Prateek Jain
- Computational Mechanics top 10%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Automotive Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Purushottam KarTrapti JainAnimashree AnandkumarPraneeth NetrapalliSujay SanghaviIoannis MitliagkasConstantine CaramanisInderjit S. Dhillon
- Topics
- Sparse and Compressive Sensing Techniques (7 papers)Advanced Battery Technologies Research (7 papers)Electric Vehicles and Infrastructure (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Signal Processing MagazineSustainable Cities and Society
- Partner nations
- IndiaUnited StatesOman
In The Last Decade
Prateek Jain
27 papers receiving 378 citations
Peers
Comparison fields: 5 of 80
- Computational Mechanics 142
- Electrical and Electronic Engineering 131
- Artificial Intelligence 90
- Automotive Engineering 82
- Computer Vision and Pattern Recognition 74
Countries citing papers authored by Prateek Jain
This map shows the geographic impact of Prateek Jain'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 Prateek Jain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prateek Jain more than expected).
Fields of papers citing papers by Prateek Jain
This network shows the impact of papers produced by Prateek Jain. 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 Prateek Jain. The network helps show where Prateek Jain may publish in the future.
Co-authorship network of co-authors of Prateek Jain
This figure shows the co-authorship network connecting the top 25 collaborators of Prateek Jain. A scholar is included among the top collaborators of Prateek Jain 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 Prateek Jain. Prateek Jain is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems | 1 |
| 6 | A Topic-Aligned Multilingual Corpus of Wikipedia Articles for Studying Information Asymmetry in Low Resource Languages. | 5 |
| 7 | 3 | |
| 8 | Efficient Algorithms for Smooth Minimax Optimization | 7 |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 11 | |
| 13 | Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations | 16 |
| 14 | 7 | |
| 15 | 3 | |
| 16 | A study on Optimization of Flow through Venturi of a Carburettor. | 3 |
| 17 | 25 | |
| 18 | 6 | |
| 19 | 31 | |
| 20 | Matrix Completion from Power-Law Distributed Samples | 27 |
About Prateek Jain
Prateek Jain is a scholar working on Computational Mathematics, Automotive Engineering and Metals and Alloys, having authored 30 papers that have together received 397 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (7 papers), Advanced Battery Technologies Research (7 papers) and Electric Vehicles and Infrastructure (6 papers). The work is most often cited by research in Computational Mathematics (21 citations), Computational Mechanics (142 citations) and Automotive Engineering (82 citations). Prateek Jain has collaborated with scholars based in India, United States and Oman. Frequent co-authors include Purushottam Kar, Trapti Jain, Animashree Anandkumar, Praneeth Netrapalli, Sujay Sanghavi, Ioannis Mitliagkas, Constantine Caramanis, Inderjit S. Dhillon, Raghu Meka and Dwaipayan Roy. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Signal Processing Magazine and Sustainable Cities and Society.
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.