BAOSHEN GUO

baoshen@mit.edu

I am currently a postdoc associate at the Singapore-MIT Alliance for Research and Technology (SMART), Massachusetts Institute of Technology (MIT), work with Prof. Jinhua Zhao and Prof. Shenhao Wang. I am involved in M3S, part of MIT’ SMART program.

I did one year of research at McGill University, Montreal as a Graduate Research Trainee, under the supervision of Prof. Steve Xue Liu. Previously, I obtained my Ph.D. degree in Computer Science from Southeast University, under supervision of Prof. Shuai Wang and Prof. Tian He. I am also working with Prof. Desheng Zhang in research. My research interests are broadly in the areas of Generative AI, Diffusion Model, Smart Cities, and Cyber-Physical Systems. My works have been recognized by the IEEE Real-Time Systems Committee with the Outstanding Paper Award of RTSS, 2021 (CCF-A) and the Distinguish Paper Award of the IoT Committee, Chinese Institute of Electronics. I was also awarded the Best Student Paper Award of ICA3PP and the Best Paper Candidate of RTSS.

Opening

Research internship (SMART Centre, MIT, Singapore)
I am hiring paid research interns (1–2) and visiting students (1–2) (Bachelor or Master students in Singapore). Please see the job description and submit your application. If you apply, please drop me an email at baoshen@mit.edu so we can speed up the process.

News

[2026/02] One paper about Urban-scale POI Updating is accepted by IEEE TMC.
[2025/12] Our paper about language models for urban mobility is online. Paper (TechRxiv)
[2025/11] Two papers accepted by ACM KDD 2026.
[2025/05] Our Cascaded diffusion model based trajectory generation paper is online.
[2024/09] I join SMART centre, MIT as a postdoc associate. I am involved in Mens, Manus, and Machina (M3S) program.

▸ More news

[2024/07] Two co-authored papers accepted by ACM CIKM 2024.
[2024/05] One paper accepted by IEEE TKDE.
[2024/05] One paper accepted by ACM SIGKDD'24.
[2023/12] One paper accepted by IEEE Transactions on Mobile Computing.
[2023/05] Two papers accepted by ACM SIGKDD'23.

Selected Publications

KDD 26

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion

Baoshen Guo, Zhiqing Hong, Junyi Li, and 2 more authors

In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2026

Bib HTML Code

@inproceedings{guo2026leveraging_kdd,
  title = {Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion},
  author = {Guo, Baoshen and Hong, Zhiqing and Li, Junyi and Wang, Shenhao and Zhao, Jinhua},
  booktitle = {Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year = {2026},
}

KDD 24

Multi-task Conditional Attention Network for Conversion Prediction in Logistics Advertising

Baoshen Guo, Xining Song, Shuai Wang, and 3 more authors

In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Bib

@inproceedings{guo2024multi-task,
  title = {Multi-task Conditional Attention Network for Conversion Prediction in Logistics Advertising},
  author = {Guo, Baoshen and Song, Xining and Wang, Shuai and Gong, Wei and Tian, He and Liu, Xue},
  booktitle = {Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages = {4078--4088},
  year = {2024}
}

KDD 23

Towards equitable assignment: Data-driven delivery zone partition at last-mile logistics

Baoshen Guo, Shuai Wang, Haotian Wang, and 4 more authors

In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Bib HTML

@inproceedings{guo2023towards,
  title = {Towards equitable assignment: Data-driven delivery zone partition at last-mile logistics},
  author = {Guo, Baoshen and Wang, Shuai and Wang, Haotian and Liu, Yunhuai and Kong, Fanshuo and Zhang, Desheng and He, Tian},
  booktitle = {Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages = {4078--4088},
  year = {2023},
}

IMWUT 22

Wepos: Weak-supervised indoor positioning with unlabeled wifi for on-demand delivery

Baoshen Guo, Weijian Zuo, Shuai Wang, and 5 more authors

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2022

Bib

@article{guo2022wepos,
  title = {Wepos: Weak-supervised indoor positioning with unlabeled wifi for on-demand delivery},
  author = {Guo, Baoshen and Zuo, Weijian and Wang, Shuai and Lyu, Wenjun and Hong, Zhiqing and Ding, Yi and He, Tian and Zhang, Desheng},
  journal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
  volume = {6},
  number = {2},
  pages = {1--25},
  year = {2022},
  publisher = {ACM New York, NY, USA},
}

RTSS 21

Concurrent order dispatch for instant delivery with time-constrained actor-critic reinforcement learning

Baoshen Guo, Shuai Wang, Yi Ding, and 4 more authors

In 2021 IEEE Real-Time Systems Symposium (RTSS), 2021

Bib

@inproceedings{guo2021concurrent,
  title = {Concurrent order dispatch for instant delivery with time-constrained actor-critic reinforcement learning},
  author = {Guo, Baoshen and Wang, Shuai and Ding, Yi and Wang, Guang and He, Suining and Zhang, Desheng and He, Tian},
  booktitle = {2021 IEEE Real-Time Systems Symposium (RTSS)},
  pages = {176--187},
  year = {2021},
  organization = {IEEE},
}