Ananya Ganesh
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Information Systems
- Safety Research
- Co-authors
- Andrew McCallumEmma StrubellKatharina KannSidney K. D’MelloMartha PalmerKatherine E GoodmanSwapna SomasundaranWilliam R. Penuel
- Topics
- Topic Modeling (6 papers)Natural Language Processing Techniques (6 papers)Innovative Teaching and Learning Methods (2 papers)
- Journals
- Frontiers in Human Neurosciencenpj Digital MedicineMADOC (University of Mannheim)
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Ananya Ganesh
10 papers receiving 356 citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 149
- Electrical and Electronic Engineering 82
- Computer Vision and Pattern Recognition 45
- Information Systems 34
- Safety Research 29
Countries citing papers authored by Ananya Ganesh
This map shows the geographic impact of Ananya Ganesh'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 Ananya Ganesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ananya Ganesh more than expected).
Fields of papers citing papers by Ananya Ganesh
This network shows the impact of papers produced by Ananya Ganesh. 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 Ananya Ganesh. The network helps show where Ananya Ganesh may publish in the future.
Co-authorship network of co-authors of Ananya Ganesh
This figure shows the co-authorship network connecting the top 25 collaborators of Ananya Ganesh. A scholar is included among the top collaborators of Ananya Ganesh 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 Ananya Ganesh. Ananya Ganesh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 9 | |
| 3 | 4 | |
| 4 | 10 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 4 | |
| 8 | 5 | |
| 9 | 2 | |
| 10 | Training and domain adaptation for supervised text segmentation | 3 |
| 11 | Energy and Policy Considerations for Modern Deep Learning Researchbreakdown → | 323 |
About Ananya Ganesh
Ananya Ganesh is a scholar working on Artificial Intelligence, Computer Science Applications and Developmental and Educational Psychology, having authored 11 papers that have together received 366 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Innovative Teaching and Learning Methods (2 papers). The work is most often cited by research in Health Informatics (13 citations), Artificial Intelligence (149 citations) and Computer Science Applications (19 citations). Ananya Ganesh has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Andrew McCallum, Emma Strubell, Katharina Kann, Sidney K. D’Mello, Martha Palmer, Katherine E Goodman, Swapna Somasundaran, William R. Penuel, Nandakishore Kambhatla and Peter W. Foltz. Their work appears in journals such as Frontiers in Human Neuroscience, npj Digital Medicine and MADOC (University of Mannheim).
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.