Experiences

Education Experiences

• Master of Science (Computer Science and Technology)
  🏫 Fudan University, Sep. 2022 - Jun. 2025
• Bachelor of Science (Elite Program in Computer Science and Technology)
  🏫 Fudan University, Sep. 2018 - Jun. 2022

Industry Experiences

• Platform Engineering Intern
  ☁️ Alibaba Cloud (China), Jun. 2021 - Sep. 2021
  
  • Explored the high-performance packet processing technique XDP for efficient network packet filtering.
  • Addressed real-world needs and further combined DPDK with XDP to handle network packets more intelligently.
  • Wrote and integrated technical documents to facilitate clear communications across teams

Research Experiences

• Compress Lineage Artifacts in Lineage-Enabled DBMS [In progress]
  🌐 Remote (Columbia University), Jun. 2024 - Present
  Collaborated with Prof. Eugene Wu.
  • Explored the properties of various lineage artifacts across different input data, physical operators, and queries.
  • Designed a suitable compression strategy for each lineage artifact and integrated it into a lineage-enabled DBMS.
  • Evaluated on TPC-H benchmarks, achieving a ~6x space saving with an 18% additional time overhead.

• Improve Tabular Data Quality for ML Models [2 submissions, 1 shepherd accepted by SIGMOD 2025]
  🏢 Shenzhen Institute of Computing Sciences, Dec. 2023 - Oct. 2024
  Collaborated with Prof. Wenfei Fan and Dr. Weilong Ren
  • Aimed to repair and enhance tabular data to improve ML classification performance across various metrics.
  • Identified key factors in tabular data impacting ML models and applied refined-scope data cleaning.
  • Designed iterative frameworks to address intractable cleaning problems and outperformed the SOTA by 30%.

• Akane: Perplexity-Guided Time Series Data Cleaning [SIGMOD 2024]
  🏫 Fudan University, Apr. 2023 - Feb. 2024
  Collaborated with Prof. X. Sean Wang, Prof. Zhenying He and Prof. Peng Wang
  • Innovatively analogized recurrent patterns in the time series data to the word combinations in the textual data.
  • Re-formalized the time series data cleaning problem to minimize the perplexity of the time series.
  • Proposed a four-phase framework Akane and several advanced solutions to handle the NP-Hard cleaning problem.
  • Compared with 11 baselines across 12 real-world datasets with real errors and achieved SOTA performance.

• RpDelta: Supporting UCR-Suite on Multi-Versioning Time Series Data
  🏫 Fudan University, Mar. 2022 - Jan. 2023
  Collaborated with Prof. X. Sean Wang and Prof. Zhenying He
  • Focused on the issues of multi-versioning time series data arising from various cleaning algorithms.
  • Designed an effective storage strategy RpDelta and saved over 5x space for multi-versioning time series data.
  • Transplanted the subsequence matching algorithm UCR-Suite onto RpDelta and doubled its speed cumulatively.

Contest Experiences

• "Loongson Cup" National Student Computer System Capability Challenge [Second Prize]
  🏫 Fudan University, Jun. 2020 - Aug. 2020
  Collaborated with Prof. Liang Zhang and Dr. Chen Chen
  • Implemented an experimental dual-issued MIPS CPU & a five-stage pipelined MIPS CPU using System Verilog.
  • Incorporated memory hierarchy design for optimization (~30x faster) with great compatibility.
  • Burned the implemented CPU into an FPGA and initiated PMON on it.
  • Served as the leader of a four-person team, orchestrating project phases and refining task assignments.