Lin Yang  Tenure-track Assistant Professor (准聘助理教授，特聘研究员，博士生导师) Nanjing University, School of Intelligent Science and Technology (Suzhou Campus) [Google Scholar] [CV] Biography    Contact    Research Interests    News    Publications    Lab

Biography

Contact

• 🏢Office: Nanjing University, Suzhou Campus.

• 📧Email: linyang@nju.edu.cn, yanglin.cuhk@gmail.com

• 🖥Homepage: https://yanglin2021.github.io/index.html

Research Interests

• Machine Learning  

  • Online Learning: Experts, Bandits, Online Convex Optimization, Multi-scale Online Learing，Online Learning with Attacks/Corruptions
  • Distributed Learning/Estimation
  • Statistical Learning
  • Optimization and Operation Research: Knapsack, Job Scheduling, Ski Rental, Online Linear Programming, Online Decision Making etc.

• Foundation Model

  • Include both "ML for Foundation Model" and "Foundation Model for ML", such as optimizing the implementation of LLMs in Edge etc.  

News

• 03/2022. Our paper "Hierarchical Learning Algorithms for Multi-scale Expert Problems" is accepted to [SIGMETRICS 2022]!

• 12/2021. A new paper  “Distributed Bandits with Heteregeneous Agents“ is accepted to  [INFOCOM 2022 ].

• 10/2021. Our paper “Competitive Algorithms for Online Multidimensional Knapsack Problems“ is accepted to [SIGMETRICS 2022]!

• 10/2021. Our paper “Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback“ is accepted to [NeurIPS 2021].

• 09/2020. Our paper “Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm “ is accepted to [NeurIPS 2020].

Openings!

• I do have several openings for students to work with me for a master/PhD degree. Please drop me emails if you are interested in working in my group with the following topics:
  • Machine Learning
  • Joint Topics on Machine Learning and Foundation Model
• 实验室招收2025年推免硕士生、直博生、申请-考核制博士，以及科研助理，研究方向为机器学习相关前沿课题（包括机器学习、大模型等）。有意向的同学请直接将简历发送邮箱：linyang@nju.edu.cn。

Selected (Representative) Publications [Full list in Google Scholar or Lab【Pub】]

1. [SIGMETRICS 2025] Asynchronous Multi-Agent Bandits: Fully Distributed vs. Leader-Coordinated Algorithms
   Xuchuang Wang, Janice Chen, Xutong Liu, , Lin Yang*, Mohammad Hajiesmaili, John CS Lui, Don Towsley
   ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2025. (Full Paper).

2. [SIGMETRICS 2023] The Online Knapsack Problem with Departures
   Bo Sun#, Lin Yang#, Mohammad Hajiesmaili, Adam Wierman, Don Towsley
   ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2023. (Full Paper).

3. [SIGMETRICS 2022] Hierarchical Learning Algorithms for Multi-scale Expert Problems [PDF]
   Lin Yang, Yu-zhen Chen, Mohammad Hajiesmaili, Mark Herbster, Don Towsley
   ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2022. (Full Paper)
   Journal Version: Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2022, 6(2): 1-29.

4. [INFOCOM 2022] Distributed Bandits with Heterogeneous Agents [PDF]
   Lin Yang, Yu-zhen Chen, Mohammad Hajiesmaili, John CS Lui, Don Towsley
   IEEE International Conference on Computer Communications (INFOCOM), 2022.

5. [SIGMETRICS 2022] Competitive Algorithms for Online Multidimensional Knapsack Problems [PDF]
   Lin Yang, Ali Zeynali, Mohammad Hajiesmaili, Ramesh Sitaraman, Donald F. Towsley
   ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2022. (Full Paper)
   Journal Version: Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2021, 5(3): 1-30.

6. [NeurIPS 2021] Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback [PDF]
   Lin Yang, Yu-Zhen Janice Chen, Stephen Pasteris, Mohammad Hajiesmaili, John CS Lui, Don Towsley
   Advances in Neural Information Processing Systems (NeurIPS), 2021.

7. [NeurIPS 2020] Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm [PDF]
   Lin Yang, Mohammad Hajiesmaili, Mohammad Sadegh Talebi, John CS Lui, Wing Shing Wong
   Advances in Neural Information Processing Systems (NeurIPS), 2020.

8. [SIGMETRICS 2020] Online Linear Optimization with Inventory Management Constraints [PDF]
   Lin Yang#, Mohammad Hajiesmaili#, Ramesh Sitaraman, Adam Wierman, Enrique Mallada, Wing Shing Wong
   ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2020. (Full Paper)
   Journal Version: Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2020, 4(1): 1-29.

9. [SIGMETRICS 2018] An Optimal Algorithm for Online Non-Convex Learning [PDF]
   Lin Yang, Lei Deng, Mohammad H. Hajiesmaili, Cheng Tan and Wing Shing Wong
   ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2018. (Full Paper)
   Journal Version: Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2018, 2(2): 25.

10. [SIGMETRICS 2018] An Optimal Randomized Online Algorithm for QoS Buffer Management [PDF]
    Lin Yang, Wing Shing Wong, and Mohammad H. Hajiesmaili
    ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2018. (Full Paper)
    Journal Version: Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2017, 1(2): 36.

11. [SIGMETRICS 2017] Hour-Ahead Offering Strategies in Electricity Market for Power Producers with Storage and Intermittent Supply [PDF]
    Lin Yang#, Mohammad H. Hajiesmaili#, Hanling Yi, and Minghua Chen
    ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), June 2017. (Poster Paper)

         (#: Equal Contribution or Co-first Author; *: Corresponding Author)    

Thesis

         Lin Yang, “Competitive and Regret Analysis for Online Optimization.“ [PDF]