Dr. ir. P. K. (Panchamy Krishnan) Krishnakumari
Panchamy Krishnakumari is an Assistant Professor of data-driven multiscale modeling for traffic and transportation and co-director of the Artificial Intelligence for Mobility Lab at the Department of Transport & Planning. Her research is on developing interpretable machine learning models for understanding the mobility dynamics of large-scale multimodal networks. She has a background in Computer Science with double MSc degrees from KTH Sweden and TU Delft Netherlands. Her interest in finding patterns in data lead her to the transport domain and to conduct her doctoral research at TU Delft in multiscale pattern recognition of transport network dynamics and its applications. She received a Cum Laude for her Ph.D. dissertation from TU Delft in February 2020. Parallel to her Ph.D., she worked part-time as a Traffic Data Scientist at CGI Netherlands B. V. for three years.
- Krishnakumari, Panchamy, Oded Cats, and Hans van Lint. A compact and scalable representation of network traffic dynamics using shapes and its applications. Transportation Research Part C: Emerging Technologies 121 (2020): 102850.
- Krishnakumari, Panchamy, Hans van Lint, Tamara Djukic, and Oded Cats. A data driven method for OD matrix estimation. Transportation Research Part C: Emerging Technologies 113 (2020): 38-56.
- Krishnakumari, Panchamy, Oded Cats, and Hans van Lint. Estimation of metro network passenger delay from individual trajectories. Transportation Research Part C: Emerging Technologies 117 (2020): 102704.
- Krishnakumari, Panchamy, Oded Cats, and Hans van Lint. Heuristic Coarsening for Generating Multiscale Transport Networks. IEEE Transactions on Intelligent Transportation Systems 21, no. 6 (2019): 2240-2253.
- Nguyen, Tin T., Panchamy Krishnakumari, Simeon C. Calvert, Hai L. Vu, and Hans Van Lint. Feature extraction and clustering analysis of highway congestion. Transportation Research Part C: Emerging Technologies 100 (2019): 238-258.
- Lopez, Clélia, Ludovic Leclercq, Panchamy Krishnakumari, Nicolas Chiabaut, and Hans Van Lint. Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps. Scientific Reports 7, no. 1 (2017): 1-11.
Faculty of Civil Engineering and Geosciences
2628 CN Delft
Transport & Planning