Kailun FENG

About Kailun FENG

Kailun FENG, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Harbin Institute of Technology, specializes in the field of Construction Management, Green Building, Occupant Behaviour.

His recent articles reflect a diverse array of research interests and contributions to the field:

Transfer of building retrofitting evaluations for data-scarce conditions: An empirical study for Sweden to China

One-class anomaly detection through color-to-thermal AI for building envelope inspection

Understanding consumers' willingness to pay for circular products: A multiple model-comparison approach

Data-driven modelling of building retrofitting with incomplete physics: A generative design and machine learning approach

Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden

A data-driven framework for building energy benchmarking and renovation decision-making support in Sweden

The characteristics of PM emissions from construction sites during the earthwork and foundation stages: an empirical study evidence

Embedding ensemble learning into simulation-based optimisation: a learning-based optimisation approach for construction planning

Kailun FENG Information

University

Position

and Luleå University of Technology

Citations(all)

275

Citations(since 2020)

267

Cited By

76

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

8

i10Index(since 2020)

8

Email

University Profile Page

Google Scholar

Kailun FENG Skills & Research Interests

Construction Management

Green Building

Occupant Behaviour

Top articles of Kailun FENG

Transfer of building retrofitting evaluations for data-scarce conditions: An empirical study for Sweden to China

Energy and Buildings

2024/5

One-class anomaly detection through color-to-thermal AI for building envelope inspection

arXiv preprint arXiv:2402.02963

2024/2/5

Understanding consumers' willingness to pay for circular products: A multiple model-comparison approach

2023/12/7

Kailun Feng
Kailun Feng

H-Index: 6

Caixia Hou
Caixia Hou

H-Index: 6

Data-driven modelling of building retrofitting with incomplete physics: A generative design and machine learning approach

Journal of Physics: Conference Series

2023/12/1

Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden

Technology in Society

2023/11/1

A data-driven framework for building energy benchmarking and renovation decision-making support in Sweden

IOP Conference Series: Earth and Environmental Science

2023/6/1

The characteristics of PM emissions from construction sites during the earthwork and foundation stages: an empirical study evidence

Environmental Science and Pollution Research

2023/5

Embedding ensemble learning into simulation-based optimisation: a learning-based optimisation approach for construction planning

Engineering, Construction and Architectural Management

2023/2/27

Modeling performance and uncertainty of construction planning under deep uncertainty: A prediction interval approach

Buildings

2023/1/16

Shuo Wang
Shuo Wang

H-Index: 31

Kailun Feng
Kailun Feng

H-Index: 6

Dynamic Environmental Impact Assessment of Cross-Sea Bridge Mud Leakage

2023

Kailun Feng
Kailun Feng

H-Index: 6

A Data-Driven Exploration of the Relations between Occupant Behaviors and Comfort Performances of Energy-Efficient Measures

2023

Kailun Feng
Kailun Feng

H-Index: 6

Thomas Olofsson
Thomas Olofsson

H-Index: 23

Energy-efficient retrofitting under incomplete information: A data-driven approach and empirical study of sweden

Buildings

2022/8/15

Kailun Feng
Kailun Feng

H-Index: 6

Planning construction projects in deep uncertainty: A data-driven uncertainty analysis approach

Journal of Construction Engineering and Management

2022/8/1

Kailun Feng
Kailun Feng

H-Index: 6

Shuo Wang
Shuo Wang

H-Index: 31

Energy-efficient retrofitting with incomplete building information: a data-driven approach

2022

Are radiators ready for the challenges of the future: A review of advancements in radiators

2022

Systematic evaluation framework and empirical study of the impacts of building construction dust on the surrounding environment

Journal of cleaner production

2020/12/1

Big-data driven building retrofitting: An integrated Support Vector Machines and Fuzzy C-means clustering method

IOP Conference Series: Earth and Environmental Science

2020/11/1

Kailun Feng
Kailun Feng

H-Index: 6

Concrete Construction: How to Explore Environmental and Economic Sustainability in Cold Climates

Sustainability

2020/5/7

Environmentally friendly construction processes under uncertainty: assessment, optimisation and robust decision-making

2020

Kailun Feng
Kailun Feng

H-Index: 6

See List of Professors in Kailun FENG University(Harbin Institute of Technology)