Yuanli Wang (王远立)

I'm a Ph.D. student at Complex Analytics & Scalable Processing (CASP) Research Lab at Boston University, and I am working with Vasiliki (Vasia) Kalavri.

My research interests are broadly in computer system, database and network. My current works are focusing on building self-managed stream processing system.

Previously, I obtained my master's degree from University of Minnesota.

Email: yuanliw at bu dot edu  /  CV  /  Twitter  /  Github  /  Google Scholar

profile photo

Publications
CAPSys: Contention-aware task placement for data stream processing
Yuanli Wang*, Lei Huang*, Zikun Wang, Vasiliki Kalavri, Ibrahim Matta.
EuroSys 2025 (To appear)
The Non-Expert Tax: Quantifying the cost of auto-scaling in Cloud-based data stream analytics
Yuanli Wang, Baiqing Lyu, Vasiliki Kalavri
BiDEDE’22, co-located with SIGMOD’22 [slides] [poster]
A New Benchmark Harness for Systematic and Robust Evaluation of Streaming State Stores
Esmail Asyabi, Yuanli Wang, John Liagouris, Vasiliki Kalavri, Azer Bestavros
EuroSys 2022 [code] [slides]
HACCS: Heterogeneity-Aware Clustered Client Selection for Accelerated Federated Learning
Joel Wolfrath, Nikhil Sreekumar, Dhruv Kumar, Yuanli Wang, Abhishek Chandra
IPDPS 2022 [code]
Accelerated Training via Device Similarity in Federated Learning
Yuanli Wang, Joel Wolfrath, Nikhil Sreekumar, Dhruv Kumar, Abhishek Chandra
EdgeSys 2021, co-located with EuroSys 2021 [talk]
Fail-slow fault tolerance needs programming support
Andrew Yoo, Yuanli Wang, Ritesh Sinha, Shuai Mu, Tianyin Xu
HotOS-XVIII [talk]
Exploiting Data Heterogeneity for Performance and Reliability in Federated Learning
Yuanli Wang, Dhruv Kumar, Abhishek Chandra
Poster in the Fifth ACM/IEEE Symposium on Edge Computing. 2020

Work Experiences
Apple

AIML - Data Processing Platform Intern | 05/2023 - 08/2023

Integrate data lineage tracking support for Flink platform.
PingCAP

Database Engineer Intern | 05/2019 - 08/2019

Worked on AutoTiKV project from scratch: use machine learning to tune database under user-specific workloads.

Invited Talks
  • Towards a cost-efficient and QoS-aware self-managed stream processing system, Meta, July.2022

  • Professional Services
  • Artifact Evaluation Committee: SIGCOMM 2021, SOSP 2021, MLSys 2023
  • Program Committee: EuroSys 2022 (Shadow PC) , IMC 2022 (Shadow PC)
  • Reviewer: ICDCS 2024 (sub-reviewer)

  • Teaching
  • Teaching Fellow, CAS CS 210 Computer Systems, Boston University, Fall 2022
  • Teaching Assistant, CSCI 5105 Distributed Systems, University of Minnesota, Spring 2021
  • Teaching Assistant, CSCI 5103 Operating Systems, University of Minnesota, Fall 2020

  • Honors and Awards
  • Selected entrant for 2019 Google Machine Learning Winter Camp
  • Rank 16/183 in 2018 ACM-ICPC North Central North America Regional Contest
  • Bronze Medal, 2015 China Collegiate Programming Contest

  • Personal
    My reading notes of system papers.
    I love traveling and collecting old computer hardware. Here are the albums of my photography and collections.


    Using template from jonbarron.