Manoj Shakya

My name is Manoj Shakya. I am a final year Ph.D. student at Nanyang Technological University, Singapore. I am under the supervison of A/Prof. Francis Lee Bu-Sung (NTU) and Dr. Ng Huey Yuen (SIMTech, A*STAR). My area of research is Deep Reinforcement Learning. The application side of my research focuses on the supply chain optimization techniques.

Before I enrolled into NTU, I was an Assistant Professor at Department of Computer Science and Engineering, Kathmandu University. Currently, I am on study leave. I graduated with a Master of Engineering in Computer Science and Technology from Hunan University, China and Bachelor of Computer Science and Engineering from Kathmandu University, Nepal

Besides research and teaching, I like to watch movies, documentaries about nature/space/war and biographies of big personalities. I love traveling around the world too.

news

Feb 25, 2023	A Deep Reinforcement Learning Approach for Inventory Control under Stochastic Lead Time and Demand is released online.

selected publications

SSCI’22

A Deep Reinforcement Learning Approach for Inventory Control for Stochastic Lead Time and Demand

Shakya, M., Lee, B. S., and Ng, H. Y.

In 2022 IEEE Symposium Series on Computational Intelligence (SSCI) Dec 2022

Bib

@inproceedings{shakya2022DQN,
  abbr = {SSCI'22},
  bibtex_show = {true},
  title = {A Deep Reinforcement Learning Approach for Inventory Control for Stochastic Lead Time and Demand},
  author = {Shakya, M. and Lee, B. S. and Ng, H. Y.},
  doi = {https://doi.org/10.1109/SSCI51031.2022.10022256},
  booktitle = {2022 IEEE Symposium Series on Computational Intelligence (SSCI)},
  year = {2022},
  month = dec,
  selected = {true}
}

AIAI’22

Reinforcement Learning Approach for Multi-period Inventory with Stochastic Demand

Shakya, M., Ng, H. Y., Ong, D. J., and Lee, Bu-Sung

In 18th International Conference on Artificial Intelligence Applications and Innovations (AIAI) Jun 2022

Bib

@inproceedings{shakya2022Qlearning,
  abbr = {AIAI'22},
  bibtex_show = {true},
  title = {Reinforcement Learning Approach for Multi-period Inventory with Stochastic Demand},
  author = {Shakya, M. and Ng, H. Y. and Ong, D. J. and Lee, Bu-Sung},
  booktitle = {18th International Conference on Artificial Intelligence Applications and Innovations (AIAI)},
  year = {2022},
  month = jun,
  selected = {true}
}

SAS’20

Euclidean Distance based Loss Function for Eye-Gaze Estimation

Lee, Bu-Sung, Phattharaphon, R., Yean, S., Liu, J., and Shakya, M.

In 2020 IEEE Sensors Applications Symposium (SAS) Mar 2020

Bib

@inproceedings{lee2020euclidean,
  abbr = {SAS'20},
  bibtex_show = {true},
  title = {Euclidean Distance based Loss Function for Eye-Gaze Estimation},
  author = {Lee, Bu-Sung and Phattharaphon, R. and Yean, S. and Liu, J. and Shakya, M.},
  booktitle = {2020 IEEE Sensors Applications Symposium (SAS)},
  pages = {1--5},
  year = {2020},
  month = mar,
  doi = {https://doi.org/10.1109/SAS48726.2020.9220051},
  organization = {IEEE},
  selected = {true}
}