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2020 – today
- 2024
[j3]Han Li
, Giuseppe Pinto, Marco Savino Piscitelli, Alfonso Capozzoli, Tianzhen Hong:
Building thermal dynamics modeling with deep transfer learning using a large residential smart thermostat dataset. Eng. Appl. Artif. Intell. 130: 107701 (2024)- [i3]Kingsley Nweye, Kathryn Kaspar, Giacomo Buscemi, Tiago Fonseca, Giuseppe Pinto, Dipanjan Ghose, Satvik Duddukuru, Pavani Pratapa, Han Li, Javad Mohammadi, Luis Lino Ferreira, Tianzhen Hong, Mohamed Ouf, Alfonso Capozzoli, Zoltán Nagy:
CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities. CoRR abs/2405.03848 (2024) - 2023
- [c6]Kingsley Nweye, Kathryn Kaspar, Giacomo Buscemi, Giuseppe Pinto, Han Li, Tianzhen Hong, Mohamed Ouf, Alfonso Capozzoli, Zoltán Nagy:
CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities. BuildSys@SenSys 2023: 274-275 - 2022
- [c5]Han Li, Giuseppe Pinto, Alfonso Capozzoli, Tianzhen Hong:
Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset. BuildSys@SenSys 2022: 242-245 - [i2]Han Li, Hicham Johra, Flavia de Andrade Pereira, Tianzhen Hong, Jérôme Le Dreau, Anthony Maturo, Mingjun Wei, Yapan Liu, Ali Saberi-Derakhtenjani, Zoltán Nagy, Anna Marszal-Pomianowska, Donal Finn, Shohei Miyata, Kathryn Kaspar, Kingsley Nweye, Zheng O. Neill, Fabiano Pallonetto, Bing Dong:
Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives. CoRR abs/2211.12252 (2022) - 2021
- [c4]Kingsley Nweye, Zoltán Nagy, Sharada P. Mohanty, Dipam Chakraborty, Siva Sankaranarayanan, Tianzhen Hong, Sourav Dey, Gregor Henze, Ján Drgona, Fangquan Lin, Wei Jiang, Hanwei Zhang, Zhongkai Yi, Jihai Zhang, Cheng Yang, Matthew Motoki, Sorapong Khongnawang, Michael Ibrahim, Abilmansur Zhumabekov, Daniel May, Zhihu Yang, Xiaozhuang Song, Han Zhang, Xiaoning Dong, Shun Zheng, Jiang Bian:
The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) 2021: 85-103 - [i1]Martina Ferrando, Francesco Causone, Tianzhen Hong, Yixing Chen:
Urban Building Energy Modeling (UBEM) Tools: A State-of-the-Art Review of bottom-up physics-based approaches. CoRR abs/2103.01761 (2021) - 2020
- [c3]Brian Cho, Teresa Dayrit, Yuan Gao, Zhe Wang, Tianzhen Hong, Alex Sim, Kesheng Wu:
Effective Missing Value Imputation Methods for Building Monitoring Data. IEEE BigData 2020: 2866-2875
2010 – 2019
- 2019
- [j2]Omer Tugrul Karaguzel, Mohammed Elshambakey, Yimin Zhu, Tianzhen Hong, William J. Tolone, Sreyasee Das Bhattacharjee, Isaac Cho, Wenwen Dou, Haopeng Wang, Siliang Lu, Mohamed Khalefa, Yong Tao:
Open Computing Infrastructure for Sharing Data Analytics to Support Building Energy Simulations. J. Comput. Civ. Eng. 33(6) (2019) - 2018
- [j1]Fisayo Caleb Sangogboye, Ruoxi Jia, Tianzhen Hong, Costas J. Spanos, Mikkel Baun Kjærgaard:
A Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems. ACM Trans. Sens. Networks 14(3-4): 30:1-30:22 (2018) - 2017
- [c2]Ruoxi Jia, Fisayo Caleb Sangogboye, Tianzhen Hong, Costas J. Spanos, Mikkel Baun Kjærgaard:
PAD: protecting anonymity in publishing building related datasets. BuildSys@SenSys 2017: 4:1-4:10 - [c1]Ruoxi Jia, Fisayo Caleb Sangogboye, Tianzhen Hong, Costas J. Spanos, Mikkel Baun Kjærgaard:
Privacy-preserving building-related data publication using PAD. BuildSys@SenSys 2017: 32:1-32:2
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