Tapas K. Das

2.4k total citations
80 papers, 1.7k citations indexed

About

Tapas K. Das is a scholar working on Electrical and Electronic Engineering, Management Information Systems and Modeling and Simulation. According to data from OpenAlex, Tapas K. Das has authored 80 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Electrical and Electronic Engineering, 15 papers in Management Information Systems and 11 papers in Modeling and Simulation. Recurrent topics in Tapas K. Das's work include Smart Grid Energy Management (15 papers), Supply Chain and Inventory Management (13 papers) and COVID-19 epidemiological studies (11 papers). Tapas K. Das is often cited by papers focused on Smart Grid Energy Management (15 papers), Supply Chain and Inventory Management (13 papers) and COVID-19 epidemiological studies (11 papers). Tapas K. Das collaborates with scholars based in United States, India and Chile. Tapas K. Das's co-authors include Abhijit Gosavi, Felipe Feijoo, Carlos D. Paternina-Arboleda, Sudeep Sarkar, Vikas Jain, Sridhar Mahadevan, Alex Savachkin, Yiliang Zhu, Rajesh Ganesan and O. Geoffrey Okogbaa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Management Science and Applied Energy.

In The Last Decade

Tapas K. Das

78 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tapas K. Das United States 25 564 269 261 221 193 80 1.7k
Hoang Pham United States 40 344 0.6× 152 0.6× 262 1.0× 321 1.5× 237 1.2× 212 6.5k
Lewis Ntaimo United States 24 200 0.4× 150 0.6× 144 0.6× 295 1.3× 362 1.9× 57 1.4k
Soheyl Khalilpourazari Iran 25 182 0.3× 276 1.0× 351 1.3× 323 1.5× 123 0.6× 30 1.6k
Shane G. Henderson United States 28 208 0.4× 452 1.7× 539 2.1× 178 0.8× 859 4.5× 148 2.6k
Siqian Shen United States 21 383 0.7× 205 0.8× 195 0.7× 279 1.3× 389 2.0× 86 1.5k
Miguel A. Lejeune United States 25 143 0.3× 208 0.8× 289 1.1× 350 1.6× 659 3.4× 91 1.8k
Adel Fahad Alrasheedi Saudi Arabia 17 212 0.4× 76 0.3× 147 0.6× 186 0.8× 192 1.0× 106 920
Richard J. Boucherie Netherlands 25 282 0.5× 254 0.9× 831 3.2× 87 0.4× 528 2.7× 187 2.4k
Arun Kumar India 25 560 1.0× 181 0.7× 465 1.8× 83 0.4× 487 2.5× 146 2.3k

Countries citing papers authored by Tapas K. Das

Since Specialization
Citations

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

Fields of papers citing papers by Tapas K. Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tapas K. Das. 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 Tapas K. Das. The network helps show where Tapas K. Das may publish in the future.

Co-authorship network of co-authors of Tapas K. Das

This figure shows the co-authorship network connecting the top 25 collaborators of Tapas K. Das. A scholar is included among the top collaborators of Tapas K. Das 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 Tapas K. Das. Tapas K. Das 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.
Shah, Ankit, et al.. (2025). Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation. ACM Transactions on Privacy and Security. 28(2). 1–33. 3 indexed citations
2.
Das, Tapas K., et al.. (2024). A stochastic Stackelberg problem with long-term investment decisions in Power-To-X technologies for multi-energy microgrids. Energy. 314. 134131–134131. 1 indexed citations
3.
Das, Tapas K., et al.. (2023). On radio k-labeling of the power of the infinite path. Information Processing Letters. 182. 106386–106386. 1 indexed citations
4.
5.
Das, Tapas K., et al.. (2022). An Acute Presentation of Epstein-Barr Virus (EBV) Infection in an Immunocompromised Gentleman. Cureus. 14(12). e33036–e33036. 1 indexed citations
6.
Sinha, Richa, Dipti Ranjan Mohapatra, & Tapas K. Das. (2021). Does interest rate changes have an impact on Nifty returns in long run? A Cointegration perspective. NVEO - NATURAL VOLATILES & ESSENTIAL OILS Journal | NVEO. 1338–1350.
7.
Das, Tapas K., et al.. (2021). Impact of school reopening on pandemic spread: A case study using an agent-based model for COVID-19. Infectious Disease Modelling. 6. 839–847. 8 indexed citations
8.
Das, Tapas K., et al.. (2021). Impact of vaccine prioritization strategies on mitigating COVID-19: an agent-based simulation study using an urban region in the United States. BMC Medical Research Methodology. 21(1). 272–272. 14 indexed citations
9.
Silva, Walter, Tapas K. Das, & Ricardo Izurieta. (2017). Estimating disease burden of a potential A(H7N9) pandemic influenza outbreak in the United States. BMC Public Health. 17(1). 898–898. 8 indexed citations
10.
Das, Tapas K., et al.. (2016). Design of Financial Incentive Programs to Promote Net Zero Energy Buildings. IEEE Transactions on Power Systems. 32(1). 75–84. 26 indexed citations
11.
Martínez, Diego A., Felipe Feijoo, José L. Zayas‐Castro, Scott Levin, & Tapas K. Das. (2016). A strategic gaming model for health information exchange markets. Health Care Management Science. 21(1). 119–130. 12 indexed citations
12.
Das, Tapas K., et al.. (2014). An operational epidemiological model for calibrating agent-based simulations of pandemic influenza outbreaks. Health Care Management Science. 19(1). 1–19. 15 indexed citations
13.
Das, Tapas K., et al.. (2014). Design of non-pharmaceutical intervention strategies for pandemic influenza outbreaks. BMC Public Health. 14(1). 1328–1328. 15 indexed citations
14.
Das, Tapas K., et al.. (2014). A MDP Model for Breast and Ovarian Cancer Intervention Strategies for BRCA1/2 Mutation Carriers. IEEE Journal of Biomedical and Health Informatics. 19(2). 720–727. 17 indexed citations
15.
Das, Tapas K., et al.. (2012). A Time-series Analysis of Impact of FDI on Economic Development In India during Post-reforms Era (1991-2010). MPRA Paper. 2(12). 529–545. 1 indexed citations
16.
Das, Tapas K., et al.. (2012). A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels. BMC Public Health. 12(1). 251–251. 31 indexed citations
17.
Savachkin, Alex, et al.. (2011). A predictive decision-aid methodology for dynamic mitigation of influenza pandemics. OR Spectrum. 33(3). 751–786. 28 indexed citations
18.
Das, Tapas K., et al.. (2008). A reinforcement learning algorithm for obtaining the Nash equilibrium of multi-player matrix games. IIE Transactions. 41(2). 158–167. 17 indexed citations
19.
Das, Tapas K., et al.. (2002). A reinforcement learning approach to a single leg airline revenue management problem with multiple fare classes and overbooking. IIE Transactions. 34(9). 729–742. 99 indexed citations
20.
Das, Tapas K., Vikas Jain, & Abhijit Gosavi. (1997). Economic design of dual-sampling-interval policies for X¯ charts with and without run rules. IIE Transactions. 29(6). 497–506. 22 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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