Baishakhi Ray
- Information Systems top 0.2%
- Artificial Intelligence top 0.5%
- Software top 0.2%
- Computer Networks and Communications top 2%
- Signal Processing top 1%
- Co-authors
- Suman JanaKexin PeiYuchi TianPrémkumar DévanbuSaikat ChakrabortyVladimir FilkovMiryung KimDaryl Posnett
- Topics
- Software Engineering Research (49 papers)Software Testing and Debugging Techniques (35 papers)Advanced Malware Detection Techniques (19 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Baishakhi Ray
72 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Information Systems 1.9k
- Artificial Intelligence 1.4k
- Software 1.4k
- Computer Networks and Communications 776
- Signal Processing 742
Countries citing papers authored by Baishakhi Ray
This map shows the geographic impact of Baishakhi Ray'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 Baishakhi Ray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baishakhi Ray more than expected).
Fields of papers citing papers by Baishakhi Ray
This network shows the impact of papers produced by Baishakhi Ray. 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 Baishakhi Ray. The network helps show where Baishakhi Ray may publish in the future.
Co-authorship network of co-authors of Baishakhi Ray
This figure shows the co-authorship network connecting the top 25 collaborators of Baishakhi Ray. A scholar is included among the top collaborators of Baishakhi Ray 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 Baishakhi Ray. Baishakhi Ray 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 | 1 | |
| 3 | 11 | |
| 4 | 0 | |
| 5 | 14 | |
| 6 | 6 | |
| 7 | 22 | |
| 8 | 5 | |
| 9 | 19 | |
| 10 | Unrestricted Adversarial Attacks For Semantic Segmentation | 1 |
| 11 | Testing Deep Neural Network based Image Classifiers. | 3 |
| 12 | NEUZZ: Efficient Fuzzing with Neural Program Learning | 15 |
| 13 | Poster: A Recommender System for Developer Onboarding | 2 |
| 14 | DeepTest: Automated Testing of Deep-Neural-Network-Driven Autonomous Cars | 2 |
| 15 | Tree2Tree Neural Translation Model for Learning Source Code Changes. | 11 |
| 16 | 20 | |
| 17 | Automatically Detecting Error Handling Bugs Using Error Specifications | 28 |
| 18 | 160 | |
| 19 | 29 | |
| 20 | 226 |
About Baishakhi Ray
Baishakhi Ray is a scholar working on Software, Information Systems and Signal Processing, having authored 81 papers that have together received 3.6k indexed citations. Recurring topics across this work include Software Engineering Research (49 papers), Software Testing and Debugging Techniques (35 papers) and Advanced Malware Detection Techniques (19 papers). The work is most often cited by research in Software (1.4k citations), Information Systems (1.9k citations) and Signal Processing (742 citations). Baishakhi Ray has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Suman Jana, Kexin Pei, Yuchi Tian, Prémkumar Dévanbu, Saikat Chakraborty, Vladimir Filkov, Miryung Kim, Daryl Posnett, Kai-Wei Chang and Wasi Uddin Ahmad. Their work appears in journals such as Communications of the ACM, IEEE Access and IEEE Transactions on Software Engineering.
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.