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PhD Student

Michael Brunner (geb. Essich)
Michael Brunner (geb. Essich), M.Sc.

Building 9
Room 132

Phone +49 7121 271 - 4041

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Michael Brunner (geb. Essich)
Michael Brunner (geb. Essich), M.Sc.

Building 9 , Room 132

Phone +49 7121 271 - 4041

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I am a PhD student in the cognitive systems research group. Before being part of the cognitive systems research group I studied Media and Communication Computer Science (B.Sc.) and Human-Centered Computing (M.Sc.) at Reutlingen University. My work focuses on machine learning, computer vision, perception and especially the field of domain adaptation.

Publications
2023                                                                                                                                                          

Essich M., Rehmann M., Curio C., "Auxiliary Task-Guided CycleGAN for Black-Box Model Domain Adaptation", 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, 2023.

Uhlmann Y. , Brunner M., Bramlage L., Scheible J., and Curio C., "Procedural- and Reinforcement-Learning-Based Automation Methods for Analog Integrated Circuit Sizing in the Electrical Design Space", Electronics, vol. 12, no. 2, p. 302, Jan. 2023, doi: 10.3390/electronics12020302.

2022                                                                                                                                                          

Uhlmann Y., Essich M., Bramlage L., Scheible J., Curio C., "Deep Reinforcement Learning for Analog Circuit Sizing with an Electrical Design Space and Sparse Rewards", Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), Snowbird / Utah, September 2022, pp. 21-26, doi: https://doi.org/10.1145/3551901.3556474.

2021                                                                                                                                                          

Uhlmann Y., Essich M., Schweikardt M., Scheible J., Curio C. (2021) "Machine Learning Based Procedural Circuit Sizing and DC Operating Point Prediction", 17th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD), Jul. 19-22 2021.

2019                                                                                                                                                          

Essich M., Ludl D., Gulde T., Curio C. (2019) Learning to Translate Between Real World and Simulated 3D Sensors While Transferring Task Models, In Proceedings of the 7th International Conference on 3D Vision (3DV), Sept. 16-19.