Tejas Kulkarni
Impact in
-
- Mobile Crowdsensing and Crowdsourcing
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Topic Modeling
- Internet Traffic Analysis and Secure E-voting
- Natural Language Processing Techniques
- Reinforcement Learning in Robotics
Papers in
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- Privacy-Preserving Technologies in Data 7
- Cryptography and Data Security 4
- Stochastic Gradient Optimization Techniques 2
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- Distributed systems and fault tolerance 4
- Opportunistic and Delay-Tolerant Networks 2
- Peer-to-Peer Network Technologies 2
- Co-authors
- Graham Cormode (5 shared papers)Divesh Srivastava (5 shared papers)Karthik Narasimhan (1 shared paper)Regina Barzilay (1 shared paper)Somesh Jha (1 shared paper)Ninghui Li (1 shared paper)Tianhao Wang (1 shared paper)John Augustine (4 shared papers)
- Journals
- Internet Mathematics (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)IEEE Transactions on Components Packaging and Manufacturing Technology (1 paper)Proceedings of the VLDB Endowment (1 paper)Proceedings on Privacy Enhancing Technologies (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Tejas Kulkarni
17 papers receiving 451 citations
Peers
Comparison fields: 5 of 58
- Computer Science Applications 80
- Artificial Intelligence 395
- Transportation 22
- Computer Vision and Pattern Recognition 67
- Computer Networks and Communications 55
Countries citing papers authored by Tejas Kulkarni
This map shows the geographic impact of Tejas Kulkarni'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 Tejas Kulkarni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tejas Kulkarni more than expected).
Fields of papers citing papers by Tejas Kulkarni
This network shows the impact of papers produced by Tejas Kulkarni. 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 Tejas Kulkarni. The network helps show where Tejas Kulkarni may publish in the future.
Co-authors
The 25 scholars most cited alongside Tejas Kulkarni, 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 | 2015 | 137 | |
| 2 | 2018 | 130 | |
| 3 | 2018 | 86 | |
| 4 | 2019 | 65 | |
| 5 | Synthesizing Programs for Images using Reinforced Adversarial Learning. | 2018 | 10 |
| 6 | 2011 | 7 | |
| 7 | 2013 | 7 | |
| 8 | 2015 | 6 | |
| 9 | Differentially Private Bayesian Inference for Generalized Linear Models | 2021 | 4 |
| 10 | 2020 | 4 | |
| 11 | 2019 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2018 | 2 | |
| 14 | 2016 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2013 | 1 | |
| 18 | 2023 | 0 | |
| 19 | 2025 | 0 |
About Tejas Kulkarni
Tejas Kulkarni is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Computer Science Applications and Cognitive Neuroscience, having authored 19 papers that have together received 470 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (7 papers), Cryptography and Data Security (4 papers), Distributed systems and fault tolerance (4 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Digital Media Forensic Detection (2 papers), Opportunistic and Delay-Tolerant Networks (2 papers), Peer-to-Peer Network Technologies (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). The work is most often cited by research in Computer Science Applications (80 citations), Artificial Intelligence (395 citations), Transportation (22 citations), Computer Vision and Pattern Recognition (67 citations) and Computer Networks and Communications (55 citations). Tejas Kulkarni has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Graham Cormode, Divesh Srivastava, Karthik Narasimhan, Regina Barzilay, Somesh Jha, Ninghui Li, Tianhao Wang, John Augustine, Niklas Elmqvist and Oriol Vinyals. Their work appears in journals such as Internet Mathematics, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Components Packaging and Manufacturing Technology, Proceedings of the VLDB Endowment and Proceedings on Privacy Enhancing Technologies.
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.