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Journal of Architectural Engineering Technology received 1142 citations as per Google Scholar report
Editor-in-Chief |
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Executive Editor |
University of Cyprus | ||
Dr. Chiu Shui Chan |
Iowa State University | ||
Dr. Michael J. Buono |
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Dr. Jawaid Haider |
Pennsylvania State University | ||
Dr. Peter Magyar |
Kansas State University | ||
Dr. Libero Andreotti |
Georgia Institute of Technology | ||
Dr. Ted Cavanagh |
Dalhousie University | ||
Dr. WK Chow |
The Hong Kong Polytechnic university | ||
Dr. Hasim Altan |
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Dr. Athanassios Economou |
Georgia Institute of Technology | ||
Jae Weon Jeong |
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Dr. Dale Clifford |
Carnegie Mellon University | ||
Dr. Ji Young Cho |
Kent State University | ||
Dr. Bernhard Sill |
Clemson University | ||
Dr. Keith E. Hedges |
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Dr. Kyoung Sun Moon |
Yale University | ||
Mohammadjavad Mahdavinejad |
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Liverpool John Moores University | |||
Executive Editor School of The Built Environment and Architecture UK |
London South Bank University | ||
Executive Editor Assistant Professor of Architectural Engineering |
Alfaisal University | ||
John K.S.S. Philip M.D, Hemato pathology fellowship University, University of Chicago, United States |
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Dr. Chandra Shekhar Kapoor, Assistant Professor, (P.I.B.S), Pacific Academy of Higher Education and Research University, INDIA |
Pacific University | ||
Dr. Pedro Gil Marques de Queirós Ferreira, Department of Civil Engineering, University of Porto, Portugal |
University of Porto | ||
Executive Editor |
Clemson University | ||
Sensing and computing technologies In combination with data analytics provides a suitable platform for building performance assessment, process development for building control, and product development as needed by the building industry. In my doctoral work, I developed a Zone-level occupancy-based Plug, Lighting and Air Conditioning, and Mechanical Ventilation system control which focuses on leveraging artificial neural networks to accurately gauge and identify occupant energy utilization within building zones. A major outcome of my Ph.D. is a robust iterative method that can be used to predict and control, in real-time, based on occupancy, the operation of Mechanical and Electrical systems across all zones in a building. Such an understanding can contribute to the efficient management of existing buildings. In continuation of my Ph.D. and postdoc work at the Centre for Integrated Building Energy and Sustainability in the Tropics (CiBEST) of NUS Singapore, My current research interest at IIT Kharagpur is to investigate the impact of outdoor/indoor pollutants and viral loads on building system control, system-level, and building-level energy efficiency, and on zone level occupant’s health and wellbeing. |
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