Osbert Bastani

2.8k citations
48 papers · 668 · h-index 16

Impact in

Papers in

    • Reinforcement Learning in Robotics 9
    • Adversarial Robustness in Machine Learning 8
    • Explainable Artificial Intelligence (XAI) 7
    • Topic Modeling 7
    • Software Engineering Research 12

Osbert Bastani

47 papers receiving 653 citations

Peers

Osbert Bastani
Comparison fields: 5 of 74
  • Software 208
  • Health Informatics 29
  • Signal Processing 136
  • Artificial Intelligence 329
  • Information Systems 183
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Hammond Pearce United States
Amin Nikanjam Canada
Mengshi Zhang United States
Gunel Jahangirova Switzerland
Rudolf Ramler Austria
Sebastian Sardiña Australia
Xiaoyuan Xie China
Kaidi Xu United States
Guangdong Bai Australia
Haiyan Zhao China
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Citations per field
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Citations per year

Countries citing papers authored by Osbert Bastani

Since Specialization
Citations

This map shows the geographic impact of Osbert Bastani'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 Osbert Bastani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Osbert Bastani more than expected).

Fields of papers citing papers by Osbert Bastani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Osbert Bastani. 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 Osbert Bastani. The network helps show where Osbert Bastani may publish in the future.

Co-authors

The 25 scholars most cited alongside Osbert Bastani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Osbert Bastani Line = papers co-authored together Osbert Bastani links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020105
2 201856
3 201753
4 202038
5 201930
6 201630
7 201729
8 201426
9 201824
10
Verifiable Reinforcement Learning via Policy Extraction
201822
11 202421
12 202121
13 201918
14 202116
15 202116
16 202115
17 201814
18 202412
19 201911
20 202110

About Osbert Bastani

Osbert Bastani is a scholar working on Artificial Intelligence, Information Systems, Software, Signal Processing and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 668 indexed citations. Recurring topics across this work include Software Engineering Research (12 papers), Software Testing and Debugging Techniques (11 papers), Reinforcement Learning in Robotics (9 papers), Adversarial Robustness in Machine Learning (8 papers), Advanced Malware Detection Techniques (7 papers), Explainable Artificial Intelligence (XAI) (7 papers), Topic Modeling (7 papers) and Software Reliability and Analysis Research (4 papers). The work is most often cited by research in Software (208 citations), Health Informatics (29 citations), Signal Processing (136 citations), Artificial Intelligence (329 citations) and Information Systems (183 citations). Osbert Bastani has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Himabindu Lakkaraju, Işıl Dillig, Alex Aiken, Saswat Anand, Yu Feng, Ruben Martins, Shuo Li, Armando Solar-Lezama, Rahul Sharma and Percy Liang. Their work appears in journals such as Proceedings of the ACM on Programming Languages, ACM SIGPLAN Notices, Management Science, ACM Transactions on Embedded Computing Systems and Theory and applications of categories.

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.

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