Abhinav Jangda
- Software top 10%
- Software Testing and Debugging Techniques 4
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques 7
-
- Distributed systems and fault tolerance 2
- Network Security and Intrusion Detection 1
- Information Systems top 10%
- Software Engineering Research 2
-
- Security and Verification in Computing 4
-
- Advanced Neural Network Applications 4
-
- Advanced Malware Detection Techniques 2
- Co-authors
- Arjun GuhaUday BondhugulaYuriy BrunMarco SerafiniEmery D. BergerYangtian ZiCarolyn Jane AndersonMichael Greenberg
- Journals
- IEEE Transactions on Software Engineering (1 paper)ACM SIGPLAN Notices (1 paper)ACM Transactions on Programming Languages and Systems (1 paper)
- Partner nations
- United StatesIndiaBelgium
In The Last Decade
Abhinav Jangda
14 papers receiving 237 citations
Peers
Comparison fields: 5 of 33
- Software 35
- Hardware and Architecture 55
- Computational Mathematics 3
- Computer Networks and Communications 95
- Information Systems 87
Countries citing papers authored by Abhinav Jangda
This map shows the geographic impact of Abhinav Jangda'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 Abhinav Jangda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhinav Jangda more than expected).
Fields of papers citing papers by Abhinav Jangda
This network shows the impact of papers produced by Abhinav Jangda. 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 Abhinav Jangda. The network helps show where Abhinav Jangda may publish in the future.
Co-authorship network
The 19 scholars most cited alongside Abhinav Jangda, 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 | 2024 | 7 | |
| 2 | 2024 | 5 | |
| 3 | 2023 | 49 | |
| 4 | 2021 | 50 | |
| 5 | 2020 | 1 | |
| 6 | Mind the Gap: Analyzing the Performance of WebAssembly vs. Native Code. | 2019 | 3 |
| 7 | Not So Fast: Analyzing the Performance of WebAssembly vs. Native Code | 2019 | 15 |
| 8 | 2019 | 56 | |
| 9 | 2019 | 17 | |
| 10 | 2018 | 21 | |
| 11 | 2018 | 9 | |
| 12 | 2017 | 5 | |
| 13 | 2017 | 1 | |
| 14 | 2015 | 7 |
About Abhinav Jangda
Abhinav Jangda is a scholar working on Software, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 246 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (7 papers), Security and Verification in Computing (4 papers), Advanced Neural Network Applications (4 papers), Software Testing and Debugging Techniques (4 papers), Software Engineering Research (2 papers), Distributed systems and fault tolerance (2 papers), Advanced Malware Detection Techniques (2 papers) and Network Security and Intrusion Detection (1 paper). The work is most often cited by research in Software (35 citations), Hardware and Architecture (55 citations) and Computational Mathematics (3 citations). Abhinav Jangda has collaborated with scholars based in United States, India and Belgium. Frequent co-authors include Arjun Guha, Uday Bondhugula, Yuriy Brun, Marco Serafini, Emery D. Berger, Yangtian Zi, Carolyn Jane Anderson, Michael Greenberg, Ming‐Ho Yee and Sydney Nguyen. Their work appears in journals such as IEEE Transactions on Software Engineering, ACM SIGPLAN Notices and ACM Transactions on Programming Languages and Systems.
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.