Postdoctoral Researcher, HUMAN Lab, University of California, Los Angeles
Ph.D. in Transportation Engineering, IIT Kharagpur
I study how people make travel decisions when the air is polluted, the day is hot or the information is new, and I build the methods and tools that turn this evidence into better routes, prices and policies. At UCLA I work with Prof. Youngseo Kim on structured discrete choice estimation and on how heat shapes daily activity and travel. I received my Ph.D. from IIT Kharagpur (advisor: Prof. Arkopal Kishore Goswami) and my M.Tech from IIT Roorkee (advisor: Prof. Amit Agarwal), and was a visiting research fellow at the Institute for Transport Studies, University of Leeds, in 2024.
| Transportation | Environment | AI & data science |
|---|---|---|
| How people choose modes and routes | Pollution and heat on the road | Interpretable models from sparse data |
- Patent. Personalised dynamic route planning system for sustainable urban mobility. Indian Patent Application No. 202631018379, published July 2026.
- In the press. The Hindu featured DRUM, our pollution-aware routing app (June 2025).
- TRB 2027. Two papers accepted for presentation at the 106th Annual Meeting, Washington, DC.
- Record. 9 journal articles, 6 manuscripts under review and 17 conference papers. Reviewer for 8 journals.
| Project | What it does | Built with |
|---|---|---|
| DRUM code |
Pollution-aware route planning for commuters: five routes from live air-quality and traffic data, including the least-exposure and least-energy options. Basis of the patent and a TRR paper. | React, Python, GraphHopper, Mapbox |
| Choice experiment platform | Adaptive stated-preference surveys with live response analysis. The instrument behind a two-wave panel of 723 Kolkata commuters. | React, Node.js, MongoDB |
| Next-day PM2.5 forecasting code |
Machine-learning forecasts of next-day fine particulate concentrations for cities worldwide, in an interactive viewer. | Python, scikit-learn |
| India air-quality dashboard | City-level analysis of real-time air quality across India. | Streamlit, Plotly |
| Mode-share dashboard code |
Cycling and motorcycle mode share in cities worldwide, with a model that predicts it. | JavaScript |
| Bharat Districts Explorer | District-level demographic and spatial data for India on an interactive map. | D3.js |
- Meena, K. K., Goswami, A. K. (2026). Not all travellers think alike: Segmenting travel behaviour under air pollution exposure using a hybrid latent class and discrete choice approach. Transportation Research Record. doi:10.1177/03611981261429472
- Meena, K. K., Singh, A. K., Goswami, A. K. (2025). Dynamic route planning for urban green mobility: Development of a web application offering sustainable route options to commuters. Transportation Research Record. doi:10.1177/03611981251331011
- Meena, K. K., Goswami, A. K. (2024). A review of air pollution exposure impacts on travel behaviour and way forward. Transport Policy, 154, 48–60. doi:10.1016/j.tranpol.2024.05.024
- Meena, K. K., Bairwa, D., Agarwal, A. (2024). A machine learning approach for unraveling the influence of air quality awareness on travel behavior. Decision Analytics Journal, 11, 100459. doi:10.1016/j.dajour.2024.100459
- Meena, K. K., Singh, V., Agarwal, A. (2023). Perception of commuters towards air quality in Delhi. Journal of Transport & Health, 31, 101643. doi:10.1016/j.jth.2023.101643
The full list is on my website and Google Scholar.
Modelling: discrete choice (hybrid latent class, ICLV, mixed logit, nested logit), panel
econometrics, stated-preference design, willingness-to-pay estimation, MCDM
Machine learning: deep learning, interpretable ML, geostatistics and kriging, LSTM and Prophet,
computer vision for the built environment
Software: Python, R, JavaScript, React, Node.js, SQL, MongoDB, Git, LaTeX, NLOGIT, SPSS,
VISSIM, QGIS, Tableau, D3.js
Fieldwork: low-cost sensor deployment, on-road exposure measurement by travel mode, panel
surveys