PAD: protecting anonymity in publishing building related datasets. - Ruoxi Jia 001; Fisayo Caleb Sangogboye; Tianzhen Hong; Costas J. Spanos; Mikkel Baun Kjærgaard (BuildSys, 2017)

Privacy-preserving building-related data publication using PAD. - Ruoxi Jia 001; Fisayo Caleb Sangogboye; Tianzhen Hong; Costas J. Spanos; Mikkel Baun Kjærgaard (BuildSys, 2017)

A Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems. - Fisayo Caleb Sangogboye; Ruoxi Jia 001; Tianzhen Hong; Costas J. Spanos; Mikkel Baun Kjærgaard (ACM Trans. Sens. Networks, 2018)

Open Computing Infrastructure for Sharing Data Analytics to Support Building Energy Simulations. - 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 (J. Comput. Civ. Eng., 2019)

Effective Missing Value Imputation Methods for Building Monitoring Data. - Brian Cho 001; Teresa Dayrit; Yuan Gao; Zhe Wang 051; Tianzhen Hong; Alex Sim; Kesheng Wu (IEEE BigData, 2020)

The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. - Kingsley Nweye; Zoltán Nagy 002; Sharada P. Mohanty; Dipam Chakraborty; Siva Sankaranarayanan; Tianzhen Hong; Sourav Dey; Gregor Henze; Ján Drgona; Fangquan Lin; Wei Jiang 027; Hanwei Zhang 002; et al. (NeurIPS (Competition and Demos), 2021)

Urban Building Energy Modeling (UBEM) Tools: A State-of-the-Art Review of bottom-up physics-based approaches. - Martina Ferrando; Francesco Causone; Tianzhen Hong; Yixing Chen 004 (CoRR, 2021)

Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset. - Han Li 013; Giuseppe Pinto; Alfonso Capozzoli; Tianzhen Hong (BuildSys, 2022)

Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives. - Han Li 013; Hicham Johra; Flavia de Andrade Pereira; Tianzhen Hong; Jérôme Le Dreau; Anthony Maturo; Mingjun Wei; Yapan Liu; Ali Saberi-Derakhtenjani; Zoltán Nagy 002; Anna Marszal-Pomianowska; Donal Finn; et al. (CoRR, 2022)

CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities. - Kingsley Nweye; Kathryn Kaspar; Giacomo Buscemi; Giuseppe Pinto; Han Li 013; Tianzhen Hong; Mohamed Ouf; Alfonso Capozzoli; Zoltán Nagy 002 (BuildSys, 2023)

CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities. - Kingsley Nweye; Kathryn Kaspar; Giacomo Buscemi; Tiago Fonseca; Giuseppe Pinto; Dipanjan Ghose; Satvik Duddukuru; Pavani Pratapa; Han Li 013; Javad Mohammadi; Luis Lino Ferreira; Tianzhen Hong; et al. (CoRR, 2024)

Building thermal dynamics modeling with deep transfer learning using a large residential smart thermostat dataset. - Han Li 013; Giuseppe Pinto; Marco Savino Piscitelli; Alfonso Capozzoli; Tianzhen Hong (Eng. Appl. Artif. Intell., 2024)

Physics-informed machine learning for building performance simulation-A review of a nascent field. - Zixin Jiang; Xuezheng Wang; Han Li; Tianzhen Hong; Fengqi You; Ján Drgona; Draguna L. Vrabie; Bing Dong (CoRR, 2025)

Systematic Evaluation of Knowledge Graph Repair with Large Language Models. - Tung-Wei Lin; Gabe Fierro; Han Li; Tianzhen Hong; Pierluigi Nuzzo 002; Alberto L. Sangiovanni-Vincentelli (CoRR, 2025)