Preethi Lahoti
Impact in
- Safety Research top 10%
- Ethics and Social Impacts of AI
Papers in
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- Ethics and Social Impacts of AI 4
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- Topic Modeling 4
- Explainable Artificial Intelligence (XAI) 2
- Adversarial Robustness in Machine Learning 2
- Text and Document Classification Technologies 1
- Co-authors
- Krishna P. Gummadi (4 shared papers)Gerhard Weikum (3 shared papers)Aristides Gionis (2 shared papers)Kiran V Garimella (1 shared paper)Gianmarco De Francisci Morales (1 shared paper)Lora M. Aroyo (1 shared paper)Kevin D. Robinson (1 shared paper)Qijun Tan (1 shared paper)
- Journals
- Machine Learning (1 paper)Proceedings of the VLDB Endowment (1 paper)ACM SIGIR Forum (1 paper)arXiv (Cornell University) (3 papers)Aaltodoc (Aalto University) (1 paper)
In The Last Decade
Preethi Lahoti
10 papers receiving 177 citations
Peers
Comparison fields: 5 of 48
- Safety Research 55
- Health Informatics 6
- Artificial Intelligence 112
- Computer Science Applications 12
- Statistical and Nonlinear Physics 24
Countries citing papers authored by Preethi Lahoti
This map shows the geographic impact of Preethi Lahoti'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 Preethi Lahoti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Preethi Lahoti more than expected).
Fields of papers citing papers by Preethi Lahoti
This network shows the impact of papers produced by Preethi Lahoti. 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 Preethi Lahoti. The network helps show where Preethi Lahoti may publish in the future.
Co-authors
The 15 scholars most cited alongside Preethi Lahoti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 57 | |
| 2 | 2019 | 36 | |
| 3 | 2018 | 34 | |
| 4 | 2019 | 13 | |
| 5 | 2023 | 12 | |
| 6 | 2017 | 12 | |
| 7 | 2023 | 9 | |
| 8 | 2021 | 8 | |
| 9 | 2022 | 8 | |
| 10 | 2017 | 3 |
About Preethi Lahoti
Preethi Lahoti is a scholar working on Safety Research, Artificial Intelligence, Cognitive Neuroscience, General Social Sciences and Computer Science Applications, having authored 10 papers that have together received 192 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (4 papers), Topic Modeling (4 papers), Psychology of Moral and Emotional Judgment (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Adversarial Robustness in Machine Learning (2 papers), Text and Document Classification Technologies (1 paper), Social Media and Politics (1 paper) and Computational and Text Analysis Methods (1 paper). The work is most often cited by research in Safety Research (55 citations), Health Informatics (6 citations), Artificial Intelligence (112 citations), Computer Science Applications (12 citations) and Statistical and Nonlinear Physics (24 citations). Preethi Lahoti has collaborated with scholars based in Germany, Finland and Ireland. Frequent co-authors include Krishna P. Gummadi, Gerhard Weikum, Aristides Gionis, Kiran V Garimella, Gianmarco De Francisci Morales, Lora M. Aroyo, Kevin D. Robinson, Qijun Tan, Hansa Srinivasan and Nicholas Blumm. Their work appears in journals such as Machine Learning, Proceedings of the VLDB Endowment, ACM SIGIR Forum, arXiv (Cornell University) and Aaltodoc (Aalto University).
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.