Chaofan Li
Karlsruhe Institute of Technology (KIT)
Campus Süd
Institute of Telematics
Chair for Pervasive Computing Systems / TECO
Vincenz-Prießnitz-Straße 1
76131 Karlsruhe
Germany
Building 07.07, Room 214
email: li(at)teco.edu
phone: +49 152 386-44903
SHORT CV
- since 2021 Ph.D. student and research associate in Computer Science at TECO
- 2018 – 2021 M.Sc. in Informatics from Karlsruhe Institute of Technology (KIT), Germany
- 2012 – 2016 B.Sc. in Computer Science and Technology from Harbin Institute of Technology (HIT), China
PROJECTS
- Since 2021 Urban Aerosol Distribution Prediction System Using Heterogeneous and Uncertain Data Sources
RESEARCH INTERESTS
- Machine Learning
- Natural Language Processing
PUBLICATION
2025
Computing with Smart Rings: A Systematic Literature Review
Wang, Z.; Yu, R.; Wang, X.; Ding, J.; Tang, J.; Fang, J.; He, Z.; Li, Z.; Röddiger, T.; Xu, W.; Zhang, X.; Gao, H.- ang; Gao, N.; Yu, C.; Shi, Y.; Wang, Y.
2025. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 9 (3), 54 S. doi:10.1145/3749480
Wang, Z.; Yu, R.; Wang, X.; Ding, J.; Tang, J.; Fang, J.; He, Z.; Li, Z.; Röddiger, T.; Xu, W.; Zhang, X.; Gao, H.- ang; Gao, N.; Yu, C.; Shi, Y.; Wang, Y.
2025. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 9 (3), 54 S. doi:10.1145/3749480
2024
Deep Neural Network Pruning with Progressive Regularizer
Zhou, Y.; Zhao, H.; Hefenbrock, M.; Li, S.; Beigl, M.
2024. 2024 IEEE International Joint Conference on Neural Network (IJCNN 2024), Yokohama, 30th June - 05 July 2024, Institute of Electrical and Electronics Engineers (IEEE)
Zhou, Y.; Zhao, H.; Hefenbrock, M.; Li, S.; Beigl, M.
2024. 2024 IEEE International Joint Conference on Neural Network (IJCNN 2024), Yokohama, 30th June - 05 July 2024, Institute of Electrical and Electronics Engineers (IEEE)
SciEx: Benchmarking Large Language Models on Scientific Exams with Human Expert Grading and Automatic Grading
Dinh, T. A.; Mullov, C.; Bärmann, L.; Li, Z.; Liu, D.; Reiß, S.; Lee, J.; Lerzer, N.; Ternava, F.; Gao, J.; Röddiger, T.; Waibel, A.; Asfour, T.; Beigl, M.; Stiefelhagen, R.; Dachsbacher, C.; Böhm, K.; Niehues, J.
2024. arxiv. doi:10.48550/arXiv.2406.10421
Dinh, T. A.; Mullov, C.; Bärmann, L.; Li, Z.; Liu, D.; Reiß, S.; Lee, J.; Lerzer, N.; Ternava, F.; Gao, J.; Röddiger, T.; Waibel, A.; Asfour, T.; Beigl, M.; Stiefelhagen, R.; Dachsbacher, C.; Böhm, K.; Niehues, J.
2024. arxiv. doi:10.48550/arXiv.2406.10421
2023
Automated Feature Engineering for Time Series Data. Bachelorarbeit
Li, K.
2023, August 1. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000161671
Li, K.
2023, August 1. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000161671
State Graph Based Explanation Approach for Black-Box Time Series Model
Huang, Y.; Li, C.; Lu, H.; Riedel, T.; Beigl, M.
2023. Explainable Artificial Intelligence – First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III, Ed.: L. Longo, 153 – 164, Springer Nature Switzerland. doi:10.1007/978-3-031-44070-0_8
Huang, Y.; Li, C.; Lu, H.; Riedel, T.; Beigl, M.
2023. Explainable Artificial Intelligence – First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III, Ed.: L. Longo, 153 – 164, Springer Nature Switzerland. doi:10.1007/978-3-031-44070-0_8
2022
Weights Assimilation for Split Manufacturing of Printed Neuromorphic Circuits. Bachelorarbeit
Li, S.
2022, Dezember 30. doi:10.5445/IR/1000158919
Li, S.
2022, Dezember 30. doi:10.5445/IR/1000158919
SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors
Li, C.; Budde, M.; Tremper, P.; Schäfer, K.; Riesterer, J.; Redelstein, J.; Petersen, E.; Khedr, M.; Liu, X.; Köpke, M.; Hussain, S.; Ernst, F.; Kowalski, M.; Pesch, M.; Werhahn, J.; Hank, M.; Philipp, A.; Cyrys, J.; Schnelle-Kreis, J.; Grimm, H.; Ziegler, V.; Peters, A.; Emeis, S.; Riedel, T.; Beigl, M.
2022. ProScience, 8. doi:10.14644/dust2021.001
Li, C.; Budde, M.; Tremper, P.; Schäfer, K.; Riesterer, J.; Redelstein, J.; Petersen, E.; Khedr, M.; Liu, X.; Köpke, M.; Hussain, S.; Ernst, F.; Kowalski, M.; Pesch, M.; Werhahn, J.; Hank, M.; Philipp, A.; Cyrys, J.; Schnelle-Kreis, J.; Grimm, H.; Ziegler, V.; Peters, A.; Emeis, S.; Riedel, T.; Beigl, M.
2022. ProScience, 8. doi:10.14644/dust2021.001
Neural Kernel Network Deep Kernel Learning for Predicting Particulate Matter from Heterogeneous Sensors with Uncertainty
Li, C.; Riedel, T.; Beigl, M.
2022. Information Integration and Web Intelligence – 24th International Conference, iiWAS 2022, Virtual Event, November 28–30, 2022, Proceedings. Ed.: E. Pardede, 252–266, Springer Nature Switzerland. doi:10.1007/978-3-031-21047-1_22
Li, C.; Riedel, T.; Beigl, M.
2022. Information Integration and Web Intelligence – 24th International Conference, iiWAS 2022, Virtual Event, November 28–30, 2022, Proceedings. Ed.: E. Pardede, 252–266, Springer Nature Switzerland. doi:10.1007/978-3-031-21047-1_22