Payal Chandak

2.2k total citations · 2 hit papers
7 papers, 320 citations indexed

About

Payal Chandak is a scholar working on Toxicology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Payal Chandak has authored 7 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Toxicology, 2 papers in Artificial Intelligence and 2 papers in Computational Theory and Mathematics. Recurrent topics in Payal Chandak's work include Pharmacovigilance and Adverse Drug Reactions (3 papers), Academic integrity and plagiarism (2 papers) and Computational Drug Discovery Methods (2 papers). Payal Chandak is often cited by papers focused on Pharmacovigilance and Adverse Drug Reactions (3 papers), Academic integrity and plagiarism (2 papers) and Computational Drug Discovery Methods (2 papers). Payal Chandak collaborates with scholars based in United States, Canada and China. Payal Chandak's co-authors include Marinka Žitnik, Kexin Huang, Qianwen Wang, Nils Gehlenborg, Nicholas P. Tatonetti, Akhil Vaid, Jure Leskovec, Girish N. Nadkarni, Benjamin S. Glicksberg and Haishuai Wang and has published in prestigious journals such as Nature Medicine, Advanced Science and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Payal Chandak

6 papers receiving 312 citations

Hit Papers

align trajectories sort by overperformance

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.

Building a knowledge graph to enable precision medicine

2023 164 citations Payal Chandak, Kexin Huang et al. Scientific Data profile →
A foundation model for clinician-centered drug repurposing

2024 72 citations Kexin Huang, Payal Chandak et al. Nature Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Payal Chandak United States	5	155	128	96	19	18	7	320
Sameh K. Mohamed Ireland	8	254 1.6×	135 1.1×	170 1.8×	9 0.5×	7 0.4×	16	379
Yassine Mrabet United States	10	126 0.8×	232 1.8×	31 0.3×	10 0.5×	16 0.9×	19	319
Abhyuday Jagannatha United States	7	179 1.2×	270 2.1×	30 0.3×	49 2.6×	11 0.6×	8	373
Kai Hakala Finland	11	257 1.7×	237 1.9×	20 0.2×	9 0.5×	12 0.7×	19	377
Eithon Cadag United States	7	406 2.6×	376 2.9×	30 0.3×	52 2.7×	12 0.7×	12	563
Christine Hessler United States	5	243 1.6×	74 0.6×	145 1.5×	8 0.4×	4 0.2×	5	389
Liang‐Chin Huang United States	11	202 1.3×	58 0.5×	161 1.7×	10 0.5×	24 1.3×	20	381
Youngmi Yoon South Korea	11	271 1.7×	39 0.3×	147 1.5×	7 0.4×	2 0.1×	52	387
Soheil Moosavinasab United States	8	225 1.5×	98 0.8×	118 1.2×	15 0.8×	2 0.1×	16	359
Julian Matschinske Germany	7	60 0.4×	109 0.9×	48 0.5×	15 0.8×	28 1.6×	11	247

Countries citing papers authored by Payal Chandak

Since Specialization

Citations

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

Fields of papers citing papers by Payal Chandak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Payal Chandak

This figure shows the co-authorship network connecting the top 25 collaborators of Payal Chandak. A scholar is included among the top collaborators of Payal Chandak 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 Payal Chandak. Payal Chandak 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:

7 of 7 papers shown

1.

Gao, Yang, Xiang Zhang, Zhongquan Sun, et al.. (2024). Precision Adverse Drug Reactions Prediction with Heterogeneous Graph Neural Network. Advanced Science. 12(4). e2404671–e2404671. 6 indexed citations

2.

Huang, Kexin, Payal Chandak, Qianwen Wang, et al.. (2024). A foundation model for clinician-centered drug repurposing. Nature Medicine. 30(12). 3601–3613. 72 indexed citations breakdown →

3.

Chandak, Payal, Kexin Huang, & Marinka Žitnik. (2023). Building a knowledge graph to enable precision medicine. Scientific Data. 10(1). 67–67. 164 indexed citations breakdown →

4.

Zhang, Xiang, Yihe Wang, Payal Chandak, & Zihuai He. (2023). Deep Learning for EEG‐Based Alzheimer’s Disease Diagnosis. Alzheimer s & Dementia. 19(S15).

5.

Wang, Qianwen, Kexin Huang, Payal Chandak, Marinka Žitnik, & Nils Gehlenborg. (2022). Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing. IEEE Transactions on Visualization and Computer Graphics. 29(1). 1266–1276. 47 indexed citations

6.

Chandak, Payal & Nicholas P. Tatonetti. (2020). Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women. Patterns. 1(7). 100108–100108. 30 indexed citations

7.

Chandak, Payal & Nicholas P. Tatonetti. (2020). AwareDX: Using Machine Learning to Identify Drugs Posing Increased Risk of Adverse Reactions to Women. SSRN Electronic Journal. 1 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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