Muhammad Ali Gulzar
- Computer Networks and Communications top 5%
- Information Systems top 2%
- Artificial Intelligence top 5%
- Information Systems and Management top 2%
- Software top 5%
- Co-authors
- Miryung KimMatteo InterlandiTyson CondieTodd MillsteinSai Deep TetaliSeunghyun YooKshitij ShahQuanquan Gu
- Topics
- Software System Performance and Reliability (16 papers)Scientific Computing and Data Management (16 papers)Software Testing and Debugging Techniques (15 papers)
- Journals
- Journal of the Association for Information SystemsProceedings of the VLDB EndowmentThe VLDB Journal
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Muhammad Ali Gulzar
38 papers receiving 553 citations
Peers
Comparison fields: 5 of 41
- Computer Networks and Communications 316
- Information Systems 288
- Artificial Intelligence 211
- Information Systems and Management 203
- Software 149
Countries citing papers authored by Muhammad Ali Gulzar
This map shows the geographic impact of Muhammad Ali Gulzar'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 Muhammad Ali Gulzar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Ali Gulzar more than expected).
Fields of papers citing papers by Muhammad Ali Gulzar
This network shows the impact of papers produced by Muhammad Ali Gulzar. 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 Muhammad Ali Gulzar. The network helps show where Muhammad Ali Gulzar may publish in the future.
Co-authorship network of co-authors of Muhammad Ali Gulzar
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Ali Gulzar. A scholar is included among the top collaborators of Muhammad Ali Gulzar 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 Muhammad Ali Gulzar. Muhammad Ali Gulzar 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 | 0 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | 5 | |
| 14 | 23 | |
| 15 | 6 | |
| 16 | 22 | |
| 17 | 18 | |
| 18 | Interactive debugging for big data analytics | 5 |
| 19 | A Classification Based Framework to Predict Viral Threads | 1 |
| 20 | Titian: Data Provenance Support in Spark. | 70 |
About Muhammad Ali Gulzar
Muhammad Ali Gulzar is a scholar working on Software, Information Systems and Management and Information Systems, having authored 43 papers that have together received 576 indexed citations. Recurring topics across this work include Software System Performance and Reliability (16 papers), Scientific Computing and Data Management (16 papers) and Software Testing and Debugging Techniques (15 papers). The work is most often cited by research in Software (149 citations), Information Systems and Management (203 citations) and Computer Networks and Communications (316 citations). Muhammad Ali Gulzar has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Miryung Kim, Matteo Interlandi, Tyson Condie, Todd Millstein, Sai Deep Tetali, Seunghyun Yoo, Kshitij Shah, Quanquan Gu, Lingxiao Wang and Madanlal Musuvathi. Their work appears in journals such as Journal of the Association for Information Systems, Proceedings of the VLDB Endowment and The VLDB Journal.
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.