Yi Wu | Building Energy Simulation | Best Researcher Award

Ms. Yi Wu | Building Energy Simulation | Best Researcher Award

PhD candidate, Tsinghua University, China

Yi Wu is a dedicated Ph.D. candidate in the Department of Building Science at the School of Architecture, Tsinghua University. With a dual background in engineering and economics, Yi bridges technical acumen and strategic insight in sustainable building practices. His academic focus lies in building thermal resilience, occupant behavior simulation, and big data analytics in HVAC systems. He has contributed as a primary and co-author to several high-impact journals, addressing real-world energy challenges using advanced simulations and data mining techniques. Yi is also recognized for developing national-scale building models and co-simulation algorithms for indoor air quality and energy. As a reviewer for prestigious journals like Building Simulation and Energy and Buildings, he is deeply involved in the academic community. His solid coding and analytical skills, coupled with a TOEFL score of 112, position him as a rising expert in the domain of energy-efficient building technologies and smart city applications.

Professional Profile

🎓 Education

Yi Wu began his academic journey at Tsinghua University, earning a Bachelor’s degree in Building Science (2017–2021), where he completed a thesis on extracting AC behavior patterns from large-scale VRF operation data and achieved a GPA of 3.70/4.0. Simultaneously, he pursued a second Bachelor’s degree in Economics and Management (2018–2021), with a thesis focused on the marketing success of blind box companies, scoring a GPA of 3.84/4.0. In 2021, he continued at Tsinghua as a Ph.D. candidate in Building Science, achieving a GPA of 3.88/4.0 to date. His doctoral research emphasizes building thermal resilience, big data mining in HVAC, and simulation of occupant behavior. Yi’s interdisciplinary educational background allows him to approach architectural challenges with both technical precision and managerial insight. This rare combination enhances his effectiveness in multidisciplinary research on energy efficiency, simulation, and behavioral modeling in smart buildings.

🏅 Awards and Honors

Yi Wu has received several prestigious accolades during his academic journey. He was awarded the National Scholarship, one of the highest academic honors in China, for his exceptional performance and contributions. Additionally, he was recognized as a Beijing Outstanding Graduate and an Excellent Graduate of Tsinghua University at the Bachelor level, signifying academic excellence, leadership, and societal contributions. These honors reflect not only his high GPA but also his active engagement in impactful research and academic service. Yi has also served as a reviewer for internationally reputed SCI journals such as Building Simulation, Energy and Buildings, and Advanced Engineering Informatics, showcasing his technical maturity and peer recognition in the research community. His honors validate his role as a young innovator in sustainable architecture and energy-efficient building systems, making him a deserving candidate for international recognition in the field of building energy simulation and data-driven HVAC optimization.

🔬 Research Focus 

Yi Wu’s research is rooted in building energy simulation, thermal resilience, and HVAC data analytics. He specializes in large-scale data mining from Variable Refrigerant Flow (VRF) systems, developing predictive occupant behavior models, and enhancing simulation accuracy through machine learning. His work aims to optimize energy performance in urban buildings by simulating real occupant actions and leveraging big data to inform policy and design. Yi also explores co-simulation of indoor air quality (IAQ) and energy performance through C++-based algorithm development. Another area of focus includes generating Typical Meteorological Year (TMY) data and establishing national-scale prototype building models for carbon emission assessments. His interdisciplinary approach blends simulation tools (DeST, EnergyPlus), programming (Python, TensorFlow), and empirical datasets (30+ TB VRF data) to support green building development at the city and national levels. Yi’s research ultimately contributes to the digitalization and decarbonization of the built environment.

📚 Publication Top Notes

  1. Weather Data Mining
    Wu, Y., An, J., Gui, C., Xiao, C., & Yan, D. (2023). A global typical meteorological year (TMY) database on ERA5 dataset. Building Simulation, 16, 1013–1026. [IF: 5.5]
    Summary: This study constructs a global TMY database based on ERA5 reanalysis data. It supports climate-adaptive building simulation across diverse locations by improving access to standardized weather input data.

  2. VRF System Performance
    Liu, H., Wu, Y., Yan, D., Hu, S., & Qian, M. (2022). Investigation of VRF system cooling operation and performance in residential buildings based on large-scale dataset. Journal of Building Engineering, 1052-1019.
    Summary: The authors evaluate operational patterns and efficiency of residential VRF systems using a vast dataset, revealing real-world behaviors that challenge existing design standards.

  3. Prototype Building Models
    An, J., Wu, Y., Gui, C., & Yan, D. (2023). Chinese prototype building models for simulating the energy performance of the nationwide building stock. Building Simulation, 16(8), 1559–1582. [IF: 5.5]
    Summary: This paper introduces Chinese prototype models to simulate the nation’s building stock energy consumption, providing a foundation for urban-scale energy policy development.

  4. Occupant AC Behavior Modeling
    Wu, Y., Zhou, X., Qian, M., Jin, Y., Sun, H., & Yan, D. (2023). Novel approach to typical air-conditioning behavior pattern extraction based on large-scale VRF system online monitoring data. Journal of Building Engineering, 106243. [IF: 6.4]
    Summary: Yi Wu presents a novel data-driven method to extract typical AC usage patterns, significantly enhancing occupant behavior modeling in HVAC simulation.

  5. OB Level-of-Detail Framework
    Wu, Y., An, J., Qian, M., & Yan, D. (2023). Application-driven level-of-detail modeling framework for occupant air-conditioning behavior in district cooling. Journal of Building Engineering, 70. [IF: 6.4]
    Summary: Proposes a flexible modeling framework adjusting detail levels of occupant behavior to improve simulation accuracy under district cooling scenarios.

  6. Renewable Energy Systems Integration
    Huang, P., Zhang, X., Copertaro, B., Saini, P. K., Yan, D., Wu, Y., & Chen, X. (2020). A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS). Sustainability, 12(17), 7035. [IF: 4.0]
    Summary: Reviews integrated modeling strategies for urban solar systems spanning buildings, electric vehicles, and storage, promoting energy synergy and carbon reduction.

Conclusion

Yi Wu is a highly promising researcher at the intersection of building science, data mining, and sustainability. His interdisciplinary training, impactful publications, and technical versatility make him a strong and deserving candidate for the Best Researcher Award 🏅. With continued growth in leadership and outreach, he is poised to make lasting contributions to the field.

Mudassar Razzaq | numerical simulation | Best Researcher Award

Dr. Mudassar Razzaq | numerical simulation | Best Researcher Award

Research Associate, University of applied sciences Bochum, Germany.

Dr. Mudassar Razzaq is an experienced academic and researcher with over two decades of expertise in STEM education, specializing in applied mathematics, computational modeling, and fluid-structure interaction (FSI). He has worked extensively in both industry and academia, holding various leadership roles. His research integrates high-performance computing with simulation, focused on mathematical modeling of coupled problems. Dr. Razzaq has supervised numerous graduate and Ph.D. students and contributed to several international conferences. Currently, he is a Visiting Professor at the International School of Management, Germany, and a Research Lead at Bochum University of Applied Sciences, specializing in multiphase flow simulations.

Profile:

Google Scholar 

Education 🎓

Dr. Mudassar Razzaq holds a Ph.D. in Applied Mathematics (Computational and Applied Mathematics) from the Technical University of Dortmund, Germany, where his dissertation focused on fluid-structure interaction using finite element methods. He completed his M.Phil. in Applied Mathematics from Quaid-i-Azam University, Islamabad, Pakistan, specializing in fluid dynamics. He also earned an M.Sc. in Mathematics from Quaid-i-Azam University, with a focus on applied mathematics and statistics. His academic journey began with a B.Sc. in Mathematics and Physics from the University of Punjab, Lahore, Pakistan.

Professional Experience 💼

Dr. Razzaq’s career spans academic and industry roles. He is currently a Visiting Professor in Management Information Systems at the International School of Management, Germany. Previously, he served as an Assistant Professor at the Lahore University of Management Sciences (LUMS), Pakistan, where he taught various mathematics and engineering courses. His industry experience includes working as a Senior CFD Engineer at IANUS Simulation GmbH in Germany. He has also contributed to research at the Weierstrass Institute for Applied Analysis and Stochastic in Berlin and various other institutions in Germany.

Awards & Honors 🏆

Dr. Mudassar Razzaq has received several prestigious awards and fellowships throughout his career, including a faculty travel grant for the International Multigrid Conference in China (2019) and a faculty start-up research grant in 2017. He was awarded the HEC-DAAD scholarship for his Ph.D. studies, receiving significant funding for his research. He also co-led the ExtremSimOpt research project funded by the Federal Ministry of Education and Research (BMBF), Germany, in 2020. In 2021, he won the first prize for a poster presentation.

Research Focus 🔬

Dr. Razzaq’s research primarily revolves around computational and applied mathematics, with a focus on fluid-structure interaction (FSI), high-performance computing, and multiphysics simulations. His work includes the development of finite element simulation techniques and numerical solvers for FSI and CFD applications in bioengineering and optimization. He is particularly interested in modeling multiphase flows, thermodynamics, and the application of statistical and machine learning models in various scientific fields such as finance and engineering. His research is highly interdisciplinary, bridging mathematics, engineering, and data science.

Publications 📚

  1. Numerical benchmarking of fluid-structure interaction: A comparison of different discretization and solution approaches
  2. Numerical simulation and benchmarking of a monolithic multigrid solver for fluid-structure interaction problems with application to hemodynamics
  3. Finite element analysis of bi-viscosity fluid enclosed in a triangular cavity under thermal and magnetic effects
  4. FEM multigrid techniques for fluid–structure interaction with application to hemodynamics
  5. Finite element simulations for energy transfer in a lid-driven porous square container filled with micropolar fluid: Impact of thermal boundary conditions and Peclet number
  6. Numerical simulation and benchmarking of fluid-structure interaction with application to hemodynamics
  7. Computational approach on three-dimensional flow of couple-stress fluid with convective boundary conditions
  8. Finite element simulation techniques for incompressible fluid structure interaction with applications to bioengineering and optimization
  9. The impact of variable fluid properties on hydromagnetic boundary layer and heat transfer flows over an exponentially stretching sheet
  10. Simulation of intra‐aneurysmal blood flow by different numerical methods
  11. Numerical benchmarking of fluid-structure interaction between elastic object and laminar incompressible flow
  12. Numerical simulation of laminar incompressible fluid-structure interaction for elastic material with point constraints
  13. Analysis of biomagnetic blood flow in a stenosed bifurcation artery amidst elastic walls
  14. Numerical techniques for solving fluid-structure interaction problems with applications to bio-engineering
  15. A simplified finite difference method (SFDM) solution via tridiagonal matrix algorithm for MHD radiating nanofluid flow over a slippery sheet submerged in a permeable medium
  16. Multi-objective optimization of a fluid structure interaction benchmarking