Cesare Alippi

10.2k citations
231 papers · 6.5k indexed · 5 hit papers · h-index 43

Impact in

Papers in

Cesare Alippi

221 papers receiving 6.2k citations

Hit Papers

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection 2024 · 139 citations
1392015202620182022100200300400500

Peers

Cesare Alippi
Comparison fields: 5 of 170
  • Artificial Intelligence 2.9k
  • Computer Networks and Communications 1.4k
  • Signal Processing 488
  • Control and Systems Engineering 995
  • Hardware and Architecture 278
Replace L.M. Patnaik with:
L.M. Patnaik India
Bo Yang China
Caro Lucas Iran
Victor O. K. Li Hong Kong
Christian Blum Spain
Zhihua Cui China
Jian Shen China
Emil M. Petriu Canada
S. S. Iyengar United States
M. R. Mosavi Iran
Cesare Alippi relative to L.M. Patnaik India L.M. Patnaik's profile →
Citations per field
00.5×
L.M. Patnaik · 1×
Citations per year

Countries citing papers authored by Cesare Alippi

Since Specialization
Citations

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

Fields of papers citing papers by Cesare Alippi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Cesare Alippi, 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 Cesare Alippi Line = papers co-authored together Cesare Alippi links everyone, so they are left out of the graph.

All Works

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About Cesare Alippi

Cesare Alippi is a scholar working on Artificial Intelligence, Hardware and Architecture, Control and Systems Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 231 papers that have together received 6.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (42 papers), Fault Detection and Control Systems (31 papers), Anomaly Detection Techniques and Applications (28 papers), Data Stream Mining Techniques (28 papers), Energy Efficient Wireless Sensor Networks (24 papers), Control Systems and Identification (13 papers), Energy Harvesting in Wireless Networks (12 papers) and Advanced Memory and Neural Computing (12 papers). The work is most often cited by research in Artificial Intelligence (2.9k citations), Computer Networks and Communications (1.4k citations), Signal Processing (488 citations), Control and Systems Engineering (995 citations) and Hardware and Architecture (278 citations). Cesare Alippi has collaborated with scholars based in Italy, Switzerland and United Kingdom. Frequent co-authors include Manuel Roveri, C. Galperti, Giacomo Boracchi, Vincenzo Piuri, Daniele Grattarola, Lorenzo Livi, Filippo Maria Bianchi, Gregory Ditzler, Robi Polikar and Derong Liu. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Fuzzy Systems, Neurocomputing and IEEE Computational Intelligence Magazine.

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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