Stefan Wild directs the Applied Mathematics and Computational Research (AMCR) Division in the Computing Sciences Area at Lawrence Berkeley National Laboratory (Berkeley Lab). AMCR conducts research and development in mathematical modeling, simulation and analysis, algorithm design, computer system architecture, and high-performance software implementation.
Wild’s primary research focuses on developing model-based algorithms and software for challenging numerical optimization problems and automated learning. He has worked across scientific areas to solve difficult science and engineering problems involving advanced computer simulations, complex data, and physical experiments.
At Northwestern University, Wild is an adjunct faculty member in Industrial Engineering and Management Sciences and a senior fellow in NAISE.
Wild came to Berkeley Lab in December of 2022 from Argonne National Laboratory where he was a senior computational mathematician and deputy division director of the Mathematics and Computer Science Division. He received his Ph.D. and M.S. in operations research from Cornell University and was then an Argonne Director’s Postdoctoral Fellow. Wild was also a Department of Energy Computational Science Graduate fellow.
Wild holds editorial responsibilities for Mathematical Programming Computation, INFORMS Journal on Computing, Data Science in Science, and the SIAM Review.
Publications and Software
Raghu Bollapragada, Stefan M. Wild, "Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization", Mathematical Programming Computation, 2023, 15:327--364, doi: 10.1007/s12532-023-00233-9
V. Cirigliano, Z. Davoudi, J. Engel, R. J. Furnstahl, G. Hagen, U. Heinz, H. Hergert, M. Horoi, C. W. Johnson, A. Lovato, E. Mereghetti, W. Nazarewicz, A. Nicholson, T. Papenbrock, S. Pastore, M. Plumlee, D. R. Phillips, P. E. Shanahan, S. R. Stroberg, F. Viens, A. Walker-Loud, K. A. Wendt, S. M. Wild, "Towards Precise and Accurate Calculations of Neutrinoless Double-Beta Decay", Journal of Physics G: Nuclear and Particle Physics, 2022, 49:120502, doi: 10.1088/1361-6471/aca03e
Ozge Surer, Filomena M. Nunes, Matthew Plumlee, Stefan M. Wild, "Uncertainty Quantification in Breakup Reactions", Physical Review C, 2022, 106:024607, doi: 10.1103/PhysRevC.106.024607
Aleksandra Ciprijanovic, Diana Kafkes, Gregory Snyder, F. Javier Sanchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild, "DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification", Machine Learning: Science and Technology, 2022, 3:035007, doi: 10.1088/2632-2153/ac7f1a
Stephen Hudson, Jeffrey Larson, John-Luke Navarro, Stefan M. Wild, "libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations", IEEE Transactions on Parallel and Distributed Systems, 2022, 33:977--988, doi: 10.1109/TPDS.2021.3082815
Jed Brown, Yunhui He, Scott MacLachlan, Matt Menickelly, Stefan M. Wild, "Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis", SIAM Journal on Scientific Computing, 2021, A109--A138, doi: 10.1137/19m1308669
Matt Menickelly, Stefan M. Wild, "Derivative-Free Robust Optimization by Outer Approximations", Mathematical Programming, 2020, 179:157--193, doi: 10.1007/s10107-018-1326-9
Anthony Austin, Zichao Wendy Di, Sven Leyffer, Stefan M. Wild, "Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach", SIAM Journal on Scientific Computing, 2019, 41:B497--B521, doi: 10.1137/18M121993X
Zichao Wendy Di, Sven Leyffer, Stefan M. Wild, "Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion", SIAM Journal on Imaging Sciences, 2016, 9:1--23, doi: 10.1137/15M1021404
Dave Higdon, Jordan D. McDonnell, Nicolas Schunck, Jason Sarich, Stefan M. Wild, "A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model", Journal of Physics G: Nuclear and Particle Physics, 2015, 42:034009, doi: 10.1088/0954-3899/42/3/034009
Stefan M. Wild, Christine A. Shoemaker, "Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms", SIAM Journal on Optimization, 2011, 761--781, doi: 10.1137/09074927X
Jorge J. More, Stefan M. Wild, "Benchmarking Derivative-Free Optimization Algorithms", SIAM Journal on Optimization, 2009, 20:172--191, doi: 10.1137/080724083
Stefan M. Wild, Rommel G. Regis, Christine A. Shoemaker, "ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions", SIAM Journal on Scientific Computing, 2008, 30:3197--3219, doi: 10.1137/070691814
Nikolay Bliznyuk, David Ruppert, Christine A. Shoemaker, Rommel G. Regis, Stefan M. Wild, Pradeep Mugunthan, "Bayesian Calibration of Computationally Expensive Models Using Optimization and Radial Basis Function Approximation", Journal of Computational and Graphical Statistics, 2008, 17:270--294, doi: 10.1198/106186008X320681
Stefan M. Wild, James H. Curry, Anne Dougherty, "Improving Non-Negative Matrix Factorizations Through Structured Initialization", Pattern Recognition, 2004, 37:2217--2232, doi: 10.1016/j.patcog.2004.02.013
Prasanna Balaprakash, Michael Salim, Thomas D. Uram, Venkat Vishwanath, Stefan M. Wild, "DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks", 25th IEEE International Conference on High Performance Computing (HiPC18), 2018, doi: 10.1109/hipc.2018.00014
E. Wes Bethel, Martin Greenwald, Kerstin Kleese Dam, Manish Parashar, Stefan M. Wild, H. Steven Wiley, "2016 IEEE 12th International Conference on e-Science", 2016 IEEE 12th International Conference on e-Science, Baltimore, MD, USA, 2016, 213--222,
Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sebastien Le Digabel, "Bayesian Optimization under Mixed Constraints with a Slack-Variable Augmented Lagrangian", Advances in Neural Information Processing Systems (NeurIPS), 2016, 29:1435--1443,
Babak Behzad, Suren Byna, Stefan Wild, Prabhat and Marc Snir, "Dynamic Model-driven Parallel I/O Performance Tuning", IEEE Cluster 2015, 2015,
Babak Behzad, Surendra Byna, Stefan M. Wild, Mr. Prabhat, Marc Snir, "Improving Parallel I/O Autotuning with Performance Modeling", ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC 2014), New York, NY, USA, ACM, 2014, 253--256, doi: 10.1145/2600212.2600708
E. G. Ng, J. Sarich, S. M.Wild, T. Munson, H. M. Aktulga, C. Yang, P. Maris, J. P. Vary, N. Schunck, M. G. Bertolli, M. Kortelainen, W. Nazarewicz, T. Papenbrock, M. V. Stoitsov, "Advancing Nuclear Physics Through TOPS Solvers and Tools", SciDAC 2011 Conference, Denver, CO, July 10, 2011, arXiv:1110.1708,
Stefan M. Wild, James H. Curry, Anne Dougherty, "Proceedings of the Eighth SIAM Conference on Applied Linear Algebra", Proceedings of the Eighth SIAM Conference on Applied Linear Algebra, 1969,
Tim Carnes, Chandrashekhar Nagarajan, Stefan M. Wild, Anke Zuylen, "ICEC '07: Proceedings of the Ninth International Conference on Electronic Commerce", ICEC '07: Proceedings of the Ninth International Conference on Electronic Commerce, 1969, 351--360,
V. Cirigliano, Z. Davoudi, J. Engel, R. J. Furnstahl, G. Hagen, U. Heinz, H. Hergert, M. Horoi, C. W. Johnson, A. Lovato, E. Mereghetti, W. Nazarewicz, A. Nicholson, T. Papenbrock, S. Pastore, M. Plumlee, D. R. Phillips, P. E. Shanahan, S. R. Stroberg, F. Viens, A. Walker-Loud, K. A. Wendt, S. M. Wild, "Towards Precise and Accurate Calculations of Neutrinoless Double-Beta Decay: Project Scoping Workshop Report", 2022, doi: 10.48550/ARXIV.2207.01085
Esmond Ng, Katherine J. Evans, Peter Caldwell, Forrest M. Hoffman, Charles Jackson, Kerstin Van Dam, Ruby Leung, Daniel F. Martin, George Ostrouchov, Raymond Tuminaro, Paul Ullrich, Stefan Wild, Samuel Williams, "Advances in Cross-Cutting Ideas for Computational Climate Science (AXICCS)", January 2017, doi: 10.2172/1341564
- Download File: AXICCS-Report.pdf (pdf: 4 MB)