John M. House

1.9k total citations
56 papers, 1.5k citations indexed

About

John M. House is a scholar working on Control and Systems Engineering, Mechanical Engineering and Building and Construction. According to data from OpenAlex, John M. House has authored 56 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Control and Systems Engineering, 16 papers in Mechanical Engineering and 11 papers in Building and Construction. Recurrent topics in John M. House's work include Advanced Control Systems Optimization (21 papers), Extremum Seeking Control Systems (20 papers) and Fault Detection and Control Systems (17 papers). John M. House is often cited by papers focused on Advanced Control Systems Optimization (21 papers), Extremum Seeking Control Systems (20 papers) and Fault Detection and Control Systems (17 papers). John M. House collaborates with scholars based in United States, Canada and South Korea. John M. House's co-authors include Timothy I. Salsbury, Theodore F. Smith, Jeffrey Schein, C. Beckermann, Steven T. Bushby, Prashant Mhaskar, Won‐Young Lee, John E. Seem, Yaoyu Li and Dong Ryeol Shin and has published in prestigious journals such as Applied Energy, Industrial & Engineering Chemistry Research and Chemical Engineering Science.

In The Last Decade

John M. House

55 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John M. House United States 17 675 649 395 224 214 56 1.5k
Martin Kozek Austria 22 837 1.2× 703 1.1× 499 1.3× 597 2.7× 70 0.3× 161 1.9k
John E. Seem United States 20 591 0.9× 561 0.9× 377 1.0× 483 2.2× 51 0.2× 68 1.5k
Yunpeng Hu China 24 497 0.7× 741 1.1× 426 1.1× 331 1.5× 143 0.7× 57 1.5k
Yuebin Yu United States 28 282 0.4× 1.0k 1.5× 1.1k 2.7× 216 1.0× 109 0.5× 55 2.0k
Luca Cecchinato Italy 22 226 0.3× 486 0.7× 1.1k 2.7× 164 0.7× 426 2.0× 56 1.5k
Hua Han China 19 461 0.7× 517 0.8× 259 0.7× 252 1.1× 74 0.3× 34 1.1k
Mirco Rampazzo Italy 15 278 0.4× 359 0.6× 366 0.9× 204 0.9× 79 0.4× 73 935
Wenjian Cai Singapore 26 1.2k 1.7× 239 0.4× 532 1.3× 292 1.3× 122 0.6× 66 1.9k
Bryan P. Rasmussen United States 16 469 0.7× 350 0.5× 762 1.9× 154 0.7× 55 0.3× 89 1.3k
Timothy I. Salsbury United States 20 928 1.4× 902 1.4× 431 1.1× 424 1.9× 24 0.1× 68 1.7k

Countries citing papers authored by John M. House

Since Specialization
Citations

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

Fields of papers citing papers by John M. House

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. House. 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 John M. House. The network helps show where John M. House may publish in the future.

Co-authorship network of co-authors of John M. House

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

All Works

20 of 20 papers shown
1.
Lin, Guanjing, et al.. (2025). Active multi-mode data analysis to improve fault diagnosis in AHUs. Energy and Buildings. 337. 115621–115621. 1 indexed citations
2.
Mhaskar, Prashant, et al.. (2024). A hybrid clustering approach integrating first-principles knowledge with data for fault detection in HVAC systems. Computers & Chemical Engineering. 187. 108717–108717. 6 indexed citations
3.
Li, Yaoyu, et al.. (2022). Data-Driven Self-Optimizing Control With Parametric Programing Based Constraint Handling. Journal of Dynamic Systems Measurement and Control. 144(9). 1 indexed citations
4.
Li, Yaoyu, et al.. (2021). Dither extremum seeking control of a variable refrigerant flow system with equality constraint handling. Science and Technology for the Built Environment. 28(2). 152–169. 4 indexed citations
5.
Mhaskar, Prashant, et al.. (2020). A hybrid modeling approach integrating first-principles knowledge with statistical methods for fault detection in HVAC systems. Computers & Chemical Engineering. 142. 107022–107022. 34 indexed citations
6.
Li, Yaoyu, et al.. (2020). Model-free control and staging for real-time energy efficient operation of a variable refrigerant flow system with multiple outdoor units. Applied Thermal Engineering. 180. 115787–115787. 11 indexed citations
7.
Mhaskar, Prashant, et al.. (2018). Distributed fault diagnosis of heating, ventilation, and air conditioning systems. AIChE Journal. 65(2). 640–651. 10 indexed citations
8.
Guay, Martin, et al.. (2018). Decentralized Proportional-Integral Extremum Seeking Control for Heating, Ventilation and Air Conditioning (HVAC) Systems. 2018 IEEE Conference on Control Technology and Applications (CCTA). 800–805. 1 indexed citations
9.
Salsbury, Timothy I., John M. House, Carlos F. Alcala, & Yaoyu Li. (2017). An extremum-seeking control method driven by input–output correlation. Journal of Process Control. 58. 106–116. 6 indexed citations
10.
11.
Li, Yaoyu, et al.. (2016). Evaluation of an Extremum Seeking Control Based Optimization and Sequencing Strategy for a Chilled-water Plant. Purdue e-Pubs (Purdue University System). 1 indexed citations
12.
Li, Yaoyu, et al.. (2016). Optimization and sequencing of chilled-water plant based on extremum seeking control. 84. 2373–2378. 6 indexed citations
13.
14.
Seem, John E. & John M. House. (2009). Integrated Control and Fault Detection of Air-Handling Units. HVAC&R Research. 15(1). 25–55. 16 indexed citations
15.
Joshi, Shailesh N., et al.. (2005). An Experimental Evaluation of Duct-Mounted Relative Humidity Sensors: Part 3 – Repeatability, Hysteresis and Linearity Results. OAKTRUST (Texas A&M University). 177–184. 1 indexed citations
16.
Schein, Jeffrey & John M. House. (2003). Application of Control Charts for Detecting Faults in Variable-Air-Volume Boxes. ASHRAE journal. 109(2). 31 indexed citations
17.
House, John M., et al.. (2001). An Expert Rule Set For Fault Detection In Air-Handling Units | NIST. ASHRAE winter conference papers. 1(1). 25–7. 34 indexed citations
18.
House, John M., Won‐Young Lee, & Dong Ryeol Shin. (1999). Classification Techniques for Fault Detection and Diagnosis of an Air-Handling Unit | NIST. ASHRAE journal. 105(1). 42 indexed citations
19.
Seem, John E., et al.. (1999). On-Line Monitoring and Fault Detection of Control System Performance | NIST. ASHRAE journal. 41(7). 8 indexed citations
20.
Seem, John E., Cheol Park, & John M. House. (1999). A New Sequencing Control Strategy for Air-Handling Units. HVAC&R Research. 5(1). 35–58. 32 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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