Cheng Yang
Doctoral student
Researcher
About me
I am a PhD student at the Division of Information Science and Engineering (ISE) since June 2022, under the supervision of Prof. Tobias Oechtering and Prof. Saikat Chatterjee. I received my master's degree in Information and Network Engineering in 2021 from KTH, Sweden (thesis: Data-driven Dynamic Baseline Calibration Method for Gas Sensors, patent), and my bachelor's degree in Electronic Information Engineering in 2019 from Zhejiang University, China.
Research
I am currently working on research projects involving gas sensor calibration and sensor fusion. My research interests primarily focus on applying statistical tools to understand why and how sensors drift, as well as developing smart calibration algorithms.
Recent papers:
- C. Yang and T. J. Oechtering, "Mean-Reverting Stochastic Modeling of Instrumental Drift in NDIR CO2 Sensors," 2025 IEEE SENSORS, Vancouver, BC, Canada, 2025, pp. 1-4，
- C. Yang, S. Chatterjee and T. J. Oechtering, "Enhancing Network Calibration for Low-Cost Gas Sensor Networks Through Adaptive Similarity Search," ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing, Hyderabad, India, 2025, pp. 1-5,
- C. Yang, G. Bohlin and T. Oechtering, "Environmental Variation or Instrumental Drift? A Probabilistic Approach to Gas Sensor Drift Modeling and Evaluation," 2024 IEEE SENSORS, Kobe, Japan, 2024, pp. 1-4
Teaching
I am the teaching assistant of the course EQ1220 Signal Theory, which is about stochastic process and its applications in estimation, filtering, signal sampling and reconstruction, etc.
I supervise groups of students in the project course EQ2443 Project in Information Engineering. The topics in 2022 and 2023 were gas sensor network calibration and sensor fusion.
The master thesis project that I have supervised:
Ci Song, thesis: Predictive Maintenance for Air-Conditioning Refrigeration and Heat Pump Systems: Data-driven Condition Monitoring and Fault Detection for Compressors
Jike Li, thesis: CO2 Sensor: Outlier Detection, Calibration and Prediction