Praneeth Vepakomma
Impact in
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- Context-Aware Activity Recognition Systems
- Human Pose and Action Recognition
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data
- Anomaly Detection Techniques and Applications
- Cryptography and Data Security
Papers in
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- Privacy-Preserving Technologies in Data 7
- Stochastic Gradient Optimization Techniques 3
- Machine Learning and Algorithms 2
- Cryptography and Data Security 2
- Adversarial Robustness in Machine Learning 2
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- Face and Expression Recognition 2
- Face recognition and analysis 2
- Co-authors
- Debraj De (1 shared paper)Shekhar Bhansali (1 shared paper)Sajal K. Das (1 shared paper)Anupam Shukla (1 shared paper)Prashant Shrivastava (1 shared paper)Ramesh Raskar (9 shared papers)Jihong Park (3 shared papers)Mehdi Bennis (3 shared papers)
- Journals
- IEEE Transactions on Big Data (1 paper)Computer Methods and Programs in Biomedicine (1 paper)Applied and Computational Harmonic Analysis (1 paper)Discrete Applied Mathematics (1 paper)2021 IEEE Global Communications Conference (GLOBECOM) (1 paper)
- Partner nations
- United StatesAustraliaFinland
In The Last Decade
Praneeth Vepakomma
11 papers receiving 242 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 115
- Artificial Intelligence 133
- Health Information Management 14
- Health Informatics 3
- Computer Networks and Communications 40
Countries citing papers authored by Praneeth Vepakomma
This map shows the geographic impact of Praneeth Vepakomma'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 Praneeth Vepakomma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Praneeth Vepakomma more than expected).
Fields of papers citing papers by Praneeth Vepakomma
This network shows the impact of papers produced by Praneeth Vepakomma. 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 Praneeth Vepakomma. The network helps show where Praneeth Vepakomma may publish in the future.
Co-authors
The 24 scholars most cited alongside Praneeth Vepakomma, 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 | 102 | |
| 2 | 2016 | 67 | |
| 3 | 2022 | 31 | |
| 4 | Assessing Disease Exposure Risk With Location Histories And Protecting Privacy: A Cryptographic Approach In Response To A Global Pandemic | 2020 | 16 |
| 5 | 2015 | 10 | |
| 6 | 2018 | 9 | |
| 7 | 2021 | 5 | |
| 8 | 2022 | 4 | |
| 9 | 2021 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2022 | 1 | |
| 12 | 2025 | 0 | |
| 13 | 2019 | 0 | |
| 14 | 2024 | 0 |
About Praneeth Vepakomma
Praneeth Vepakomma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Neurology, having authored 14 papers that have together received 250 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (7 papers), Stochastic Gradient Optimization Techniques (3 papers), Face and Expression Recognition (2 papers), Face recognition and analysis (2 papers), Machine Learning and Algorithms (2 papers), Cryptography and Data Security (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Analog and Mixed-Signal Circuit Design (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (115 citations), Artificial Intelligence (133 citations), Health Information Management (14 citations), Health Informatics (3 citations) and Computer Networks and Communications (40 citations). Praneeth Vepakomma has collaborated with scholars based in United States, Australia and Finland. Frequent co-authors include Debraj De, Shekhar Bhansali, Sajal K. Das, Anupam Shukla, Prashant Shrivastava, Ramesh Raskar, Jihong Park, Mehdi Bennis, Seong‐Lyun Kim and Ahmed Elgammal. Their work appears in journals such as IEEE Transactions on Big Data, Computer Methods and Programs in Biomedicine, Applied and Computational Harmonic Analysis, Discrete Applied Mathematics and 2021 IEEE Global Communications Conference (GLOBECOM).
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.