CV
Education
- Doctor of Sciences (Dr. sc.), ETH Zurich, Switzerland (Dec 2020-2025)
Department of Civil, Environmental and Geomatic Engineering, Institute for Cartography and Geoinformation
Thesis defended: 27 March 2025; Degree granted: 30 May 2025
Dissertation: Data-driven Congestion Prediction - Challenges, Solutions, and its Impact on Connected Infrastructures
https://www.research-collection.ethz.ch/handle/20.500.11850/737852 - Master of Technology (M.Tech.), Computer Science, Indian Statistical Institute, Kolkata, India (2014-2016)
Dissertation: On the Identification of Grocery Products
Award: TCS Gold Medal for best dissertation
http://dspace.isical.ac.in:8080/jspui/handle/10263/6846 - Bachelor of Technology (B.Tech.), Civil Engineering, Delhi Technological University, New Delhi, India (2010-2014), First Division
Work experience
- Postdoctoral Research Fellow, National University of Singapore (NUS), Singapore (Feb 2026-present)
PI: Dr. Prateek Bansal - Postdoctoral Researcher, Singapore-ETH Centre / ETH Zurich (Aug 2025-Sep 2025)
- PhD Researcher, Future Resilient Systems, Singapore-ETH Centre / ETH Zurich (May 2020-Jul 2025)
Mobility Information Engineering Lab (MIE Lab), ETH Zurich; Supervisor: Prof. Dr. Martin Raubal - Research Associate, Future Resilient Systems, Singapore-ETH Centre / ETH Zurich (Nov 2019-Apr 2020)
- Research Fellow (PhD Stipendiat), NTNU, Trondheim, Norway (Jun 2019-Nov 2019)
PI: Prof. Zhirong Yang - Visiting Researcher, Ariel University, Israel (Jul 2019)
PI: Dr. Bat-Hen Nahmias-Biran - Senior Research Engineer, SMART Future Urban Mobility, Singapore (Jan 2018-May 2019)
PI: Prof. Moshe Ben-Akiva - Research Engineer, SMART Future Urban Mobility, Singapore (Aug 2016-Dec 2017)
PI: Prof. Moshe Ben-Akiva - Visiting Research Scholar, Indian Statistical Institute, Kolkata, India (Jun 2016-Aug 2016)
Skills
- ML and Modelling: spatio-temporal forecasting, time-series feature engineering, complexity-aware deep learning, interpretable ML, Bayesian modelling, uncertainty quantification
- Programming and Software: Python, C/C++, MATLAB, SQL, Git, Linux shell scripting; packaging, CLI tools, testing, CI/CD, PyPI publishing
- Simulation and Transport Modelling: agent-based transport simulation and calibration (SimMobility mid-term and pre-day planning modules)
- Open Source: contributor to Matplotlib, trackintel, simmobility-prod; creator of
smartprint (46.5K+ downloads); developer of meaningful-pdf-names and LitSearch - Data Apps and Community: Streamlit-based interactive tools; Stack Overflow contributor (1,300+ reputation)
Teaching
- Teaching Assistant, TDT4173: Modern Machine Learning in Practice, NTNU, Norway (2019)
Instructor: Prof. Zhirong Yang - Co-supervision of Master’s Theses, ETH Zurich
Alexander Timmans (now PhD student, University of Amsterdam)
Jingyan Li (now PhD student, Cornell University)
Publications
- Kumar, N., Wang, Y., Chin, J.-X., & Raubal, M. (2025). Quantifying the impacts of non-recurrent congestion on workplace EV charging infrastructures. Transportation Research Part D: Transport and Environment, 146, 104869. https://doi.org/10.1016/j.trd.2025.104869
- Kumar, N., Martin, H., & Raubal, M. (2024). Enhancing Deep Learning-Based City-Wide Traffic Prediction Pipelines Through Complexity Analysis. Data Science for Transportation, 6(3), Article 24. https://doi.org/10.1007/s42421-024-00109-x
- Kumar, N., & Raubal, M. (2021). Applications of Deep Learning in Congestion Detection, Prediction and Alleviation: A Survey. Transportation Research Part C: Emerging Technologies, 133, 103432. https://doi.org/10.1016/j.trc.2021.103432
- Kumar, N., Oke, J. B., & Nahmias-Biran, B.-H. (2021). Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas. Scientific Reports, 11, 22665. https://doi.org/10.1038/s41598-021-01522-w
- Nahmias-Biran, B.-H., Oke, J. B., & Kumar, N. (2021). Who benefits from AVs? Equity implications of automated vehicles policies in full-scale prototype cities. Transportation Research Part A: Policy and Practice, 154, 92-107. https://doi.org/10.1016/j.tra.2021.09.013
- Nahmias-Biran, B.-H., Oke, J. B., Kumar, N., Lima Azevedo, C., & Ben-Akiva, M. (2021). Evaluating the impacts of shared automated mobility on-demand services: an activity-based accessibility approach. Transportation, 48(4), 1613-1638. https://doi.org/10.1007/s11116-020-10106-y
- Oh, S., Seshadri, R., Lima Azevedo, C., Kumar, N., Basak, K., & Ben-Akiva, M. (2020). Assessing the impacts of automated mobility-on-demand through agent-based simulation: A study of Singapore. Transportation Research Part A: Policy and Practice. https://doi.org/10.1016/j.tra.2020.06.009
- Nahmias-Biran, B.-H., Oke, J. B., Kumar, N., et al. (2019). From Traditional to Automated Mobility on Demand: A Comprehensive Framework for Modeling On-Demand Services in SimMobility. Transportation Research Record, 2673(12), 15-29. https://journals.sagepub.com/doi/10.1177/0361198119853553
- Ray, A., Kumar, N., Shaw, A., & Mukherjee, D. P. (2018). U-PC: Unsupervised Planogram Compliance. ECCV, 586-600. https://openaccess.thecvf.com/content_ECCV_2018/html/Archan_Ray_U-PC_Unsupervised_Planogram_ECCV_2018_paper.html
- Kumar, N., Zhang, Y., Wiedemann, N., Oke, J. B., & Raubal, M. (2025). A multiscale interpretability framework for identifying actionable road network features to mitigate congestion in highly congested cities. Under revision at Scientific Reports; ResearchSquare preprint. https://www.researchsquare.com/article/rs-4952650/v2
Talks
- World Cities Summit 2022: “Improving post-accident rescue routing: A complexity-aware approach”
- ETH Risk Centre Webinar (7 Nov 2022): “Modelling cross-domain risks through simulator coupling”
- ICRS 2024, Singapore (28-30 Aug 2024): “Explaining Road Network Resilience using Spatial Variations of Network Topology”
Peer Review Service
- Peer-review to publication ratio: 1.7:1 (Web of Science profile)
- Journals include IEEE T-ITS, Scientific Reports, Transportation Letters, Nonlinear Dynamics, Applied Soft Computing, and others
Awards and Recognition
- TCS Gold Medal, Best M.Tech. Dissertation, ISI Kolkata (2016)
- Among 27 students selected nationally for fully funded M.Tech. at ISI Kolkata
- IIT-JEE 2010: AIR 8654, percentile >98 (national-level engineering college joint examination; approx. 0.4 million students)
- AIEEE 2010: AIR 9899, percentile >99 (national-level engineering college joint examination; approx. 1.2 million students)
- 13th rank, Regional Mathematical Olympiad (RMO) 2005
Patent
- System and method for object recognition based estimation of planogram compliance, Application No. WO2018069861A1 (granted in US, WO, AUS)
