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

John M. House

CSE

EEE

Martin Kozek Austria

John E. Seem United States

Yunpeng Hu China

Yuebin Yu United States

Luca Cecchinato Italy

Hua Han China

Mirco Rampazzo Italy

Wenjian Cai Singapore

Bryan P. Rasmussen United States

Timothy I. Salsbury United States

Martin Kozek Austria

John M. House

837 ×1.2

CSE

703 ×1.1

499 ×1.3

597 ×2.7

EEE

70 ×0.3

Citations per year, relative to John M. House John M. House (= 1×) peers Martin Kozek

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

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20 of 20 papers shown

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

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

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

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

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

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

Mhaskar, Prashant, et al.. (2018). Distributed fault diagnosis of heating, ventilation, and air conditioning systems. AIChE Journal. 65(2). 640–651. 10 indexed citations

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

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.

Li, Yaoyu, et al.. (2017). Input selection for multivariable extremum seeking control with application to real-time optimization of a chilled-water plant. 62–67. 4 indexed citations

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.

Li, Yaoyu, et al.. (2016). Self-optimizing control and mode switching for multi-functional Variable Refrigerant Flow air conditioning systems via extremum seeking. 49. 593–598. 2 indexed citations

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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