Nishant Kumar

504 total citations
8 papers, 341 citations indexed

About

Nishant Kumar is a scholar working on Automotive Engineering, Transportation and Control and Systems Engineering. According to data from OpenAlex, Nishant Kumar has authored 8 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Automotive Engineering, 5 papers in Transportation and 2 papers in Control and Systems Engineering. Recurrent topics in Nishant Kumar's work include Transportation and Mobility Innovations (5 papers), Transportation Planning and Optimization (5 papers) and Sharing Economy and Platforms (2 papers). Nishant Kumar is often cited by papers focused on Transportation and Mobility Innovations (5 papers), Transportation Planning and Optimization (5 papers) and Sharing Economy and Platforms (2 papers). Nishant Kumar collaborates with scholars based in United States, Singapore and Israel. Nishant Kumar's co-authors include Martin Raubal, Moshe Ben‐Akiva, Carlos Lima Azevedo, Bat-hen Nahmias–Biran, Ravi Seshadri, Jimi Oke, Kakali Basak, Simon Oh, Andrea Araldo and Arun Prakash Akkinepally and has published in prestigious journals such as Scientific Reports, Transportation Research Part C Emerging Technologies and Transportation Research Part A Policy and Practice.

In The Last Decade

Nishant Kumar

8 papers receiving 322 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Nishant Kumar United States	7	269	245	108	82	43	8	341
Arun Prakash Akkinepally United States	10	273 1.0×	229 0.9×	76 0.7×	54 0.7×	44 1.0×	13	334
Junyi Ji United States	8	201 0.7×	123 0.5×	144 1.3×	64 0.8×	16 0.4×	22	328
Kaveh Farokhi Sadabadi United States	7	285 1.1×	138 0.6×	194 1.8×	132 1.6×	45 1.0×	24	384
Kakali Basak Singapore	8	259 1.0×	240 1.0×	86 0.8×	62 0.8×	49 1.1×	14	327
David Charypar Switzerland	9	339 1.3×	246 1.0×	84 0.8×	134 1.6×	17 0.4×	23	398
Zhengfei Zheng Hong Kong	6	388 1.4×	249 1.0×	240 2.2×	134 1.6×	104 2.4×	12	476
Federico Rossi United States	8	231 0.9×	302 1.2×	62 0.6×	103 1.3×	64 1.5×	25	392
Claudio Ruch Switzerland	11	266 1.0×	342 1.4×	89 0.8×	101 1.2×	110 2.6×	19	428
Andrea Araldo France	9	140 0.5×	141 0.6×	38 0.4×	37 0.5×	25 0.6×	29	278
Nicolai Mallig Germany	9	191 0.7×	235 1.0×	50 0.5×	39 0.5×	75 1.7×	22	309

Countries citing papers authored by Nishant Kumar

Since Specialization

Citations

This map shows the geographic impact of Nishant Kumar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nishant Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nishant Kumar more than expected).

Fields of papers citing papers by Nishant Kumar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nishant Kumar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nishant Kumar. The network helps show where Nishant Kumar may publish in the future.

Co-authorship network of co-authors of Nishant Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Nishant Kumar. A scholar is included among the top collaborators of Nishant Kumar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nishant Kumar. Nishant Kumar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

Kumar, Nishant, Henry Martin, & Martin Raubal. (2024). Enhancing Deep Learning-Based City-Wide Traffic Prediction Pipelines Through Complexity Analysis. Repository for Publications and Research Data (ETH Zurich). 6(3). 2 indexed citations

Kumar, Nishant & Martin Raubal. (2021). Applications of deep learning in congestion detection, prediction and alleviation: A survey. Transportation Research Part C Emerging Technologies. 133. 103432–103432. 76 indexed citations

Kumar, Nishant, Jimi Oke, & Bat-hen Nahmias–Biran. (2021). Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas. Scientific Reports. 11(1). 22665–22665. 6 indexed citations

Nahmias–Biran, Bat-hen, Jimi Oke, & Nishant Kumar. (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. 16 indexed citations

Nahmias–Biran, Bat-hen, Jimi Oke, Nishant Kumar, Carlos Lima Azevedo, & Moshe Ben‐Akiva. (2020). Evaluating the impacts of shared automated mobility on-demand services: an activity-based accessibility approach. Transportation. 48(4). 1613–1638. 44 indexed citations

Oh, Simon, Ravi Seshadri, Carlos Lima Azevedo, et al.. (2020). Assessing the impacts of automated mobility-on-demand through agent-based simulation: A study of Singapore. Transportation Research Part A Policy and Practice. 138. 367–388. 80 indexed citations

Nahmias–Biran, Bat-hen, Jimi Oke, Nishant Kumar, et al.. (2019). From Traditional to Automated Mobility on Demand: A Comprehensive Framework for Modeling On-Demand Services in SimMobility. Transportation Research Record Journal of the Transportation Research Board. 2673(12). 15–29. 21 indexed citations

Basu, Rounaq, Andrea Araldo, Arun Prakash Akkinepally, et al.. (2018). Automated Mobility-on-Demand vs. Mass Transit: A Multi-Modal Activity-Driven Agent-Based Simulation Approach. Transportation Research Record Journal of the Transportation Research Board. 2672(8). 608–618. 96 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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