Petar M. Djurić
- Artificial Intelligence top 0.1%
- Target Tracking and Data Fusion in Sensor Networks 175
- Bayesian Methods and Mixture Models 47
- Gaussian Processes and Bayesian Inference 38
- Signal Processing top 0.2%
- Blind Source Separation Techniques 71
- Computer Networks and Communications top 0.5%
- Distributed Sensor Networks and Detection Algorithms 93
- Distributed Control Multi-Agent Systems 26
- Control and Systems Engineering top 0.5%
- Fault Detection and Control Systems 62
- Aerospace Engineering top 0.5%
-
- Indoor and Outdoor Localization Technologies 50
- Co-authors
- J.H. KotechaMónica F. BugalloMiodrag BolićJoaquı́n Mı́guezDavide DardariSteven KayTadesse GhirmaiFranz Hlawatsch
- Partner nations
- United StatesSpainItaly
In The Last Decade
Petar M. Djurić
409 papers receiving 9.2k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Artificial Intelligence 4.7k
- Signal Processing 1.4k
- Computer Networks and Communications 2.4k
- Control and Systems Engineering 1.6k
- Aerospace Engineering 1.6k
Countries citing papers authored by Petar M. Djurić
This map shows the geographic impact of Petar M. Djurić'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 Petar M. Djurić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Petar M. Djurić more than expected).
Fields of papers citing papers by Petar M. Djurić
This network shows the impact of papers produced by Petar M. Djurić. 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 Petar M. Djurić. The network helps show where Petar M. Djurić may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Petar M. Djurić, 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 | 2025 | 0 | |
| 2 | 2024 | 6 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 6 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 17 | |
| 10 | 2022 | 5 | |
| 11 | 2021 | 3 | |
| 12 | Consensus for continuous belief functions | 2014 | 2 |
| 13 | Sequential estimation of linear models in distributed settings | 2013 | 3 |
| 14 | Population Monte Carlo methodology a la Gibbs sampling | 2011 | 5 |
| 15 | Multiple marginalized population Monte Carlo | 2010 | 3 |
| 16 | Particle filtering and the inverse problem of biochemical networks | 2008 | 1 |
| 17 | 2007 | 323 | |
| 18 | Decision fusion for distributed target tracking using cost reference particle filtering | 2005 | 2 |
| 19 | Particle filteringbreakdown → | 2003 | 517 |
| 20 | Stochastic simulation and parameter estimation of enzyme reaction models | 2003 | 2 |
About Petar M. Djurić
Petar M. Djurić is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 447 papers that have together received 9.6k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (175 papers), Distributed Sensor Networks and Detection Algorithms (93 papers), Blind Source Separation Techniques (71 papers), Fault Detection and Control Systems (62 papers), Indoor and Outdoor Localization Technologies (50 papers), Bayesian Methods and Mixture Models (47 papers), Gaussian Processes and Bayesian Inference (38 papers) and Distributed Control Multi-Agent Systems (26 papers). The work is most often cited by research in Artificial Intelligence (4.7k citations), Signal Processing (1.4k citations) and Computer Networks and Communications (2.4k citations). Petar M. Djurić has collaborated with scholars based in United States, Spain and Italy. Frequent co-authors include J.H. Kotecha, Mónica F. Bugallo, Miodrag Bolić, Joaquı́n Mı́guez, Davide Dardari, Steven Kay, Tadesse Ghirmai, Franz Hlawatsch, Pau Closas and Tiancheng Li.
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.