Roberto Chiosa

414 total citations · 1 hit paper
7 papers, 262 citations indexed

About

Roberto Chiosa is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Civil and Structural Engineering. According to data from OpenAlex, Roberto Chiosa has authored 7 papers receiving a total of 262 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Electrical and Electronic Engineering and 2 papers in Civil and Structural Engineering. Recurrent topics in Roberto Chiosa's work include Anomaly Detection Techniques and Applications (4 papers), Building Energy and Comfort Optimization (2 papers) and Infrastructure Maintenance and Monitoring (2 papers). Roberto Chiosa is often cited by papers focused on Anomaly Detection Techniques and Applications (4 papers), Building Energy and Comfort Optimization (2 papers) and Infrastructure Maintenance and Monitoring (2 papers). Roberto Chiosa collaborates with scholars based in Italy, China and United States. Roberto Chiosa's co-authors include Marco Savino Piscitelli, Alfonso Capozzoli, Cheng Fan, Yongjun Sun, Marco Pritoni, Yimin Chen, Xing Lu, Jin Wen, Seungjae Lee and Zheng O’Neill and has published in prestigious journals such as Applied Energy, Energy and Energy and Buildings.

In The Last Decade

Roberto Chiosa

7 papers receiving 256 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review of data-driven fault detection and diagnostics for building HVAC systems

2023 149 citations Zhelun Chen, Zheng O’Neill et al. Applied Energy profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Roberto Chiosa Italy	5	123	79	77	56	40	7	262
Zhelun Chen United States	9	163 1.3×	87 1.1×	96 1.2×	52 0.9×	43 1.1×	19	329
Jaewon Jeoung South Korea	9	132 1.1×	66 0.8×	116 1.5×	32 0.6×	46 1.1×	18	330
Yimin Chen United States	9	157 1.3×	140 1.8×	85 1.1×	62 1.1×	40 1.0×	30	345
Ojas Pradhan United States	7	106 0.9×	101 1.3×	51 0.7×	53 0.9×	25 0.6×	12	251
Biao Sun China	8	214 1.7×	114 1.4×	188 2.4×	31 0.6×	52 1.3×	15	377
Zehan Tan China	4	211 1.7×	50 0.6×	205 2.7×	53 0.9×	64 1.6×	9	375
Zhenxin Zhou China	10	210 1.7×	126 1.6×	131 1.7×	67 1.2×	39 1.0×	11	386
Baihong Jin United States	9	64 0.5×	52 0.7×	99 1.3×	45 0.8×	20 0.5×	17	250
Radiša Jovanović Serbia	7	187 1.5×	52 0.7×	186 2.4×	58 1.0×	98 2.5×	33	362
Denchai Woradechjumroen Thailand	6	248 2.0×	99 1.3×	63 0.8×	34 0.6×	60 1.5×	14	376

Countries citing papers authored by Roberto Chiosa

Since Specialization

Citations

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

Fields of papers citing papers by Roberto Chiosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roberto Chiosa

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Chiosa. A scholar is included among the top collaborators of Roberto Chiosa 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 Roberto Chiosa. Roberto Chiosa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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7 of 7 papers shown

1.

Chiosa, Roberto, Marco Savino Piscitelli, Marco Pritoni, & Alfonso Capozzoli. (2024). A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema. Energy and Buildings. 323. 114802–114802. 1 indexed citations

2.

Capozzoli, Alfonso, et al.. (2024). Investigation of ground movements induced by underground gas storages via unsupervised ML methodology applied to InSAR data. Gas Science and Engineering. 125. 205293–205293. 3 indexed citations

3.

Chen, Zhelun, Zheng O’Neill, Jin Wen, et al.. (2023). A review of data-driven fault detection and diagnostics for building HVAC systems. Applied Energy. 339. 121030–121030. 149 indexed citations breakdown →

4.

Fan, Cheng, Marco Savino Piscitelli, Roberto Chiosa, et al.. (2023). Leveraging graph convolutional networks for semi-supervised fault diagnosis of HVAC systems in data-scarce contexts. Building Simulation. 16(8). 1499–1517. 23 indexed citations

5.

Chiosa, Roberto, Marco Savino Piscitelli, Cheng Fan, & Alfonso Capozzoli. (2022). Towards a self-tuned data analytics-based process for an automatic context-aware detection and diagnosis of anomalies in building energy consumption timeseries. Energy and Buildings. 270. 112302–112302. 17 indexed citations

6.

Chiosa, Roberto, Marco Savino Piscitelli, & Alfonso Capozzoli. (2021). A Data Analytics-Based Energy Information System (EIS) Tool to Perform Meter-Level Anomaly Detection and Diagnosis in Buildings. Energies. 14(1). 237–237. 24 indexed citations

7.

Fan, Cheng, et al.. (2021). Data-centric or algorithm-centric: Exploiting the performance of transfer learning for improving building energy predictions in data-scarce context. Energy. 240. 122775–122775. 45 indexed citations

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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