Dr.-Ing. Xiang Xie
- PhD Defense: 31.01.2023
- Artificial Intelligence for Spectral Analysis: a Comprehensive Framework
- Group: Prof. Stork
- Phone: +49 721 608-42499
- xiang xie ∂does-not-exist.kit edu
Engesserstr. 5
76131 Karlsruhe
Dr.-Ing. Xiang Xie
Curriculum Vitae
- Bachelor degree in mechatronics from Tongji University, Shanghai
- Bachelor thesis: Design and implementation of a stand-alone software for automated analysis and display of measurement data at VW AG in Wolfsburg, Germany
- Master studies in electrical engineering and information technology at KIT
- Master thesis: Evaluation and optimization of the filter approach for feature selection based on evaluation data sets
- Research associate at ITIV since July 2019
- PhD finished in January 2023: "Artificial Intelligence for Spectral Analysis: a Comprehensive Framework"
Supervised completed student theses (selection)
- MA: "Conception and Optimization of an X-Ray Flouresence based Thickness and Concentration Measurement Method of Coating using Neural Networks and Meta Learning Techniques"
- MA: "Implementation, Optimization and Evaluation of a Feature Selection Method with Evolutionary Algorithm".
- MA: "Application of Reinforcement Learning Algorithms in Spectral Analysis".
- MA: "Implementation and Evaluation of Deep Reinforcement Learning Algorithms and their Ability to Generalize in a Virtual Environment".
- MA: "Implementation and Evaluation of a Recommender System based on Multi-Label Classication Algorithms for the Identication of Composition of Unknown Alloys"
- MA: "Feature-Selection-Based Iterative Pruning for Neural Network Compression".
- MA: "Automatic Calibration of Neural-Network-Based X-Ray fluorescence Analysis Using Meta-Learning Techniques"
- MA: "Adaptation and Extension of Deep Reinforcement Learning Algorithms for Applicability to a TurtleBot3"
| Titel | Type | Datum |
|---|---|---|
| Deep learning approach to driving behavior prediction with data fusion. | Masterarbeit | ab 03 / 2023 |
| Meta-learning: learning to learn. Generalization of neural network capability for task series. | Bachelor-/ Masterarbeit | ab 03 / 2023 |
| Machine learning algorithms for multi-label classification problems. | Bachelor-/ Masterarbeit | ab 03 / 2023 |
| Feature selection and model compression: fast, efficient and explainable machine learning | Bachelor-/ Masterarbeit | ab 03 / 2023 |
| Cross-platform deployment and update of neural networks | Bachelor-/ Masterarbeit | ab 03 / 2023 |
| Train your own AI agent with Reinforcement Learning: Gaming, dynamic controlling like a pro | Bachelor-/ Masterarbeit | ab 03 / 2023 |
| Title |
|---|
| Building a deep learning framework for driving behavior prediction with data fusion. |
Publications
2023
PhD Theses
Artificial Intelligence for Spectral Analysis: a Comprehensive Framework. PhD dissertation
Xie, X.
2023, April 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000157893
Xie, X.
2023, April 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000157893
2022
Journal Articles
RGB Image- and Lidar-Based 3D Object Detection Under Multiple Lighting Scenarios
Chen, W.; Tian, W.; Xie, X.; Stork, W.
2022. Automotive Innovation, 5 (3), 251–259. doi:10.1007/s42154-022-00176-2
Chen, W.; Tian, W.; Xie, X.; Stork, W.
2022. Automotive Innovation, 5 (3), 251–259. doi:10.1007/s42154-022-00176-2
Conference Papers
PA-DCGAN: Efficient Spectrum Generation using Physics-Aware Deep Convolutional Generative Adversarial Network with Latent Physical Characteristics and Constraints
Xie, X.; Gao, Y.; Stork, W.
2022. 2022 IEEE Symposium Series on Computational Intelligence (SSCI), Singapore, Singapore, 04-07 December 2022, 1164–1171, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SSCI51031.2022.10022246
Xie, X.; Gao, Y.; Stork, W.
2022. 2022 IEEE Symposium Series on Computational Intelligence (SSCI), Singapore, Singapore, 04-07 December 2022, 1164–1171, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SSCI51031.2022.10022246
Efficient Comprehensive Element Identification in Large Scale Spectral Analysis with Interpretable Dimension Reduction
Xie, X.; Stork, W.
2022. IEEE International Conference on Big Data (Big Data), Osaka, Japan, 17th-20th December 2022, 5623–5631, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData55660.2022.10020993
Xie, X.; Stork, W.
2022. IEEE International Conference on Big Data (Big Data), Osaka, Japan, 17th-20th December 2022, 5623–5631, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData55660.2022.10020993
Enabling Real-Time Low-Cost Spectral Analysis on Edge Devices with Deep Neural Networks: a Robust Hybrid Approach
Xie, X.; Chen, T.; Stork, W.
2022. IEEE International Conference on Big Data (Big Data), Osaka, Japan, 17th-20th December 2022, 2431–2436, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData55660.2022.10020541
Xie, X.; Chen, T.; Stork, W.
2022. IEEE International Conference on Big Data (Big Data), Osaka, Japan, 17th-20th December 2022, 2431–2436, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData55660.2022.10020541
Minimal Cost Device Calibration in Spectral Analysis via Meta Learning: Towards Efficient Deployment of Deep Neural Networks in Industry
Xie, X.; Jin, M.; Chu, A.; Stork, W.
2022. IEEE International Conference on Big Data (Big Data), Osaka, Japan, 17th-20th December 2022, 2123–2132, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData55660.2022.10020366
Xie, X.; Jin, M.; Chu, A.; Stork, W.
2022. IEEE International Conference on Big Data (Big Data), Osaka, Japan, 17th-20th December 2022, 2123–2132, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData55660.2022.10020366
Efficient Network Pruning via Feature Selection
Xie, X.; Chen, T.; Chu, A.; Stork, W.
2022. 2022 26th International Conference on Pattern Recognition (ICPR), 1843–1850, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICPR56361.2022.9956190
Xie, X.; Chen, T.; Chu, A.; Stork, W.
2022. 2022 26th International Conference on Pattern Recognition (ICPR), 1843–1850, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICPR56361.2022.9956190
Large-Scale Spectral Analysis for Element Quantification using Deep Neural Networks
Xie, X.; Stork, W.
2022. 2022 International Joint Conference on Neural Networks (IJCNN), Padua, Italy, 18-23 July 2022, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IJCNN55064.2022.9891970
Xie, X.; Stork, W.
2022. 2022 International Joint Conference on Neural Networks (IJCNN), Padua, Italy, 18-23 July 2022, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IJCNN55064.2022.9891970
2020
Conference Papers
Watermelon: a Novel Feature Selection Method Based on Bayes Error Rate Estimation and a New Interpretation of Feature Relevance and Redundancy
Xie, X.; Stork, W.
2020. Proceedings of ICPR 2020 25th International Conference on Pattern Recognition, Milan, 10 – 15 January 2021, 1360–1367, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICPR48806.2021.9413262
Xie, X.; Stork, W.
2020. Proceedings of ICPR 2020 25th International Conference on Pattern Recognition, Milan, 10 – 15 January 2021, 1360–1367, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICPR48806.2021.9413262