Hum Nath Bhandari

403 total citations · 1 hit paper
10 papers, 238 citations indexed

About

Hum Nath Bhandari is a scholar working on Management Science and Operations Research, Economics and Econometrics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Hum Nath Bhandari has authored 10 papers receiving a total of 238 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Management Science and Operations Research, 4 papers in Economics and Econometrics and 3 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Hum Nath Bhandari's work include Stock Market Forecasting Methods (7 papers), Advanced Chemical Physics Studies (3 papers) and Spectroscopy and Quantum Chemical Studies (2 papers). Hum Nath Bhandari is often cited by papers focused on Stock Market Forecasting Methods (7 papers), Advanced Chemical Physics Studies (3 papers) and Spectroscopy and Quantum Chemical Studies (2 papers). Hum Nath Bhandari collaborates with scholars based in United States and India. Hum Nath Bhandari's co-authors include Nawa Raj Pokhrel, Ramchandra Rimal, Keshab Raj Dahal, William L. Hase, Subha Pratihar, Moumita Majumder, Philip W. Smith, Amit Kumar Paul and Xinyou Ma and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Physical Chemistry C and The Journal of Physical Chemistry A.

In The Last Decade

Hum Nath Bhandari

9 papers receiving 226 citations

Hit Papers

Predicting stock market index using LSTM 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hum Nath Bhandari United States 7 142 77 68 28 25 10 238
Tianyi Wang China 10 31 0.2× 92 1.2× 11 0.2× 14 0.5× 99 4.0× 41 294
Sudeepa Roy Dey India 4 210 1.5× 84 1.1× 96 1.4× 85 3.0× 31 1.2× 12 275
Leonardo Rojas‐Nandayapa Australia 7 123 0.9× 37 0.5× 25 0.4× 105 3.8× 26 1.0× 19 260
Piotr Nowak Poland 10 96 0.7× 22 0.3× 136 2.0× 114 4.1× 20 0.8× 28 279
Blanka Horvath United Kingdom 8 68 0.5× 19 0.2× 76 1.1× 161 5.8× 33 1.3× 29 257
Carlos Ibarra-Valdez Mexico 8 70 0.5× 31 0.4× 441 6.5× 165 5.9× 9 0.4× 24 535
Christie Smith New Zealand 12 36 0.3× 78 1.0× 160 2.4× 94 3.4× 6 0.2× 29 386
Yumo Xu United Kingdom 5 199 1.4× 70 0.9× 75 1.1× 78 2.8× 153 6.1× 11 309
Matthias Fischer Germany 8 29 0.2× 5 0.1× 13 0.2× 30 1.1× 15 0.6× 33 276
Luca Grilli Italy 9 50 0.4× 21 0.3× 49 0.7× 21 0.8× 44 1.8× 41 226

Countries citing papers authored by Hum Nath Bhandari

Since Specialization
Citations

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

Fields of papers citing papers by Hum Nath Bhandari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hum Nath Bhandari. 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 Hum Nath Bhandari. The network helps show where Hum Nath Bhandari may publish in the future.

Co-authorship network of co-authors of Hum Nath Bhandari

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

All Works

10 of 10 papers shown
1.
Pokhrel, Nawa Raj, et al.. (2024). Deep-SDM: A Unified Computational Framework for Sequential Data Modeling Using Deep Learning Models. SHILAP Revista de lepidopterología. 3(1). 47–61. 5 indexed citations
2.
Bhandari, Hum Nath, et al.. (2024). Implementation of deep learning models in predicting ESG index volatility. Financial Innovation. 10(1). 3 indexed citations
3.
Rimal, Ramchandra, et al.. (2024). Real Estate Market Prediction Using Deep Learning Models. Annals of Data Science. 12(4). 1113–1156. 1 indexed citations
4.
Bhandari, Hum Nath, et al.. (2022). LSTM-SDM: An integrated framework of LSTM implementation for sequential data modeling. Software Impacts. 14. 100396–100396. 12 indexed citations
5.
Bhandari, Hum Nath, et al.. (2022). Predicting stock market index using LSTM. SHILAP Revista de lepidopterología. 9. 100320–100320. 155 indexed citations breakdown →
6.
Pokhrel, Nawa Raj, et al.. (2022). Predicting NEPSE index price using deep learning models. SHILAP Revista de lepidopterología. 9. 100385–100385. 22 indexed citations
7.
Pokhrel, Nawa Raj, et al.. (2022). Predicting Nepse Index Price Using Deep Learning Models. SSRN Electronic Journal. 7 indexed citations
8.
Bhandari, Hum Nath, et al.. (2019). Chemical Dynamics Simulation of Energy Transfer: Propylbenzene Cation and N2 Collisions. The Journal of Physical Chemistry A. 123(12). 2301–2309. 8 indexed citations
9.
Bhandari, Hum Nath, Xinyou Ma, Amit Kumar Paul, Philip W. Smith, & William L. Hase. (2018). PSO Method for Fitting Analytic Potential Energy Functions. Application to I(H2O). Journal of Chemical Theory and Computation. 14(3). 1321–1332. 6 indexed citations
10.
Majumder, Moumita, Hum Nath Bhandari, Subha Pratihar, & William L. Hase. (2017). Chemical Dynamics Simulation of Low Energy N2 Collisions with Graphite. The Journal of Physical Chemistry C. 122(1). 612–623. 19 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026