I am currently a Ph.D. student working in School of Computing, National University of Singapore, supervised by Prof. Dong Jin Song.
My research interests include trustworthy AI, graph neural networks and many other computer science topics.
I got my Master's and B.Eng. degree in NUS and Xidian University respectively.
RESEARCH π§ͺ
PUBLICATIONS 𧻠[view full list]
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Xinke Li, Junchi Lu, Henghui Ding
PointCVaR: Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024. [pdf | website | code]
, Joey Tianyi Zhou, Chee Yeow Meng.
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Yan Xiao, Yun Lin, Ivan Beschastnikh,
Repairing Failure-inducing Inputs with Input Reflection. The 37th IEEE/ACM International Conference on Automated Software Engineering (ASE) 2022. [pdf | code]
, David S. Rosenblum, Jin Song Dong. -
Hui Li, Mengting Xu, Sourav S Bhowmick, Joty Shafiq Rayhan,
PIANO: Influence Maximization Meets Deep Reinforcement Learning. IEEE Transactions on Computational Social Systems. [pdf | ieee]Since its introduction in 2003, the influence maximization (IM) problem has drawn significant research attention in the literature. The aim of IM, which is NP-hard, is to select a set of k users known as seed users who can influence the most individuals in the social network. The state-of-the-art algorithms estimate the expected influence of nodes based on sampled diffusion paths. As the number of required samples has been recently proven to be lower bounded by a particular threshold that presets tradeoff between the accuracy and the efficiency, the result quality of these traditional solutions is hard to be further improved without sacrificing efficiency. In this article, we present an orthogonal and novel paradigm to address the IM problem by leveraging deep reinforcement learning (RL) to estimate the expected influence. In particular, we present a novel framework called deeP reInforcement leArning-based iNfluence β¦
, Jiangtao Cui.
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Yan Xiao, Ivan Beschastnikh, David S. Rosenblum,
Self-Checking Deep Neural Networks in Deployment. The 43rd IEEE/ACM International Conference on Software Engineering (ICSE), 2021.. [pdf | code]
, Sebastian Elbaum, Y. Lin, Jin Song Dong.
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Zekun Tong, Yuxuan Liang,
Digraph Inception Convolutional Networks. Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020.. [pdf | poster | code]
, Xinke Li, David S. Rosenblum, Andrew Lim.
, David S Rosenblum, Jin Song Dong
, David S. Rosenblum, Andrew Lim.
, Zhongyuan Jiang, Jiangtao Cui
TEACHING π
- CS5232 Formal Specification and Design Techniques (2024), Teaching Assistant, NUS
- CS4218 Software Testing (2023), Teaching Assistant, NUS
- CS4211 Formal Methods for Software Engineering (2022), Teaching Assistant, NUS
BIO πΈ
PhD Candidate @NUS (supervisor: Dong Jin Song)◄ MComp @NUS◄ Research Intern & Algorithm Engineer @ JD Intelligent Cities Research , China. (2018) ◄ BEng @Xidian University.
CONTACT π
Sun Changsheng (εεΈΈζ)Programming Languages & Software Engineering Lab (PLSE@NUS),
Computing 3 #02-20,
11 Research Link, Singapore 119391.
Email: cssun[at]u[dot]nus[dot]edu
PHOTO GALLERY πΈ
Here are some selected photos, see more at my Instagram: changsheng_sun.β» click to show large image.
- ◄ Mount Bromo, is an active somma volcano and part of the Tengger mountains, in East Java, Indonesia.
- ◄ New York City Midtown with One World Trade Center, shot from Empire State Building at Sunset.
- ◄ Alishan Range.
- ◄ Portland Head Light coastline.
- ◄ Qingshui Cliff, Hualien County, Taiwan.
- ◄ Temple Street, Kowloon, Hong Kong.
Β© Sun Changsheng | Updated 2023-12-16