Giuseppe Pinto

986 total citations · 1 hit paper
19 papers, 611 citations indexed

About

Giuseppe Pinto is a scholar working on Building and Construction, Electrical and Electronic Engineering and Environmental Engineering. According to data from OpenAlex, Giuseppe Pinto has authored 19 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Building and Construction, 11 papers in Electrical and Electronic Engineering and 4 papers in Environmental Engineering. Recurrent topics in Giuseppe Pinto's work include Building Energy and Comfort Optimization (11 papers), Smart Grid Energy Management (7 papers) and Integrated Energy Systems Optimization (4 papers). Giuseppe Pinto is often cited by papers focused on Building Energy and Comfort Optimization (11 papers), Smart Grid Energy Management (7 papers) and Integrated Energy Systems Optimization (4 papers). Giuseppe Pinto collaborates with scholars based in Italy, United States and Canada. Giuseppe Pinto's co-authors include Alfonso Capozzoli, Tianzhen Hong, Zhe Wang, Abhishek Roy, Marco Savino Piscitelli, Zoltán Nagy, José R. Vázquez-Canteli, A. Villone, F. Nanna and Giacobbe Braccio and has published in prestigious journals such as Applied Energy, Energy and Energy and Buildings.

In The Last Decade

Giuseppe Pinto

18 papers receiving 587 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.

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

2022 193 citations Giuseppe Pinto, Zhe Wang et al. Advances in Applied Energy profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Giuseppe Pinto Italy	10	310	264	98	93	86	19	611
Zherui Ma China	13	425 1.4×	98 0.4×	85 0.9×	81 0.9×	70 0.8×	29	659
William Livingood United States	5	279 0.9×	281 1.1×	31 0.3×	65 0.7×	119 1.4×	5	502
Mario Sisinni Italy	7	141 0.5×	165 0.6×	35 0.4×	77 0.8×	67 0.8×	11	519
Timo Laukkanen Finland	16	169 0.5×	92 0.3×	118 1.2×	187 2.0×	143 1.7×	57	721
Yanfeng Gong China	16	292 0.9×	66 0.3×	205 2.1×	71 0.8×	58 0.7×	71	833
Julien Eynard France	14	320 1.0×	254 1.0×	192 2.0×	152 1.6×	91 1.1×	41	624
Hamid Shakibi Iran	15	220 0.7×	124 0.5×	31 0.3×	296 3.2×	49 0.6×	20	821
Emrah Bıyık Türkiye	16	354 1.1×	422 1.6×	225 2.3×	383 4.1×	196 2.3×	35	1.2k
Tobias Massier Germany	12	625 2.0×	81 0.3×	151 1.5×	74 0.8×	102 1.2×	54	830
Matteo Manganelli Italy	13	389 1.3×	130 0.5×	182 1.9×	101 1.1×	21 0.2×	50	575

Countries citing papers authored by Giuseppe Pinto

Since Specialization

Citations

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

Fields of papers citing papers by Giuseppe Pinto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giuseppe Pinto

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Nweye, Kingsley, Alfonso Capozzoli, Zoltán Nagy, et al.. (2024). Effects of occupant thermostat preferences and override behavior on residential demand response in CityLearn. Energy and Buildings. 324. 114830–114830. 9 indexed citations

Nweye, Kingsley, Giuseppe Pinto, Han Li, et al.. (2023). CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities. 274–275. 4 indexed citations

Nweye, Kingsley, Giuseppe Pinto, Han Li, et al.. (2023). A framework for the design of representative neighborhoods for energy flexibility assessment in CityLearn. Building Simulation Conference proceedings. 18. 5 indexed citations

Li, Han, Giuseppe Pinto, Marco Savino Piscitelli, Alfonso Capozzoli, & Tianzhen Hong. (2023). Building thermal dynamics modeling with deep transfer learning using a large residential smart thermostat dataset. Engineering Applications of Artificial Intelligence. 130. 107701–107701. 17 indexed citations

Zoli, Matteo, et al.. (2022). Shadows and Lights: Perspectives of Training and Education in Neurosurgery for Undergraduate Students. Frontiers in Surgery. 9. 882063–882063. 8 indexed citations

Pinto, Giuseppe, Anjukan Kathirgamanathan, Eleni Mangina, Donal Finn, & Alfonso Capozzoli. (2022). Enhancing energy management in grid-interactive buildings: A comparison among cooperative and coordinated architectures. Applied Energy. 310. 118497–118497. 34 indexed citations

Pinto, Giuseppe, Zhe Wang, Abhishek Roy, Tianzhen Hong, & Alfonso Capozzoli. (2022). Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives. Advances in Applied Energy. 5. 100084–100084. 193 indexed citations breakdown →

Pinto, Giuseppe, et al.. (2022). Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics. Energy and Buildings. 276. 112530–112530. 27 indexed citations

Li, Han, Giuseppe Pinto, Alfonso Capozzoli, & Tianzhen Hong. (2022). Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset. 242–245.

10.

Pinto, Giuseppe, et al.. (2021). Application of a Stochastic Multicriteria Acceptability Analysis to support decision-making within a macro-scale energy model: Case study of the electrification of the road European transport sector. Energy. 236. 121444–121444. 9 indexed citations

11.

Pinto, Giuseppe, et al.. (2021). Data-driven district energy management with surrogate models and deep reinforcement learning. Applied Energy. 304. 117642–117642. 92 indexed citations

12.

Pinto, Giuseppe, et al.. (2021). Exploring the Potentialities of Deep Reinforcement Learning for Incentive-Based Demand Response in a Cluster of Small Commercial Buildings. Energies. 14(10). 2933–2933. 27 indexed citations

13.

Pinto, Giuseppe, Marco Savino Piscitelli, José R. Vázquez-Canteli, Zoltán Nagy, & Alfonso Capozzoli. (2021). Coordinated energy management for a cluster of buildings through deep reinforcement learning. Energy. 229. 120725–120725. 69 indexed citations

14.

Pinto, Giuseppe, Elnaz Abdollahi, Alfonso Capozzoli, Laura Savoldi, & Risto Lahdelma. (2019). Optimization and Multicriteria Evaluation of Carbon-neutral Technologies for District Heating. Energies. 12(9). 1653–1653. 13 indexed citations

15.

Pinto, Giuseppe, et al.. (2018). Small scale Organic Rankine Cycle testing for low grade heat recovery by using refrigerants as working fluids. ENEA Open Archive (National Agency for New Technologies, Energy and Sustainable Economic Development). 79(3). 70–78. 2 indexed citations

16.

Pinto, Giuseppe, et al.. (2018). Parameters identification for scroll expander semi-empirical model by using genetic algorithm. Energy Procedia. 148. 736–743. 1 indexed citations

17.

Barisano, D., F. Nanna, Giuseppe Pinto, et al.. (2015). Steam/oxygen biomass gasification at pilot scale in an internally circulating bubbling fluidized bed reactor. Fuel Processing Technology. 141. 74–81. 93 indexed citations

18.

Barisano, D., et al.. (2014). Production of Gaseous Carriers Via Biomass Gasification for Energy Purposes. Energy Procedia. 45. 2–11. 7 indexed citations

19.

Freda, Cesare, F. Nanna, Giacobbe Braccio, et al.. (2010). Syngas Production by Steam-Oxygen Gasification of Biomass and its Cleaning by Bio-Diesel and Water Scrubbing. ETA Florence. 577–585. 1 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.

Explore authors with similar magnitude of impact