PhD Researcher
Huanzhuo Wu is a Ph.D. researcher at the Deutsche Telekom Chair of Communication Networks (ComNets) at TU Dresden, Germany. His work includes contributing to research projects, teaching, and supervising students of the faculty. His particular research interest is Big Data analysis on Blind Source Separation (BSS) and COmputing In the Network (COIN).
From 2017 to 2020, he worked on a research project named 5Gang, together with Ericsson, Robert Bosch GmbH, RWTH Aachen, and other key partners. He is the lead of the research project with the name of Software Campus NetBliSS starting 2021, in cooperation with Huawei Munich Research Center. Both projects are funded by the Federal Ministry of Education and Research Germany (BMBF). Huanzhuo holds a Master of Science in Computer Science at TU Dresden with honors. During his studies, he worked as a student assistant and completed internships at BMW AG in 2015 and Audi AG in 2016. He received his Bachelor degree in Engineering with honors in Computer Science in 2011 from Chang’an University, China.
Phone: +49 351 463-38611 Email: huanzhuo.wu(at)tu-dresden.de
SS 22
SS 21
WS 20/21
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WS 19/20
SS 19
WS 18/19
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WS 17/18
Open Topics and SHK Positions
Master Thesis
Bachelor Thesis
StudentThesis
Hauptseminar/Oberseminar/Actual Topics
Zhang, Jiajing; Wu, Huanzhuo; Shen, Shiwei; Bassoli, Riccardo; Nguyen, Giang T.; Fitzek, Frank H. P.
Evaluation of an Intelligent Task Scheduling Algorithm for 6G 3D Networking Inproceedings
In: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) (MELECON 2022), Palermo, Italy, 2022.
BibTeX
@inproceedings{Zhan2206:Evaluation, title = {Evaluation of an Intelligent Task Scheduling Algorithm for 6G 3D Networking}, author = {Jiajing {Zhang} and Huanzhuo {Wu} and Shiwei {Shen} and Riccardo {Bassoli} and Giang T. {Nguyen} and Frank H. P. {Fitzek}}, year = {2022}, date = {2022-06-14}, urldate = {2022-06-14}, booktitle = {2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) (MELECON 2022)}, address = {Palermo, Italy}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
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Wu, Huanzhuo; He, Jia; Tömösközi, Máté; Zhang, Jiajing; Fitzek, Frank H. P.
You Only Hear Once: Lightweight In-Network AI Design for Multi-Object Anomaly Detection Inproceedings
@inproceedings{Wu2206:You, title = {You Only Hear Once: Lightweight In-Network AI Design for Multi-Object Anomaly Detection}, author = {Huanzhuo {Wu} and Jia {He} and M\'{a}t\'{e} {T\"{o}m\"{o}sk\"{o}zi} and Jiajing {Zhang} and Frank H. P. {Fitzek}}, year = {2022}, date = {2022-06-13}, urldate = {2022-06-01}, booktitle = {2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) (MELECON 2022)}, address = {Palermo, Italy}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Zhang, Jiajing; Wu, Huanzhuo; Bassoli, Riccardo; Bonetto, Riccardo; Fitzek, Frank H. P.
Deep Learning-based Energy Optimization for Electric Vehicles Integrated Smart Micro Grid Inproceedings
In: 2022 IEEE International Conference on Communications (ICC): Green Communication Systems and Networks Symposium (IEEE ICC'22 - GCSN Symposium), Seoul, Korea (South), 2022.
Abstract | BibTeX
@inproceedings{Zhan2205:Deep, title = {Deep Learning-based Energy Optimization for Electric Vehicles Integrated Smart Micro Grid}, author = {Jiajing {Zhang} and Huanzhuo {Wu} and Riccardo {Bassoli} and Riccardo {Bonetto} and Frank H. P. {Fitzek}}, year = {2022}, date = {2022-05-01}, urldate = {2022-05-01}, booktitle = {2022 IEEE International Conference on Communications (ICC): Green Communication Systems and Networks Symposium (IEEE ICC'22 - GCSN Symposium)}, address = {Seoul, Korea (South)}, abstract = {\"{A}pplying renewable energy in smart micro grid (MG) is increasingly receiving attention to reducing greenhouse gas emissions. However, the mismatch between supply and demand hinders the realization of this process. With the widespread use of Electrical Vehicles (EVs) and the development of emerging Mobile Edge Clouds (MECs), intelligent energy optimization becomes a way to the addressee the challenge. Therefore, in this paper, we propose a novel two-stage approach based on Deep Learning (DL) to reduce overall energy cost for sharing EVs integrated MG by forecasting its state and optimizing EVs scheduling. Our simulation results show that the joint design of forecasting and optimization reduces the overall energy consumption and the payment to the external grid."}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Wu, Huanzhuo; Shen, Yunbin; Tömösközi, Máté; Nguyen, Giang T.; Fitzek, Frank H. P.
Demonstration of In-Network Audio Processing for Low-Latency Anomaly Detection in Smart Factories Inproceedings
In: 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC) (CCNC 2022), virtual, 2022.
Links | BibTeX
@inproceedings{Wu2201:Demonstration, title = {Demonstration of In-Network Audio Processing for Low-Latency Anomaly Detection in Smart Factories}, author = {Huanzhuo {Wu} and Yunbin {Shen} and M\'{a}t\'{e} {T\"{o}m\"{o}sk\"{o}zi} and Giang T. {Nguyen} and Frank H. P. {Fitzek}}, doi = { 10.1109/CCNC49033.2022.9700506}, year = {2022}, date = {2022-01-08}, urldate = {2022-01-08}, booktitle = {2022 IEEE 19th Annual Consumer Communications \& Networking Conference (CCNC) (CCNC 2022)}, address = {virtual}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Tömösközi, Máté; Taghouti, Maroua; Wu, Huanzhuo; Fitzek, Frank H. P.
Bitteiler: Demonstration of Efficient and Private Massive Industrial IoT Communications Inproceedings
@inproceedings{Tomo2201:Bitteiler, title = {Bitteiler: Demonstration of Efficient and Private Massive Industrial IoT Communications}, author = {M\'{a}t\'{e} {T\"{o}m\"{o}sk\"{o}zi} and Maroua {Taghouti} and Huanzhuo {Wu} and Frank H. P. {Fitzek}}, doi = { 10.1109/CCNC49033.2022.9700509}, year = {2022}, date = {2022-01-08}, urldate = {2022-01-08}, booktitle = {2022 IEEE 19th Annual Consumer Communications \& Networking Conference (CCNC) (CCNC 2022)}, address = {virtual}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Wu, Huanzhuo; Shen, Yunbin; Xiao, Xun; Hecker, Artur; Fitzek, Frank H. P.
In-Network Processing Acoustic Data for Anomaly Detection in Smart Factory Inproceedings
In: 2021 IEEE Global Communications Conference: IoT and Sensor Networks (Globecom2021 IoTSN), Madrid, Spain, 2021.
@inproceedings{Wu21:InNetworkProcessingAcousticData, title = {In-Network Processing Acoustic Data for Anomaly Detection in Smart Factory}, author = {Huanzhuo {Wu} and Yunbin {Shen} and Xun {Xiao} and Artur {Hecker} and Frank H. P. {Fitzek}}, year = {2021}, date = {2021-12-07}, urldate = {2021-12-01}, booktitle = {2021 IEEE Global Communications Conference: IoT and Sensor Networks (Globecom2021 IoTSN)}, address = {Madrid, Spain}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Wu, Huanzhuo; He, Jia; Tömösközi, Máté; Xiang, Zuo; Fitzek, Frank H. P.
In-Network Processing for Low-Latency Industrial Anomaly Detection in Softwarized Networks Inproceedings
In: 2021 IEEE Global Communications Conference: Next-Generation Networking and Internet (Globecom2021 NGNI), Madrid, Spain, 2021.
@inproceedings{Wu21:InNetworkProcessingLowLatency, title = {In-Network Processing for Low-Latency Industrial Anomaly Detection in Softwarized Networks}, author = {Huanzhuo {Wu} and Jia {He} and M\'{a}t\'{e} {T\"{o}m\"{o}sk\"{o}zi} and Zuo {Xiang} and Frank H. P. {Fitzek}}, year = {2021}, date = {2021-12-07}, urldate = {2021-12-01}, booktitle = {2021 IEEE Global Communications Conference: Next-Generation Networking and Internet (Globecom2021 NGNI)}, address = {Madrid, Spain}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Wu, Huanzhuo; Xiang, Zuo; Nguyen, Giang T.; Shen, Yunbin; Fitzek, Frank H. P.
Computing Meets Network: COIN-aware Offloading for Data-intensive Blind Source Separation Journal Article
In: IEEE Network Magazine, Special Issue , 2021.
@article{Wu2021njica, title = {Computing Meets Network: COIN-aware Offloading for Data-intensive Blind Source Separation}, author = {Huanzhuo {Wu} and Zuo {Xiang} and Giang T. {Nguyen} and Yunbin {Shen} and Frank H. P. {Fitzek}}, year = {2021}, date = {2021-09-01}, journal = {IEEE Network Magazine, Special Issue }, keywords = {}, pubstate = {published}, tppubtype = {article} }
Wu, Huanzhuo; He, Jia; Tömösközi, Máté; Fitzek, Frank H. P.
Abstraction-based Multi-object Acoustic Anomaly Detection for Low-complexity Big Data Analysis Inproceedings
In: WS17 IEEE ICC 2021 Workshop on Communication, Computing, and Networking in Cyber-Physical Systems (WS17 ICC'21 Workshop - CCN-CPS), Montreal, Canada, 2021.
@inproceedings{Wu2106:Abstraction, title = {Abstraction-based Multi-object Acoustic Anomaly Detection for Low-complexity Big Data Analysis}, author = {Huanzhuo {Wu} and Jia {He} and M\'{a}t\'{e} {T\"{o}m\"{o}sk\"{o}zi} and Frank H. P. {Fitzek}}, year = {2021}, date = {2021-06-14}, booktitle = {WS17 IEEE ICC 2021 Workshop on Communication, Computing, and Networking in Cyber-Physical Systems (WS17 ICC'21 Workshop - CCN-CPS)}, address = {Montreal, Canada}, abstract = {In the deployments of cyber-physical systems, specifically predictive maintenance and Internet of Things applications, a staggering amount of data can be harvested, transmitted, and recorded. Although the collection of large data sets can be used for many solutions, its utilization is made difficult by the increased overhead on the transmission and limited processing capabilities of the underlying physical system. For such highly correlated and extensive data, this situation is usually described as data-rich, information-poor. We propose for the first time a novel one-stage method, called Information-Abstraction-Net (IA-Net), for the detection of abnormal events in multi-object anomaly detection scenarios by utilizing highly abstracted sensory information instead of the entire sampled data set to elevate the transmission and analysis needs of the system. We find that the computation complexity of IA-Net is reduced by half compared to competing solutions and the detection accuracy is increased by about 5-47%, as well.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }
Wu, Huanzhuo; Shen, Yunbin; Zhang, Jiajing; Salah, Hani; Tsokalo, Ievgenii A.; Fitzek, Frank H. P.
Adaptive Extraction-Based Independent Component Analysis for Time-Sensitive Applications Inproceedings
In: 2020 IEEE Global Communications Conference: Selected Areas in Communications: Internet of Things and Smart Connected Communities (Globecom2020 SAC IoTSCC), 2020.
@inproceedings{Wu2020b, title = {Adaptive Extraction-Based Independent Component Analysis for Time-Sensitive Applications}, author = {Huanzhuo {Wu} and Yunbin {Shen} and Jiajing {Zhang} and Hani {Salah} and Ievgenii A. {Tsokalo} and Frank H. P. {Fitzek}}, year = {2020}, date = {2020-12-07}, booktitle = {2020 IEEE Global Communications Conference: Selected Areas in Communications: Internet of Things and Smart Connected Communities (Globecom2020 SAC IoTSCC)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} }