Arnav Wadhwa

494 total citations
11 papers, 330 citations indexed

About

Arnav Wadhwa is a scholar working on Management Science and Operations Research, Economics and Econometrics and Electrical and Electronic Engineering. According to data from OpenAlex, Arnav Wadhwa has authored 11 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Management Science and Operations Research, 6 papers in Economics and Econometrics and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Arnav Wadhwa's work include Stock Market Forecasting Methods (6 papers), Energy Load and Power Forecasting (5 papers) and Complex Systems and Time Series Analysis (5 papers). Arnav Wadhwa is often cited by papers focused on Stock Market Forecasting Methods (6 papers), Energy Load and Power Forecasting (5 papers) and Complex Systems and Time Series Analysis (5 papers). Arnav Wadhwa collaborates with scholars based in India and United States. Arnav Wadhwa's co-authors include Ramit Sawhney, Rajiv Ratn Shah, Shivam Agarwal, Tyler Derr, Himanshu Sharma, Dhiraj Sangwan, Neeraj Kumar and Shivam Agarwal and has published in prestigious journals such as Journal of Cultural Heritage, IETE Journal of Research and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Arnav Wadhwa

11 papers receiving 323 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Arnav Wadhwa India	9	197	98	90	80	64	11	330
Khaled Al-Thelaya Qatar	9	164 0.8×	81 0.8×	96 1.1×	51 0.6×	45 0.7×	19	351
Akito Sakurai Japan	8	121 0.6×	68 0.7×	32 0.4×	73 0.9×	51 0.8×	35	304
Dadabada Pradeepkumar India	4	196 1.0×	102 1.0×	101 1.1×	94 1.2×	33 0.5×	6	317
Akhter Mohiuddin Rather India	6	335 1.7×	101 1.0×	173 1.9×	131 1.6×	103 1.6×	11	447
Haoyu Zhang China	4	256 1.3×	66 0.7×	136 1.5×	77 1.0×	100 1.6×	7	388
Bikash Sadhukhan India	10	135 0.7×	107 1.1×	63 0.7×	43 0.5×	30 0.5×	34	317
Salahadin Mohammed Saudi Arabia	7	170 0.9×	91 0.9×	99 1.1×	45 0.6×	43 0.7×	27	344
Zehong Yang China	5	138 0.7×	159 1.6×	102 1.1×	54 0.7×	38 0.6×	11	321
Qianggang Ding China	6	121 0.6×	69 0.7×	58 0.6×	40 0.5×	33 0.5×	7	234
Yingjun Chen China	4	235 1.2×	64 0.7×	92 1.0×	104 1.3×	72 1.1×	8	335

Countries citing papers authored by Arnav Wadhwa

Since Specialization

Citations

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

Fields of papers citing papers by Arnav Wadhwa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arnav Wadhwa

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Sawhney, Ramit, Arnav Wadhwa, Shivam Agarwal, & Rajiv Ratn Shah. (2021). FAST: Financial News and Tweet Based Time Aware Network for Stock Trading. 2164–2175. 25 indexed citations

2.

Sawhney, Ramit, et al.. (2021). Hyperbolic Online Time Stream Modeling. 40. 1682–1686. 7 indexed citations

3.

Sawhney, Ramit, Arnav Wadhwa, Shivam Agarwal, & Rajiv Ratn Shah. (2021). Quantitative Day Trading from Natural Language using Reinforcement Learning. 4018–4030. 9 indexed citations

4.

Sawhney, Ramit, Shivam Agarwal, Arnav Wadhwa, Tyler Derr, & Rajiv Ratn Shah. (2021). Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 35(1). 497–504. 84 indexed citations

5.

Sawhney, Ramit, et al.. (2021). TEC: A Time Evolving Contextual Graph Model for Speaker State Analysis in Political Debates. 3552–3558. 2 indexed citations

6.

Wadhwa, Arnav, et al.. (2021). Comparative Assessment of Regression Techniques for Wind Power Forecasting. IETE Journal of Research. 69(3). 1393–1402. 12 indexed citations

7.

Sawhney, Ramit, Shivam Agarwal, Arnav Wadhwa, & Rajiv Ratn Shah. (2021). Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. 11–22. 22 indexed citations

8.

Wadhwa, Arnav, et al.. (2021). An object detection approach for detecting damages in heritage sites using 3-D point clouds and 2-D visual data. Journal of Cultural Heritage. 48. 74–82. 41 indexed citations

9.

Sawhney, Ramit, Shivam Agarwal, Arnav Wadhwa, & Rajiv Ratn Shah. (2020). Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations. 8415–8426. 82 indexed citations

10.

Sawhney, Ramit, Arnav Wadhwa, Shivam Agarwal, & Rajiv Ratn Shah. (2020). GPolS: A Contextual Graph-Based Language Model for Analyzing Parliamentary Debates and Political Cohesion. 4847–4859. 9 indexed citations

11.

Sawhney, Ramit, Shivam Agarwal, Arnav Wadhwa, & Rajiv Ratn Shah. (2020). Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting. 482–491. 37 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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