Mark Nejad

2.0k total citations · 1 hit paper
43 papers, 1.3k citations indexed

About

Mark Nejad is a scholar working on Information Systems, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Mark Nejad has authored 43 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Information Systems, 18 papers in Artificial Intelligence and 10 papers in Electrical and Electronic Engineering. Recurrent topics in Mark Nejad's work include Blockchain Technology Applications and Security (24 papers), Cloud Computing and Resource Management (11 papers) and Privacy-Preserving Technologies in Data (11 papers). Mark Nejad is often cited by papers focused on Blockchain Technology Applications and Security (24 papers), Cloud Computing and Resource Management (11 papers) and Privacy-Preserving Technologies in Data (11 papers). Mark Nejad collaborates with scholars based in United States, China and Sweden. Mark Nejad's co-authors include Lena Mashayekhy, Daniel Grosu, Wanxin Li, Hao Guo, Collin Meese, Chien-Chung Shen, Athanasios V. Vasilakos, Chien‐Chung Shen, Weisong Shi and Maryam Shaygan and has published in prestigious journals such as IEEE Access, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Computers.

In The Last Decade

Mark Nejad

38 papers receiving 1.3k citations

Hit Papers

Traffic prediction using artificial intelligence: Review ... 2022 2026 2023 2024 2022 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities
    2022 117 citations Maryam Shaygan, Collin Meese et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Nejad United States 21 900 603 279 180 177 43 1.3k
Tianyu Wo China 22 840 0.9× 1.1k 1.8× 395 1.4× 72 0.4× 160 0.9× 111 1.8k
Suttipong Thajchayapong Thailand 15 276 0.3× 262 0.4× 188 0.7× 73 0.4× 130 0.7× 42 841
Lena Mashayekhy United States 19 710 0.8× 716 1.2× 144 0.5× 207 1.1× 167 0.9× 56 1.1k
Áron Lászka United States 18 399 0.4× 373 0.6× 152 0.5× 66 0.4× 203 1.1× 75 957
Yufeng Zhan China 23 510 0.6× 827 1.4× 1.1k 4.1× 131 0.7× 397 2.2× 47 2.0k
Jia-Dong Zhang Hong Kong 20 900 1.0× 257 0.4× 414 1.5× 90 0.5× 43 0.2× 41 1.5k
Cathy H. Xia United States 16 237 0.3× 449 0.7× 105 0.4× 80 0.4× 154 0.9× 64 856
Jia Xu China 20 208 0.2× 375 0.6× 417 1.5× 193 1.1× 313 1.8× 98 1.3k
Yongrui Qin United Kingdom 16 502 0.6× 876 1.5× 288 1.0× 37 0.2× 233 1.3× 67 1.4k

Countries citing papers authored by Mark Nejad

Since Specialization
Citations

This map shows the geographic impact of Mark Nejad'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 Mark Nejad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Nejad more than expected).

Fields of papers citing papers by Mark Nejad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Nejad. 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 Mark Nejad. The network helps show where Mark Nejad may publish in the future.

Co-authorship network of co-authors of Mark Nejad

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Nejad. A scholar is included among the top collaborators of Mark Nejad 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 Mark Nejad. Mark Nejad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Shaygan, Maryam, et al.. (2024). Optimizing mixed traffic environments with shared and private autonomous vehicles: An equilibrium analysis of entrance permit and tradable credit strategies. Transportation Research Part E Logistics and Transportation Review. 194. 103897–103897. 1 indexed citations
3.
Guo, Hao, Wanxin Li, Collin Meese, & Mark Nejad. (2024). Decentralized Electronic Health Records Management via Redactable Blockchain and Revocable IPFS. 167–171. 3 indexed citations
4.
Meese, Collin, Danielle Lee, Hang Chen, & Mark Nejad. (2023). vLOFT: Variable Learning Rate for Online Federated Traffic Prediction. 4247–4253. 2 indexed citations
5.
Guo, Hao, Collin Meese, Wanxin Li, Chien‐Chung Shen, & Mark Nejad. (2023). B2SFL: A Bi-Level Blockchained Architecture for Secure Federated Learning-Based Traffic Prediction. IEEE Transactions on Services Computing. 16(6). 4360–4374. 10 indexed citations
6.
Li, Wanxin, Collin Meese, Mark Nejad, & Hao Guo. (2023). ZK-BFT: A Zero-knowledge and Byzantine Fault Tolerant Consensus for Permissioned Blockchain Networks. 70–77. 1 indexed citations
7.
8.
Li, Wanxin, Collin Meese, Hao Guo, & Mark Nejad. (2023). Aggregated Zero-Knowledge Proof and Blockchain-Empowered Authentication for Autonomous Truck Platooning. IEEE Transactions on Intelligent Transportation Systems. 24(9). 9309–9323. 15 indexed citations
9.
Meese, Collin, et al.. (2022). BFRT: Blockchained Federated Learning for Real-time Traffic Flow Prediction. arXiv (Cornell University). 317–326. 20 indexed citations
10.
Li, Wanxin, Collin Meese, Hao Guo, & Mark Nejad. (2020). Blockchain-Enabled Identity Verification for Safe Ridesharing Leveraging Zero-Knowledge Proof. 18–24. 20 indexed citations
11.
Guo, Hao, Wanxin Li, Mark Nejad, & Chien‐Chung Shen. (2020). Proof-of-Event Recording System for Autonomous Vehicles: A Blockchain-Based Solution. IEEE Access. 8. 182776–182786. 33 indexed citations
12.
Guo, Hao, Wanxin Li, Mark Nejad, & Chien-Chung Shen. (2019). Access Control for Electronic Health Records with Hybrid Blockchain-Edge Architecture. 44–51. 112 indexed citations
13.
Nejad, Mark, Lena Mashayekhy, Ratna Babu Chinnam, & Anthony M. Phillips. (2015). Hierarchical time-dependent shortest path algorithms for vehicle routing under ITS. IIE Transactions. 48(2). 158–169. 8 indexed citations
14.
Mashayekhy, Lena, Mark Nejad, Daniel Grosu, & Athanasios V. Vasilakos. (2015). An Online Mechanism for Resource Allocation and Pricing in Clouds. IEEE Transactions on Computers. 65(4). 1172–1184. 121 indexed citations
15.
Mashayekhy, Lena, et al.. (2014). Energy-Aware Scheduling of MapReduce Jobs. 32–39. 20 indexed citations
16.
Mashayekhy, Lena, Mark Nejad, & Daniel Grosu. (2014). Cloud Federations in the Sky: Formation Game and Mechanism. IEEE Transactions on Cloud Computing. 3(1). 14–27. 102 indexed citations
17.
Mashayekhy, Lena, Mark Nejad, & Daniel Grosu. (2014). A two-sided market mechanism for trading big data computing commodities. 153–158. 10 indexed citations
18.
Mashayekhy, Lena, Mark Nejad, & Daniel Grosu. (2014). Physical Machine Resource Management in Clouds: A Mechanism Design Approach. IEEE Transactions on Cloud Computing. 3(3). 247–260. 40 indexed citations
19.
Nejad, Mark, Lena Mashayekhy, & Daniel Grosu. (2013). A Family of Truthful Greedy Mechanisms for Dynamic Virtual Machine Provisioning and Allocation in Clouds. 7. 188–195. 40 indexed citations
20.
Mashayekhy, Lena, Mark Nejad, & Daniel Grosu. (2013). A truthful approximation mechanism for autonomic virtual machine provisioning and allocation in clouds. 1–10. 13 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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