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ORCIDHao Wang 0025
Person information
- affiliation: Sorbonne University, CNRS, LIP6, Paris, France
- affiliation: University of Leiden, Netherlands
Other persons with the same name
- Hao Wang — disambiguation page
- Hao Wang 0001 — Rockefeller University, New York City, NY, USA (and 2 more)
- Hao Wang 0002 — Virginia Tech, Blacksburg, VA, USA
- Hao Wang 0003
![[0000-0001-9301-5989]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-9301-5989")
— Norwegian University of Science and Technology, Alesund, Norway - Hao Wang 0004 — Hangzhou Dianzi University, School of Communication Engineering, China (and 1 more)
- Hao Wang 0005 — Qihoo 360 Inc., Beijing, China (and 2 more)
- Hao Wang 0006 — University of California, San Diego, CA. USA
- Hao Wang 0007 — Shandong University, Jinan, China
- Hao Wang 0008 — Hefei University of Technology, School of Computer Science and Information Engineering, MoE Key Laboratory of Knowledge Engineering with Big Data, China
- Hao Wang 0009 — Dalian Maritime University, Dalian, China
- Hao Wang 0010 — Google, Mountain View, CA, USA (and 1 more)
- Hao Wang 0011 — University of Wisconsin-Madison, Madison, WI, USA
- Hao Wang 0012 — China Institute of Water Resources and Hydropower Research, Beijing, China
- Hao Wang 0013 — Nanjing University, Nanjing, China
- Hao Wang 0014 — Rutgers University, Department of Computer Science, NJ, USA (and 2 more)
- Hao Wang 0015 — Shanghai Jiao Tong University, State Key Laboratory of Mechanical Systems and Vibration, Shanghai, China (and 1 more)
- Hao Wang 0016 — Stanford University, CA, USA (and 3 more)
- Hao Wang 0018 — North China University of Technology, School of Computer Science and Technology, Beijing, China (and 1 more)
- Hao Wang 0019 — Babytree Inc., Beijing, China (and 2 more)
- Hao Wang 0020 — Nokia Research Center, Beijing, China (and 1 more)
- Hao Wang 0021 — Helsinki University of Technology, Finland (and 2 more)
- Hao Wang 0022 — University of Toronto, Canada (and 1 more)
- Hao Wang 0023 — University of Kaiserslautern, Germany
- Hao Wang 0024 — Carnegie Mellon University, Pittsburgh, PA, USA
- Hao Wang 0026 — Michigan State University, East Lansing, MI, USA
- Hao Wang 0027 — University of Alberta, Edmonton, Canada
- Hao Wang 0028 — Tech Mahindra, Shanghai, China (and 1 more)
- Hao Wang 0029 — IBM Silicon Valley Lab, San Jose, CA, USA
- Hao Wang 0030 — CUHK, Department of Electronic Engineering, Hong Kong
- Hao Wang 0031 — University of Georgia, Athens, GA, USA (and 1 more)
- Hao Wang 0032 — University of Melbourne, Australia (and 1 more)
- Hao Wang 0033 — Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, China
- Hao Wang 0034 — Sichuan University, School of Computer Science, Chengdu, China
- Hao Wang 0035 — Peking University, Key Laboratory of High Confidence Software Technologies, Beijing, China
- Hao Wang 0036 — Shanghai University, Key Laboratory of Specialty Fiber Optics and Optical Access Network, China
- Hao Wang 0037 — Harbin Institute of Technology, Department of Computer Science, China
- Hao Wang 0038 — China Earthquake Administration, Key Laboratory of Earthquake Geodesy, Wuhan, China
- Hao Wang 0039 — Shanghai Jiao Tong University, Department of Electronic Engineering, Shanghai, China (and 1 more)
- Hao Wang 0040 — Southeast University, School of Civil Engineering, Nanjing, China
- Hao Wang 0041 — Tsinghua University, Department of Electrical Engineering, State Key Laboratory of Power Systems, Beijing, China
- Hao Wang 0042 — Rensselaer Polytechnic Institute, Department of Electrical, Computer and System Engineering, Troy, NY, USA
- Hao Wang 0043 — National University of Defense Technology, College of Electronic Science and Engineering, Changsha, China
- Hao Wang 0044 — University of California at Davis, Department of Electrical and Computer Engineering, CA, USA (and 1 more)
- Hao Wang 0045 — ShanghaiTech University, School of Information Science and Technology, China (and 1 more)
- Hao Wang 0046 — Wuhan University, School of Physics and Technology, China
- Hao Wang 0047 — Hohai University, Department of Internet of Things Engineering, Changzhou, China
- Hao Wang 0048 — National University of Singapore, Department of Mechanical Engineering, Singapore
- Hao Wang 0049 — Nanjing University, Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, China (and 1 more)
- Hao Wang 0050 — Tencent AI Lab, Beijing, China
- Hao Wang 0051 — Sichuan University, School of Mathematics, Chengdu, China (and 1 more)
- Hao Wang 0052 — Tsinghua University, Department of Automation, Bejing, China
- Hao Wang 0053 — Queen's University Belfast, School of Natural and Built Environment, UK
- Hao Wang 0054 — Aalborg University, Department of Energy Technology, Denmark
- Hao Wang 0055 — City University of Hong Kong, Department of Electronic Engineering, Hong Kong
- Hao Wang 0056 — University of Michigan, Department of Naval Architecture and Marine Engineering, Ann Arbor, MI, USA
- Hao Wang 0057 — Huawei Technologies Co Ltd, Riemann Lab, Wuhan, China (and 2 more)
- Hao Wang 0058 — Fujian University of Technology, School of Information Science and Engineering, Fuzhou, China
- Hao Wang 0059 — Southeast University, School of Transportation, Nanjing, China
- Hao Wang 0060 — Nanjing University of Information Science and Technology, School of Automation, Department of Computer and Software, China
- Hao Wang 0061 — Qingdao University of Science and Technology, College of Automation and Electronic Engineering, China
- Hao Wang 0062 — Xidian University, Xi'an, Shaanxi, China
- Hao Wang 0063 — Harvard University, Cambridge, MA, USA
- Hao Wang 0064 — University of Oregon, Eugene, OR, USA
- Hao Wang 0065 — University College London, Computer Science Departmen, UK
- Hao Wang 0066 — Jiangsu University, School of Electrical and Information Engineering, Zhenjiang, China
- Hao Wang 0067 — Fujian Normal University, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fujian, China
- Hao Wang 0068 — Southwest Jiaotong University, School of Information Science and Technology, Chengdu, China
- Hao Wang 0069 — Central South University, School of Geosciences and InfoPhysics, Changsha, China
- Hao Wang 0070 — Beijing University of Posts and Telecommunications, Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing, China
- Hao Wang 0071 — Nanjing University of Aeronautics and Astronautics, College of Electronic and Information Engineering, Nanjing, China
- Hao Wang 0072 — Tianjin University, School of Electronic Information Engineering, Tianjin, China
- Hao Wang 0073 — Harbin Institute of Technology, China
- Hao Wang 0074 — Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- Hao Wang 0075 — City University of Hong Kong, Department of Electrical Engineering, Hong Kong
- Hao Wang 0076 — University of Science and Technology of China, School of Computer Science and Technology, Anhui Province Key Laboratory of Big Data Analysis and Application, Hefei, China
- Hao Wang 0077 — Chinese University of Hong Kong, Department of Systems Engineering and Engineering Management, Hong Kong
- Hao Wang 0078 — Chalmers University of Technology, Department of Biology and Biological Engineering, Gothenburg, Sweden (and 1 more)
- Hao Wang 0079 — University of California Davis, CA, USA (and 1 more)
- Hao Wang 0080 — Jiangxi Normal University, School of Software, Nanchang, China
- Hao Wang 0081 — Hefei University of Technology, School of Management, MoE Key Laboratory of Process Optimization and Intelligent Decision-Making, China
- Hao Wang 0082 — Beihang University, School of Electronic and Information Engineering, Beijing, China
- Hao Wang 0083 — Beijing Institute of Remote Sensing Equipment, China (and 1 more)
- Hao Wang 0084 — Zhejiang University, School of Aeronautics and Astronautics, Hangzhou, China
- Hao Wang 0085 — Air Force Engineering University, Aeronautical Engineering Department, Xi'an, China
- Hao Wang 0086 — Tiangong University, School of Electrical Engineering and Automation, Tianjin Key Laboratory of Advanced Technology of Electrical Engineering and Energy, Tianjin, China
- Hao Wang 0087 — Chinese Academy of Sciences, Aerospace Information Research Institute, State Key Laboratory of Transducer Technology, Beijing, China (and 1 more)
- Hao Wang 0088 — Nanchang Hangkong University, MoE Key Laboratory of Nondestructive Test, China Jiangxi Engineering Laboratory for Optoelectronics Testing Technology, China
- Hao Wang 0089 — Beijing Sport University, China Swimming Sports College, China
- Hao Wang 0090 — Nanjing University of Aeronautics and Astronautics, College of Civil Aviation, China
- Hao Wang 0091 — Qilu University of Technology (Shandong Academy of Sciences), School of Computer Science and Technology, Jinan, China
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2020 – today
- 2020
[j5]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck:
Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. 50(3): 778-791 (2020)- [j4]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking discrete optimization heuristics with IOHprofiler. Appl. Soft Comput. 88: 106027 (2020) - [j3]Víctor Adrián Sosa-Hernández, Oliver Schütze, Hao Wang, André H. Deutz, Michael Emmerich:
The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. IEEE Trans. Cybern. 50(5): 2186-2196 (2020) - [c41]Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Can Single Solution Optimisation Methods Be Structurally Biased? CEC 2020: 1-9 - [c40]Diederick Vermetten, Hao Wang, Thomas Bäck, Carola Doerr:
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. GECCO 2020: 654-662 - [c39]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. GECCO 2020: 903-912 - [c38]Hao Wang, Carola Doerr, Ofer M. Shir, Thomas Bäck:
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion 2020: 1043-1054 - [c37]Rick Boks, Hao Wang, Thomas Bäck:
A modular hybridization of particle swarm optimization and differential evolution. GECCO Companion 2020: 1418-1425 - [c36]Ullah Ullah, Zhao Xu, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models. IJCNN 2020: 1-9 - [c35]Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr:
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. PPSN (1) 2020: 169-183 - [c34]Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Can Compact Optimisation Algorithms Be Structurally Biased? PPSN (1) 2020: 229-242 - [c33]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. PPSN (2) 2020: 699-713 - [c32]Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke:
Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. SSCI 2020: 996-1003 - [c31]Bas van Stein, Hao Wang, Thomas Bäck:
Neural Network Design: Learning from Neural Architecture Search. SSCI 2020: 1341-1349 - [c30]Sibghat Ullah, Duc Anh Nguyen, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization. SSCI 2020: 2965-2974 - [c29]Milan Koch, Hao Wang, Robert Bürgel, Thomas Bäck:
Towards Data-driven Services in Vehicles. VEHITS 2020: 45-52 - [e2]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12269, Springer 2020, ISBN 978-3-030-58111-4 [contents] - [e1]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12270, Springer 2020, ISBN 978-3-030-58114-5 [contents] - [i15]Andrés Camero, Hao Wang, Enrique Alba, Thomas Bäck:
Bayesian Neural Architecture Search using A Training-Free Performance Metric. CoRR abs/2001.10726 (2020) - [i14]Furong Ye, Hao Wang, Carola Doerr, Thomas Bäck:
Benchmarking a $(μ+λ)$ Genetic Algorithm with Configurable Crossover Probability. CoRR abs/2006.05889 (2020) - [i13]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case. CoRR abs/2006.06586 (2020) - [i12]Rick Boks, Hao Wang, Thomas Bäck:
A Modular Hybridization of Particle Swarm Optimization and Differential Evolution. CoRR abs/2006.11886 (2020) - [i11]Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr:
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. CoRR abs/2007.00925 (2020) - [i10]Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR abs/2007.03953 (2020) - [i9]Bas van Stein, Hao Wang, Thomas Bäck:
Neural Network Design: Learning from Neural Architecture Search. CoRR abs/2011.00521 (2020) - [i8]Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter:
Squirrel: A Switching Hyperparameter Optimizer. CoRR abs/2012.08180 (2020)
2010 – 2019
- 2019
- [j2]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich:
Search Dynamics on Multimodal Multiobjective Problems. Evol. Comput. 27(4): 577-609 (2019) - [j1]Hao Wang, Michael Emmerich, Thomas Bäck:
Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies. Evol. Comput. 27(4): 699-725 (2019) - [c28]Milan Koch, Victor Geraedts, Hao Wang, Martijn Tannemaat, Thomas Bäck:
Automated Machine Learning for EEG-Based Classification of Parkinson's Disease Patients. BigData 2019: 4845-4852 - [c27]Hao Wang, Yitan Lou, Thomas Bäck:
Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution. CEC 2019: 2649-2656 - [c26]Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss:
On the potential of evolution strategies for neural network weight optimization. GECCO (Companion) 2019: 191-192 - [c25]Borja Calvo, Ofer M. Shir, Josu Ceberio, Carola Doerr, Hao Wang, Thomas Bäck, José Antonio Lozano:
Bayesian performance analysis for black-box optimization benchmarking. GECCO (Companion) 2019: 1789-1797 - [c24]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking discrete optimization heuristics with IOHprofiler. GECCO (Companion) 2019: 1798-1806 - [c23]Bas van Stein, Hao Wang, Thomas Bäck:
Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. IJCNN 2019: 1-7 - [c22]Sina Däubener, Sebastian Schmitt, Hao Wang, Peter Krause, Thomas Bäck:
Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. ICDM 2019: 161-175 - [c21]Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. SSCI 2019: 819-828 - [c20]Teddy Etoeharnowo, Koen Castelein, Hao Wang, Thomas Bäck:
Switching Between Swarm Optimization Algorithms During a Run: An Empirical Study. SSCI 2019: 2295-2302 - [i7]Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. CoRR abs/1912.05899 (2019) - [i6]Carola Doerr, Furong Ye, Naama Horesh, Hao Wang, Ofer M. Shir, Thomas Bäck:
Benchmarking Discrete Optimization Heuristics with IOHprofiler. CoRR abs/1912.09237 (2019) - 2018
- [c19]Hao Wang, Michael Emmerich, Thomas Bäck:
Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. CEC 2018: 1-8 - [c18]Hao Wang, Thomas Bäck:
Ranking empirical cumulative distribution functions using stochastic and pareto dominance. GECCO (Companion) 2018: 257-258 - [c17]Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck:
Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. GECCO 2018: 951-958 - [c16]Milan Koch, Hao Wang, Thomas Bäck:
Machine Learning for Predicting the Damaged Parts of a Low Speed Vehicle Crash. ICDIM 2018: 179-184 - [c15]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck:
A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) 2018: 480-491 - [r1]Michael Emmerich, Ofer M. Shir, Hao Wang:
Evolution Strategies. Handbook of Heuristics 2018: 89-119 - [i5]Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck:
Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling (1+λ) EA Variants on OneMax and LeadingOnes. CoRR abs/1808.05850 (2018) - [i4]Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck:
IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. CoRR abs/1810.05281 (2018) - [i3]Bas van Stein, Hao Wang, Thomas Bäck:
Automatic Configuration of Deep Neural Networks with EGO. CoRR abs/1810.05526 (2018) - 2017
- [c14]Hao Wang, André H. Deutz, Thomas Bäck, Michael Emmerich:
Hypervolume Indicator Gradient Ascent Multi-objective Optimization. EMO 2017: 654-669 - [c13]Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck:
Algorithm configuration data mining for CMA evolution strategies. GECCO 2017: 737-744 - [c12]Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck:
Time complexity reduction in efficient global optimization using cluster kriging. GECCO 2017: 889-896 - [c11]Sheir Yarkoni, Hao Wang, Aske Plaat, Thomas Bäck:
Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning. QTOP@NetSys 2017: 157-168 - [c10]Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck:
A new acquisition function for Bayesian optimization based on the moment-generating function. SMC 2017: 507-512 - [i2]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR abs/1702.01313 (2017) - 2016
- [c9]Hao Wang, Michael T. M. Emmerich, Thomas Bäck:
Balancing risk and expected gain in kriging-based global optimization. CEC 2016: 719-727 - [c8]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE 2016: 939-945 - [c7]Zhiwei Yang, Hao Wang, Kaifeng Yang, Thomas Bäck, Michael Emmerich:
SMS-EMOA with multiple dynamic reference points. ICNC-FSKD 2016: 282-288 - [c6]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich:
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN 2016: 962-972 - [c5]Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck:
Evolving the structure of Evolution Strategies. SSCI 2016: 1-8 - [p1]Michael Emmerich, Kaifeng Yang, André H. Deutz, Hao Wang, Carlos M. Fonseca:
A Multicriteria Generalization of Bayesian Global Optimization. Advances in Stochastic and Deterministic Global Optimization 2016: 229-242 - [i1]Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck:
Evolving the Structure of Evolution Strategies. CoRR abs/1610.05231 (2016) - 2015
- [c4]Hao Wang, Thomas Bäck, Michael T. M. Emmerich:
Multi-point Efficient Global Optimization Using Niching Evolution Strategy. EVOLVE 2015: 146-162 - [c3]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich:
Optimally Weighted Cluster Kriging for Big Data Regression. IDA 2015: 310-321 - [c2]Hao Wang, Yiyi Ren, André H. Deutz, Michael T. M. Emmerich:
On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. NEO 2015: 175-203 - 2014
- [c1]Hao Wang, Michael Emmerich, Thomas Bäck:
Mirrored orthogonal sampling with pairwise selection in evolution strategies. SAC 2014: 154-156
Coauthor Index
[j5] [j4] [c41] [c40] [c39] [c38] [c37] [c36] [c34] [c33] [c32] [c31] [c30] [c29] [e2] [e1] [i15] [i14] [i13] [i12] [i10] [i9] [j1] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [i7] [i6] [c19] [c18] [c17] [c16] [c15] [i5] [i4] [i3] [c14] [c13] [c12] [c11] [c10] [i2] [c9] [c8] [c7] [c5] [i1] [c4] [c3] [c1]
Michael T. M. Emmerich
aka: Michael Emmerich
aka: Michael Emmerich
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