Jennifer (Jiaxin) Huang |
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Phone Visitor's Address |
n/a Helmholtzstrasse 18, III60 |
Jennifer (Jiaxin) obtained her bachelor’s in Communication Engineering at the Shanghai University in 2015 and her Master’s in Electrical Engineering Karlsruhe Institute of Technology in 2020. She did an industrial PhD at Infineon Technologies Dresden and then worked at SpiNNcloud Systems Gmbh.
In July 2026 she joined the chair as postdoc researcher in the context of ScaDS.AI project, with strong synergies with the COMETH ERC Consolidator Grant and the REC2 Excellence Cluster.
2026
- Hector A. Gonzalez, Javier Acevedo, Khaleelulla K. Nazeer, Clément Fournier, Abdul Rehman Aslam, Jiaxin Huang, Matthias A. Lohrmann, Robert A. Tietze, Christian Eichhorn, Stefan Gumhold, Sami Haddadin, Hamid Sadeghian, Reinhard Heckel, Frank H.P. Fitzek, Jeronimo Castrillon, Christian Mayr, "Artificial intelligence in 6G ecosystem", Chapter in 6G-life (Frank H.P. Fitzek and Holger Boche and Wolfgang Kellerer and Patrick Seeling), Academic Press, pp. 205–227, Feb 2026. [doi] [Bibtex & Downloads]
Artificial intelligence in 6G ecosystem
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Hector A. Gonzalez, Javier Acevedo, Khaleelulla K. Nazeer, Clément Fournier, Abdul Rehman Aslam, Jiaxin Huang, Matthias A. Lohrmann, Robert A. Tietze, Christian Eichhorn, Stefan Gumhold, Sami Haddadin, Hamid Sadeghian, Reinhard Heckel, Frank H.P. Fitzek, Jeronimo Castrillon, Christian Mayr, "Artificial intelligence in 6G ecosystem", Chapter in 6G-life (Frank H.P. Fitzek and Holger Boche and Wolfgang Kellerer and Patrick Seeling), Academic Press, pp. 205–227, Feb 2026. [doi]
Abstract
The future technical standard of sixth-generation (6G) technology for wireless communications has accelerated the arrival of interconnected autonomous systems and other sensing devices in a wide range of industrial zones, such as smart factories, smart farms, and cognitive cities, among others. The imminent digitalization of these ecosystems has created highly dynamic environments that demand real-time decisions, making it difficult for humans to keep up with all their details. These dynamic scenarios require planning and execution that is more precise and faster than the speed at which data is acquired. The use of Artificial Intelligence (AI) offers high potential to enable the monitoring and assessment of multi-modal sensor data at a superhuman level, leading to faster decisions with better precision, which reduces undesired automated behavior, while enabling new forms of interaction. This chapter describes techniques, software frameworks, compilation flows, and hardware infrastructure for achieving large-scale, energy-efficient, trustworthy, real-time, and distributed AI in the newly developed era of 6G ecosystems, which produce vast amounts of data. The chapter also describes an economic perspective on the challenges in achieving this vision.
Bibtex
@InCollection{gonzalez_6GBook26,
author = {Hector A. Gonzalez and Javier Acevedo and Khaleelulla K. Nazeer and Clément Fournier and Abdul Rehman Aslam and Jiaxin Huang and Matthias A. Lohrmann and Robert A. Tietze and Christian Eichhorn and Stefan Gumhold and Sami Haddadin and Hamid Sadeghian and Reinhard Heckel and Frank H.P. Fitzek and Jeronimo Castrillon and Christian Mayr},
booktitle = {6G-life},
title = {Artificial intelligence in 6G ecosystem},
doi = {https://doi.org/10.1016/B978-0-44-327410-7.00024-7},
editor = {Frank H.P. Fitzek and Holger Boche and Wolfgang Kellerer and Patrick Seeling},
isbn = {978-0-443-27410-7},
pages = {205--227},
publisher = {Academic Press},
url = {https://www.sciencedirect.com/science/article/pii/B9780443274107000247},
abstract = {The future technical standard of sixth-generation (6G) technology for wireless communications has accelerated the arrival of interconnected autonomous systems and other sensing devices in a wide range of industrial zones, such as smart factories, smart farms, and cognitive cities, among others. The imminent digitalization of these ecosystems has created highly dynamic environments that demand real-time decisions, making it difficult for humans to keep up with all their details. These dynamic scenarios require planning and execution that is more precise and faster than the speed at which data is acquired. The use of Artificial Intelligence (AI) offers high potential to enable the monitoring and assessment of multi-modal sensor data at a superhuman level, leading to faster decisions with better precision, which reduces undesired automated behavior, while enabling new forms of interaction. This chapter describes techniques, software frameworks, compilation flows, and hardware infrastructure for achieving large-scale, energy-efficient, trustworthy, real-time, and distributed AI in the newly developed era of 6G ecosystems, which produce vast amounts of data. The chapter also describes an economic perspective on the challenges in achieving this vision.},
month = feb,
year = {2026},
}Downloads
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2024
- Daniel Scholz, Oliver Emonds, Felix Kreutz, Pascal Gerhards, Jiaxin Huang, Klaus Knobloch, Alois Knoll, Christian Mayr, "Capturing Uncertainty over Time for Spiking Neural Networks by Exploiting Conformal Prediction Sets", In Proceeding: 2024 International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 107–114, Dec 2024. [doi] [Bibtex & Downloads]
Capturing Uncertainty over Time for Spiking Neural Networks by Exploiting Conformal Prediction Sets
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Daniel Scholz, Oliver Emonds, Felix Kreutz, Pascal Gerhards, Jiaxin Huang, Klaus Knobloch, Alois Knoll, Christian Mayr, "Capturing Uncertainty over Time for Spiking Neural Networks by Exploiting Conformal Prediction Sets", In Proceeding: 2024 International Conference on Machine Learning and Applications (ICMLA), IEEE, pp. 107–114, Dec 2024. [doi]
Bibtex
@inproceedings{Scholz_2024, title={Capturing Uncertainty over Time for Spiking Neural Networks by Exploiting Conformal Prediction Sets}, url={http://dx.doi.org/10.1109/ICMLA61862.2024.00021}, DOI={10.1109/icmla61862.2024.00021}, booktitle={2024 International Conference on Machine Learning and Applications (ICMLA)}, publisher={IEEE}, author={Scholz, Daniel and Emonds, Oliver and Kreutz, Felix and Gerhards, Pascal and Huang, Jiaxin and Knobloch, Klaus and Knoll, Alois and Mayr, Christian}, year={2024}, month=Dec, pages={107–114} }Downloads
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- Jiaxin Huang, Bernhard Vogginger, Florian Kelber, Hector Gonzalez, Klaus Knobloch, Christian Georg Mayr, "Fast Switching Serial and Parallel Paradigms of SNN Inference on Multi-Core Heterogeneous Neuromorphic Platform SpiNNaker2", In Proceeding: 2024 International Conference on Neuromorphic Systems (ICONS), IEEE, pp. 117–123, July 2024. [doi] [Bibtex & Downloads]
Fast Switching Serial and Parallel Paradigms of SNN Inference on Multi-Core Heterogeneous Neuromorphic Platform SpiNNaker2
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Jiaxin Huang, Bernhard Vogginger, Florian Kelber, Hector Gonzalez, Klaus Knobloch, Christian Georg Mayr, "Fast Switching Serial and Parallel Paradigms of SNN Inference on Multi-Core Heterogeneous Neuromorphic Platform SpiNNaker2", In Proceeding: 2024 International Conference on Neuromorphic Systems (ICONS), IEEE, pp. 117–123, July 2024. [doi]
Bibtex
@inproceedings{Huang_2024, title={Fast Switching Serial and Parallel Paradigms of SNN Inference on Multi-Core Heterogeneous Neuromorphic Platform SpiNNaker2}, url={http://dx.doi.org/10.1109/ICONS62911.2024.00025}, DOI={10.1109/icons62911.2024.00025}, booktitle={2024 International Conference on Neuromorphic Systems (ICONS)}, publisher={IEEE}, author={Huang, Jiaxin and Vogginger, Bernhard and Kelber, Florian and Gonzalez, Hector and Knobloch, Klaus and Mayr, Christian Georg}, year={2024}, month=July, pages={117–123} }Downloads
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- Hector A. Gonzalez, Jiaxin Huang, Florian Kelber, Khaleelulla Khan Nazeer, Tim Langer, Chen Liu, Matthias Lohrmann, Amirhossein Rostami, Mark Schöne, Bernhard Vogginger, Timo C. Wunderlich, Yexin Yan, Mahmoud Akl, Christian Mayr, "SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning", arXiv, 2024. [doi] [Bibtex & Downloads]
SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning
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Hector A. Gonzalez, Jiaxin Huang, Florian Kelber, Khaleelulla Khan Nazeer, Tim Langer, Chen Liu, Matthias Lohrmann, Amirhossein Rostami, Mark Schöne, Bernhard Vogginger, Timo C. Wunderlich, Yexin Yan, Mahmoud Akl, Christian Mayr, "SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning", arXiv, 2024. [doi]
Bibtex
@misc{https://doi.org/10.48550/arxiv.2401.04491,
doi = {10.48550/ARXIV.2401.04491},
url = {https://arxiv.org/abs/2401.04491},
author = {Gonzalez, Hector A. and Huang, Jiaxin and Kelber, Florian and Nazeer, Khaleelulla Khan and Langer, Tim and Liu, Chen and Lohrmann, Matthias and Rostami, Amirhossein and Schöne, Mark and Vogginger, Bernhard and Wunderlich, Timo C. and Yan, Yexin and Akl, Mahmoud and Mayr, Christian},
keywords = {Emerging Technologies (cs.ET), Machine Learning (cs.LG), Neural and Evolutionary Computing (cs.NE), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning},
publisher = {arXiv},
year = {2024},
copyright = {arXiv.org perpetual, non-exclusive license}
}Downloads
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2023
- Pascal Gerhards, Martin Weih, Jiaxin Huang, Klaus Knobloch, Christian Georg Mayr, "Hybrid Spiking and Artificial Neural Networks for Radar-Based Gesture Recognition", In Proceeding: 2023 8th International Conference on Frontiers of Signal Processing (ICFSP), IEEE, pp. 83–87, Oct 2023. [doi] [Bibtex & Downloads]
Hybrid Spiking and Artificial Neural Networks for Radar-Based Gesture Recognition
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Pascal Gerhards, Martin Weih, Jiaxin Huang, Klaus Knobloch, Christian Georg Mayr, "Hybrid Spiking and Artificial Neural Networks for Radar-Based Gesture Recognition", In Proceeding: 2023 8th International Conference on Frontiers of Signal Processing (ICFSP), IEEE, pp. 83–87, Oct 2023. [doi]
Bibtex
@inproceedings{Gerhards_2023, title={Hybrid Spiking and Artificial Neural Networks for Radar-Based Gesture Recognition}, url={http://dx.doi.org/10.1109/ICFSP59764.2023.10372930}, DOI={10.1109/icfsp59764.2023.10372930}, booktitle={2023 8th International Conference on Frontiers of Signal Processing (ICFSP)}, publisher={IEEE}, author={Gerhards, Pascal and Weih, Martin and Huang, Jiaxin and Knobloch, Klaus and Mayr, Christian Georg}, year={2023}, month=Oct, pages={83–87} }Downloads
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- Jiaxin Huang, Florian Kelber, Bernhard Vogginger, Chen Liu, Felix Kreutz, Pascal Gerhards, Daniel Scholz, Klaus Knobloch, Christian G. Mayr, "Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2", In Frontiers in Neuroscience, Frontiers Media SA, vol. 17, Aug 2023. [doi] [Bibtex & Downloads]
Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2
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Jiaxin Huang, Florian Kelber, Bernhard Vogginger, Chen Liu, Felix Kreutz, Pascal Gerhards, Daniel Scholz, Klaus Knobloch, Christian G. Mayr, "Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2", In Frontiers in Neuroscience, Frontiers Media SA, vol. 17, Aug 2023. [doi]
Bibtex
@article{Huang_2023, title={Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2}, volume={17}, ISSN={1662-453X}, url={http://dx.doi.org/10.3389/fnins.2023.1223262}, DOI={10.3389/fnins.2023.1223262}, journal={Frontiers in Neuroscience}, publisher={Frontiers Media SA}, author={Huang, Jiaxin and Kelber, Florian and Vogginger, Bernhard and Liu, Chen and Kreutz, Felix and Gerhards, Pascal and Scholz, Daniel and Knobloch, Klaus and Mayr, Christian G.}, year={2023}, month=Aug }Downloads
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- Felix Kreutz, Daniel Scholz, Julian Hille, Huang Jiaxin, Florian Hauer, Klaus Knobloch, Christian Georg Mayr, "Continuous Inference of Time Recurrent Neural Networks for Field Oriented Control", In Proceeding: 2023 IEEE Conference on Artificial Intelligence (CAI), IEEE, pp. 266–269, June 2023. [doi] [Bibtex & Downloads]
Continuous Inference of Time Recurrent Neural Networks for Field Oriented Control
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Felix Kreutz, Daniel Scholz, Julian Hille, Huang Jiaxin, Florian Hauer, Klaus Knobloch, Christian Georg Mayr, "Continuous Inference of Time Recurrent Neural Networks for Field Oriented Control", In Proceeding: 2023 IEEE Conference on Artificial Intelligence (CAI), IEEE, pp. 266–269, June 2023. [doi]
Bibtex
@inproceedings{Kreutz_2023, title={Continuous Inference of Time Recurrent Neural Networks for Field Oriented Control}, url={http://dx.doi.org/10.1109/cai54212.2023.00119}, DOI={10.1109/cai54212.2023.00119}, booktitle={2023 IEEE Conference on Artificial Intelligence (CAI)}, publisher={IEEE}, author={Kreutz, Felix and Scholz, Daniel and Hille, Julian and Huang, Jiaxin and Hauer, Florian and Knobloch, Klaus and Mayr, Christian Georg}, year={2023}, month=June, pages={266–269} }Downloads
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- Daniel Scholz, Felix Kreutz, Pascal Gerhards, Jiaxin Huang, Florian Hauer, Klaus Knobloch, Christian Mayr, "Augmenting Radar Data via Sampling from Learned Latent Space", In Proceeding: 2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI), IEEE, pp. 120–126, May 2023. [doi] [Bibtex & Downloads]
Augmenting Radar Data via Sampling from Learned Latent Space
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Daniel Scholz, Felix Kreutz, Pascal Gerhards, Jiaxin Huang, Florian Hauer, Klaus Knobloch, Christian Mayr, "Augmenting Radar Data via Sampling from Learned Latent Space", In Proceeding: 2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI), IEEE, pp. 120–126, May 2023. [doi]
Bibtex
@inproceedings{Scholz_2023, title={Augmenting Radar Data via Sampling from Learned Latent Space}, url={http://dx.doi.org/10.1109/CCAI57533.2023.10201307}, DOI={10.1109/ccai57533.2023.10201307}, booktitle={2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI)}, publisher={IEEE}, author={Scholz, Daniel and Kreutz, Felix and Gerhards, Pascal and Huang, Jiaxin and Hauer, Florian and Knobloch, Klaus and Mayr, Christian}, year={2023}, month=May, pages={120–126} }Downloads
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2022
- Jiaxin Huang, Pascal Gerhards, Felix Kreutz, Bernhard Vogginger, Florian Kelber, Daniel Scholz, Klaus Knobloch, Christian Georg Mayr, "Spiking Neural Network based Real-time Radar Gesture Recognition Live Demonstration", In Proceeding: 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), IEEE, pp. 500–500, June 2022. [doi] [Bibtex & Downloads]
Spiking Neural Network based Real-time Radar Gesture Recognition Live Demonstration
×Reference
Jiaxin Huang, Pascal Gerhards, Felix Kreutz, Bernhard Vogginger, Florian Kelber, Daniel Scholz, Klaus Knobloch, Christian Georg Mayr, "Spiking Neural Network based Real-time Radar Gesture Recognition Live Demonstration", In Proceeding: 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), IEEE, pp. 500–500, June 2022. [doi]
Bibtex
@inproceedings{Huang_2022, title={Spiking Neural Network based Real-time Radar Gesture Recognition Live Demonstration}, url={http://dx.doi.org/10.1109/AICAS54282.2022.9869943}, DOI={10.1109/aicas54282.2022.9869943}, booktitle={2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS)}, publisher={IEEE}, author={Huang, Jiaxin and Gerhards, Pascal and Kreutz, Felix and Vogginger, Bernhard and Kelber, Florian and Scholz, Daniel and Knobloch, Klaus and Mayr, Christian Georg}, year={2022}, month=June, pages={500–500} }Downloads
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- Jiaxin Huang, Bernhard Vogginger, Pascal Gerhards, Felix Kreutz, Florian Kelber, Daniel Scholz, Klaus Knobloch, Christian Georg Mayr, "Real-time Radar Gesture Classification with Spiking Neural Network on SpiNNaker 2 Prototype", In Proceeding: 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), IEEE, pp. 362–365, June 2022. [doi] [Bibtex & Downloads]
Real-time Radar Gesture Classification with Spiking Neural Network on SpiNNaker 2 Prototype
×Reference
Jiaxin Huang, Bernhard Vogginger, Pascal Gerhards, Felix Kreutz, Florian Kelber, Daniel Scholz, Klaus Knobloch, Christian Georg Mayr, "Real-time Radar Gesture Classification with Spiking Neural Network on SpiNNaker 2 Prototype", In Proceeding: 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), IEEE, pp. 362–365, June 2022. [doi]
Bibtex
@inproceedings{Huang_2022, title={Real-time Radar Gesture Classification with Spiking Neural Network on SpiNNaker 2 Prototype}, url={http://dx.doi.org/10.1109/aicas54282.2022.9869987}, DOI={10.1109/aicas54282.2022.9869987}, booktitle={2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS)}, publisher={IEEE}, author={Huang, Jiaxin and Vogginger, Bernhard and Gerhards, Pascal and Kreutz, Felix and Kelber, Florian and Scholz, Daniel and Knobloch, Klaus and Mayr, Christian Georg}, year={2022}, month=June, pages={362–365} }Downloads
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