• “Modeling Infinite-Dimensional Optimization Problems with InfiniteOptjl”, 2020 AICHE Annual Meeting (Virtual), November 2020. [Joshua Pulsipher]
  • “Large Deviation Theory for the Analysis of Power Tansmission Systems Subject to Stochastic Forcing”, 2020 INFORMS Annual Meeting (Virtual), November 2020. [David A. Barajas-Solano]
  • Cornell University SORIE, colloquium, November 2020. [Stephen Wright]
  • Theoretical and Applied Data Science Seminar, Iowa State, October 2020. [Stephen Wright]
  • Plenary speaker at Information Theory and Applications (ITA), 2020. [Rebecca Willett]
  • Keynote speaker at the International Traveling Workshop on Interactions between Low-Complexity Data Models and Sensing Techniques (iTWIST), 2020. [Rebecca Willett]
  • Plenary speaker at the 28th European Signal Processing Conference, 2020. [Rebecca Willett]
  • Plenary speaker at the International Symposium on Biomedical Imaging (ISBI), 2020. [Rebecca Willett]
  • Plenary speaker at the Foundations of Computational Mathematics (FoCM), 2020. [Rebecca Willett]
  • Plenary speaker at the 33rd Annual Conference on Learning Theory (COLT), 2020. [Rebecca Willett]
  • “Balancing Wildfire Risk and Power Outages Through Optimized Power Shut-Offs”, 2021 Grid Science Winter School, Los Alamos National Laboratory (Virtual), January 2020. [Line Roald]
  • “Managing Risk in Power System Operations: From Climate Chance Mitigation to Climate Change Adaptation”, Washington State University (Virtual), February 2020. [Line Roald]
  • “Balancing Wildfire Risk and Power System Reliability: Pre-emptive power shut-offs and proactive restoration planning”, Washington State University (Virtual), February 2020. [Line Roald]
  • “Preparing for the Extremes: Modeling and Mitigating Risk of Wildfire and Natural Gas Shortages”, PSERC Seminar (Virtual), April 2020. [Line Roald]
  • “Balancing Wildfire Risk and Power System Reliability: Pre-emptive power shut-offs and proactive restoration planning”, RASEI Terawatt to Nanowatt Seminar, CU Boulder (Virtual), April 2020. [Line Roald]
  • “An Uncertainty Management Framework for Integrated Gas-Electric Networks”, Department Seminar, Energy Resources Engineering, Stanford University (Virtual), May 2020. [Line Roald]
  • “How to Reduce the Risk of Wild re Ignitions from Power Grids?”, Wednesday Nite at the Lab, University of Wisconsin, Madison (Virtual), June 2020. [Line Roald]
  • “Modeling Infinite-Dimensional Optimization Problems with InfiniteOptjl”, University of Wisconsin, Madison (Virtual), 2020. [Joshua Pulsipher]
  • “On solving ACOPF and SCACOPF problems using nonlinear programming and high-performance computing”, 2020 Georgia Tech Workshop on Energy Systems and Optimization Workshop, December 2020. [Cosmin Petra]
  • “Data-driven sample-average approximation for stochastic optimization with covariate information”, University of Michigan, October 2020. [Jim Luedtke]
  • “Using mathematical optimization to manage uncertainty in the power grid”, Sustainable Energy Seminar, University of Wisconsin, Madison, November 2020. [Jim Luedtke]
  • “Detecting instabilities in spatio-temporal power grid data with Bayesian decision theory”, Southern Methodist University (Virtual seminar), October 2020. [Amanda Lenzi]
  • “Hospital Resource Use Forecasting”, Wisconsin Emergency Response Briefing, Madison, Wisconsin, December 2020. [Michael Ferris]
  • Statistics Department seminar, University of Wisconsin, Madison (Virtual), October 2020. [Julie Bessac]
  • Environmental Data Science Lunch seminar, University of Chicago (Virtual), November 2020. [Julie Bessac]
  • “Data-Driven Sample Average Approximation with Covariate Information”, Georgia Tech Energy Systems and OptimizationWorkshop (Virtual), December 2020. [Guzin Bayraksan]
  • “Werewolf and NetZero: the interactions between operations, planning, investments and policies,” Public Services Commission Strategic Energy Assessment Group, May 2020. [Michael Ferris]
  • INFORMS Annual Meeting 2020 (Virtual), November 2020.
    • “Multistage Distributionally Robust Optimization via Phi-Divergences with Application to Water Allocation Under Climate Uncertainty” [Guzin Bayraksan]
    • “Stochastic Equilibria: Data and Applications” [Michael Ferris]
    • “Dual Decomposition of Two-Stage DRMIP under the Wasserstein Ambiguity Set” [Kibaek Kim]
    • “Modeling Infinite-Dimensional Optimization Problems with InfiniteOptjl” [Joshua Pulsipher]
    • “Using Effective Scenarios to Accelerate Benders Decomposition for Two-stage Distributionally Robust Optimization With Total Variation Distance” [Chennan Zhou]
  • Computing in Engineering Forum, University of Wisconsin-Madison (Virtual Event), September 2020.
    • “Large Deviation Theory for the Analysis of Power Transmission Systems Subject to Stochastic Forcing” [David Barajas-Solano]
    • “Data-Driven Sample Average Approximation with Covariate Information” [Guzin Bayraksan]
    • “Stochastic optimization: Making complex design, planning, and operation decisions in the face of uncertainty” [Jim Luedtke]
  • IPAM Workshop on “Intersections between Control, Learning and Optimization”, UCLA, Los Angeles, California, February 2020.
    • “Nonconvex optimization in matrix optimization and distributionally robust optimization” [Stephen Wright]
    • “Predict, then smart optimize with stochastic programming” [R. Kannan]
    • “A Unifying Framework for Subspace Identification and Dynamic Mode Decomposition,” IPAM Workshop on “Intersections between Control, Learning and Optimization” [Sungho Shin]
  • Data Science in Engineering Conference, Madison, September 2020. [Mihai Anitescu]
  • “Rare event simulation of energy cascades using Kinetic Monte Carlo,” August 2020 IEEE PES CAMP webinar. [Mihai Anitescu]
  • “A Multistage Distributionally Robust Approach to Water Allocation under Climate Uncertainty,” Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA, January 2020. [Guzin Bayraksan]
  • “An Optimal Experimental Design framework for sensor placement and acquisition of highly-correlated data,” WCCM-ECCOMAS Congress, Paris, July 2020. Now in digital format, January 2021. [Ahmed Attia]
  • Keynote “Overview of Electricity Markets,” Regional Transmission Organization Fundamentals, Wisconsin Public Utilities Institute, May 2020. [Michael Ferris]
  • Keynote “Solving equilibrium problems using extended mathematical programming,” Dynamics, Optimization and Variational Analysis in Applied Games, Fields Institute, Toronto, May, 2020. [Michael Ferris]
  • “Werewolf and NetZero: the interactions between operations, planning, investments and policies,” Public Services Commission Strategic Energy Assessment Group, May 2020. [Michael Ferris]
  • “Planning Towards a 100 percent renewable electricity system,” ESIG Spring Technical Workshop, April 2020. [Michael Ferris]
  • “Integer Packing Sets are Well-Quasi Ordered,” 24rd Combinatorial Optimization Workshop, Aussois, France, January, 2020. [Je Linderoth]
  • “Data-driven sample-average approximation for stochastic optimization with covariate information,” University of Waterloo Tutte Colloquium, July 2020. [Jim Luedtke]
  • “Lagrangian dual decision rules for multi-stage stochastic optimization,” Los Alamos National Laboratory, February 2020. [Jim Luedtke]
  • “Data-driven stochastic optimization with covariate information,” Argonne National Laboratory, September 2020. [R. Kannan]
  • “Predict, then smart optimize with stochastic programming,” Los Alamos National Laboratory, July 2020. [R. Kannan] “
  • “gollnlp approach for Solving SC-ACOPF using nonlinear non-convex optimization and high-performance computing,” ARPA-E Grid Optimization Outreach Event, February 2020. [Cosmin G. Petra]
  • “Electric Grid Operations: From Climate Change Mitigation to Climate Change Adaptation,” Cornell Energy Seminar, October 2020. [Line A. Roald]
  • “Models for distributions when extremes are of interest.” UC Davis Department of Statistics, February 2020. [Michael Stein]
  • “Parametric Models for Distributions When Extremes Are of Interest.” Joint Statistical Meetings, August 2020. [Michael Stein]
  • “Parametric Models for Distributions When Extremes Are of Interest.” University of Illinois Urbana-Champaign Department of Statistics, special student-organized seminar. [Michael Stein]
  • “Domain-Aware Machine Learning Methods For Model Reduction,” HICSS 2020 : Hawaii International Conference on System Sciences, Hawaii, January, 2020. [Alexandre Tartakovsky]
  • “Physics-informed deep neural network (DNN) method for solving inverse problems and learning unknown physics,” Department of Mathematics and Statistics Seminar, Pullman, March, 2020. [Alexandre Tartakovsky]
  • “Implementation of Non-Steady-State Start of Dynamic Security Assessment,” IEEE PES GM 2020 Panel Session, IEEE PES PSDP PSSS Dynamic Security Assessment (DSA) Working Group, August, 2020. [Shaobu Wang]
  • Plenary speaker at the 33rd Annual Conference on Learning Theory (COLT), 2020. [Rebecca Willett]
  • Plenary speaker at the Foundations of Computational Mathematics (FoCM), 2020. [Rebecca Willett]
  • Plenary speaker at the International Symposium on Biomedical Imaging (ISBI), 2020. [Rebecca Willett]
  • Plenary speaker at the 28th European Signal Processing Conference, 2020. [Rebecca Willett]
  • Keynote speaker at the international Traveling Workshop on Interactions between lowcomplexity data models and Sensing Techniques (iTWIST), 2020. [Rebecca Willett]
  • Plenary speaker at Information Theory and Applications (ITA), 2020. [Rebecca Willett]
  • One-World Optimization Seminar, September, 2020. [Stephen Wright]
  • Theoretical and Applied Data Science Seminar, Iowa State, October, 2020. [Stephen Wright]
  • “Using Parallel Computing Insights to Design and Analyze Control Architectures,” Los Alamos National Laboratory, 2020. [Victor Zavala]
  • “Optimization of Energy Systems: Data, Modeling, and Decision-Making,” University of Washington, 2020. [Victor Zavala]
  • “Extremes of Dynamical Systems and Spatiotemporal Processes,” Conference on Data Analysis (CoDA), Santa Fe, NM, March 2020. [Charlotte Haley]
  • “Integrated Learning and Optimization,” Wisconsin Institute for Discovery Annual Symposium, Madison, Wisconsin, August 2020. [R. Kannan]