BAOSHEN GUO

Postdoc Associate, SMART Singapore

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.

Previously, I obtained my Ph.D. degree in Computer Science from Southeast University, under supervision of Prof. Shuai Wang. I am also working with Prof. Desheng Zhang and Prof. Tian He in research. I did one year of research at McGill University, Montreal as a Graduate Research Trainee, under the supervision of Prof. Xue Liu.

My research interests are broadly in the areas of Generative AI, Human-Centered Computing, and Learning-based Decision-Making in Smart Cities and Urban Cyber-Physical Systems.

My long-term research goal is to build Robust, Interpretable, Safe, and Efficient reinforcement learning and generative AI models for real-world urban systems.

You can contact me at (baoshen DOT guo AT smart DOT mit DOT edu) or (baoshen AT mit DOT edu) if you’re interested in any of my research or collaboration

I am involved in M3S, part of MIT’ SMART program as a Postdoc. I am open to research discussion and collaboration, please drop me an email if you are interested!

news

Jul 22, 2024	Two co-authored paper accepted by ACM CIKM 2024.
May 14, 2024	One paper accepted by IEEE TKDE
May 10, 2024	One paper accepted by ACM SIGKDD’24
Dec 15, 2023	One paper accepted by IEEE Transactions on Mobile Computing.
May 15, 2023	Two papers accepted by ACM SIGKDD’23.

selected publications

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},
}