Qin Lin(林勤)

Ph.D. Candidate
Delft University of Technology
E-mail: q.lin[at]tudelft[dot]nl
office: HB11. 160, EEMCS


I am a Third-year PhD student in Group of Cyber Security, Delft University of Technology. My PhD supervisor is Dr. Sicco Verwer. My research interests include machine learning, grammatical inference, and time series data mining.


Research Interest

Grammatical Inference (Automata Learning), Syntactic Pattern Recognition, Time Series Mining


My current research is about time series data mining using symbolic and hierarchical representation, which is applied in renewable energy and autonomous driving area.


My research is funded by Technologiestichting STW VENI project 13136 (MANTA) and NWO project 62001628 (LEMMA).


My Google Scholar profile

  1. Vertically Correlated Echelon Model for the Interpolation of Missing Wind Speed Data, Q. Lin, J. Wang, Sustainable Energy, IEEE Transactions on 5 (3), 804-812

  2. Automatic Contour-Based Road Network Design for Optimized Wind Farm Micrositing, H. Gu, J. Wang, Q. Lin, Q. Gong, Sustainable Energy, IEEE Transactions on 6 (1), 281-289


  1. Denoising of wind speed data by wavelet thresholding, Q. Lin, J. Wang, W. Qiao, Chinese Automation Congress (CAC), 2013, 518-521

  2. Short-term Time Series Forecasting with Regression Automata, Q. Lin, C. Hammerschmidt, G. Pellegrino, S. Verwer, ACM SIGKDD’16 Workshop on Mining and Learning from Time Series (MiLeTS), San Francisco, USA, 14 August 2016

  3. Learning Deterministic Finite Automata from Infinite Alphabets, G. Pellegrino, C. Hammerschmidt, Q. Lin, S. Verwer, the 13th International Conference on Grammatical Inference (ICGI), Delft, the Netherlands, October 5-7, 2016

  4. Probabilistic Model Learning from Noisy Data, Q. Lin, G. Pellegrino, S. Verwer, the 13th International Conference on Grammatical Inference (ICGI), Delft, the Netherlands, October 5-7, 2016 (Extended Abstract)

  5. Interpreting Finite Automata for Sequential Data, C. Hammerschmidt, S. Verwer, Q. Lin, R. State, Interpretable ML for Complex Systems NIPS 2016 Workshop, Barcelona, Spain, 9 December, 2016

  6. Car-following Behaviors Using Timed Automata, Y. Zhang, Q. Lin, J. Wang, S. Verwer, the 20th World Congress of the International Federation of Automatic Control (IFAC 2017), Toulouse, France, 9-14 July, 2017

  7. Behavior Generation Algorithm in Car-following Scenarios, Y. Zhang, Q. Lin, J. Wang, S. Verwer, J. Dolan, 25th International Symposium on Dynamics of Vehicles on Roads and Tracks (IAVSD 2017), Queensland, Australia, 14-18 August, 2017

  8. Detection in a Digital Video Broadcasting System Using Timed Automata, X. Liu, Q. Lin, S. Verwer, D. Jarnikov, Thirty-Second Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) Workshop on Learning and Automata (LearnAut), Reykjavik, Iceland, 19 June, 2017


  1. Interpolation Techniques Based on Wind Speed Correlation for Anemometers’ Missing Data in Wind Farm (基于风速相关性的风电场测风仪风速缺失数据插补方法), J. Wang, Q. Lin, Patent Number: ZL201310119605.8, Publication Date: 20-01-2016, Certificate Number: 1926442 (Chinese Invention Patent).

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