization, December 2018. [Steve Wright]
  • American Institute of Chemical Engineers Annual Meeting, Pittsburgh, PA, November 2018.
  •  “A Mixed-Integer Conic Programming Formulation for Computing the Flexibility Index Under Multivariate Gaussian Random Variables” [Victor Zavala]
    •  “A Sigmoidal Approximation for Chance-Constrained Nonlinear Programs” [Victor Zavala]
    • “Design of Flare Systems Under Uncertainty: A Chance-Constrained Nonlinear Pro- gramming Approach” [Victor Zavala]
  •  “Approximate Bayesian model inversion for PDEs with unknown parameters and con- stitutive relations”, American Geophysical Union, Fall Meeting 2018, Washington DC, December 2018