My Chinese name is “王上上”. The direct translation of my first name is “Upup” (my nickname). It means “Always Be Better” (my motto). I pick “Ashton” as my English name, inspired by the G.O.A.T. video games: Bloodborne, Dark Souls and Elden Ring.
I am a first-year CS Phd student at University of Southern California (USC), in the Viterbi School and School of Advanced Computing (SAC), where I am fortunately advised by Prof. Willie Neiswanger. Previous to that, I obtained my CS Master's degree and Bachelor's degree at ShanghaiTech University.
In terms of research, I’ve spent over five years of time at ShanghaiTech University, exploring the constrained bandit theory and its application to distributed edge systems. This style of bridging theory and practice continues to be the first principle I’d stick to during my current Phd study at USC and future research life.
Now, my research interests include
- 🦙 Generative AI, e.g., LLM post-training (fine-tuning, serving, test-time compute, etc)
- 🎰 Decision-making, e.g., Bandits & Reinforcement learning
- 🔬 AI-for-Science, e.g., LLM for Genomics.
⇒ Contact email: upup.ashton.wang at gmail dot com
⇒ Google scholar: https://scholar.google.com/citations?user=KOhDoFMAAAAJ&hl
⇒ Github: https://github.com/shangshang-wang
⇒ LinkedIn: https://www.linkedin.com/in/upup-ashton-wang/
⇒ Bluesky: https://bsky.app/profile/shangshang-wang.bsky.social
Publications
Ph.D. at USC
- O. Liu, S. Jaghouar, J. Hagemann, S. Wang, J. Wiemels, J. Kaufman and W. Neiswanger, “METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring" 2025. [PDF] [Web] [Github] [HF] [Bluesky] [X]
- S. Wang, Z. Shao and Y. Yang, "Constrained Dueling Bandits for Edge Intelligence," IEEE TNSE, 2025. [PDF]
Undergraduate & Master at ShanghaiTech
- M. Chen, S. Wang, T. Zhang, Z. Shao, and Y. Yang, “GNN-Aided Distributed GAN with Partially Observable Social Graph.” IEEE WCNC, 2024. [PDF]
- T. Zhang, S. Wang, Y. Tang, Z. Shao, and Y. Yang, “Privacy-Preserving Edge Intelligence: A Perspective of Constrained Bandits.” IEEE WCNC, 2024. [PDF]
- Y. Xu, S. Wang, H. Guo, Z. Shao, and X. Liu, "Learning to Schedule Online Tasks with Bandit Feedback," AAMAS, 2024. (Oral) [PDF]
- S. Wang, Z. Shao, and J. Lui, "Next-Word Prediction: A Perspective of Energy-Aware Distributed Inference," IEEE TMC, 2023. [PDF]
- S. Wang, S. Bian, X. Liu, and Z. Shao, "Neural Constrained Combinatorial Bandits," IEEE INFOCOM, 2023. [PDF] [Slides]
- S. Wang, and Z. Shao, "Green Dueling Bandits," IEEE ICC, 2023. [PDF] [Slides]
- S. Wang, S. Bian, Y. Tang, and Z. Shao, "Social-Aware Distributed Meta-Learning: A Perspective of Constrained Graphical Bandits," IEEE ICC, 2023. [PDF] [Slides]
- S. Wang, J. Wang, Y. Mao, and Z. Shao, "Online Learning-Based Beamforming for Rate-Splitting Multiple Access: A Constrained Bandit Approach," IEEE ICC, 2023. [PDF] [Slides]
- S. Bian, S. Wang, Y. Tang, and Z. Shao, "Social-Aware Edge Intelligence: A Constrained Graphical Bandit Approach," IEEE GLOBECOM, 2022. [PDF] [Slides]
- Q. Leng, S. Wang, X. Huang, Z. Shao, and Y. Yang, "Decentralized Multi-Agent Bandit Learning for Intelligent Internet of Things Systems," IEEE WCNC, 2022. [PDF] [Slides]
Teaching Assistantship
Undergraduate & Master at ShanghaiTech
- Probability and Statistics for EECS
- Undergrad course, Head TA, Spring 2023, 2024 & Fall 2021, 2022, 2023
- Reinforcement Learning
- Grad course, TA, Spring 2021, 2022
Awards & Honors
Undergraduate & Master at ShanghaiTech
- Jun 2024: Outstanding Graduate Student of Shanghai Province
- Jun 2024: Outstanding Graduate Student of ShanghaiTech
- Oct 2023: China National Scholarship for Graduate Students
- Jun 2021: Outstanding Undergraduate Thesis Award
Research Guidelines