Qinghua Liu

PhD Student at OSU CSE

my photo

Location: Columbus, USA

Email: liu.11085@osu.edu

Google Scholar: Link

Linkedin: Link

Twitter: @qhliu26

Blog: Zhihu

About Me

I'm a third-year PhD student advised by Prof. John Paparrizos at The Ohio State University.
I work on time-series analysis, anomaly detection, and AutoML, with the goal of building intelligent systems that can reliably analyze complex temporal data at scale. My research is organized around three interconnected pillars:

📝 Education

TJU Aug 2023 - Present
PhD Student in Computer Science and Engineering,
The Ohio State University (OSU), USA
TJU Sept. 2018 - Jun. 2022
B.Eng. in Electronic Information Engineering
Qiushi Honors College, Tianjin University (TJU), China

📖 Publication

Chameleon 📄 Chameleon: Towards A Reliable and Efficient Automated System for Time-Series Anomaly Detection
✍️ Qinghua Liu, Mingyi Huang, John Paparrizos
[Paper] [Code]
Under Review
HYDRA 📄 HYDRA: A Multi-Level HierarchY-Driven Approach for Robust Anomaly Detection in Time Series
✍️ Mingyi Huang, Qinghua Liu, Paul Boniol, John Paparrizos
[Paper] [Code]
SIGMOD 2026
MLLM4TS 📄 MLLM4TS: Leveraging Vision and Multimodal Language Models for General Time-Series Analysis
✍️ Qinghua Liu*, Sam Heshmati*, Zheda Mai*, Zubin Abraham, John Paparrizos, Liu Ren
[Paper]
Preprint
TSB-AutoAD 📄 TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection
✍️ Qinghua Liu, Seunghak Lee, John Paparrizos
[Paper] [Demo] [Code]
VLDB 2025
TSB-AD 📄 The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark
✍️ Qinghua Liu, John Paparrizos
[Paper] [Website] [Code]
NeurIPS 2024
TSAD survey 📄 Dive into Time-Series Anomaly Detection: A Decade Review
✍️ Paul Boniol, Qinghua Liu, Mingyi Huang, Themis Palpanas, John Paparrizos
[Paper]
Preprint
TSAD survey 📄 VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection
✍️ Paul Boniol, Ashwin K Krishna, Marine Bruel, Qinghua Liu, Mingyi Huang, Themis Palpanas, Ruey S Tsay, Aaron Elmore, Michael J Franklin, John Paparrizos
[Paper] [Code]
VLDB Journal 2025
TSAD Tutorial 📄 Time-Series Anomaly Detection: Overview and New Trends
✍️ Qinghua Liu, Paul Boniol, Themis Palpanas, John Paparrizos
[Paper] [Code]
VLDB Tutorial 2024
PIAVE flowchart 📄 PIAVE: A Pose-Invariant Audio-Visual Speaker Extraction Network
✍️ Qinghua Liu, Meng Ge, Zhizheng Wu, Haizhou Li
[Paper] [Code]
INTERSPEECH 2023
Dive into Big Model Training 📄 Dive into Big Model Training
✍️ Qinghua Liu, Yuxiang Jiang
[Paper]
Preprint
LiMuSE flowchart 📄 LiMuSE: Lightweight Multi-modal Speaker Extraction
✍️ Qinghua Liu*, Yating Huang*, Yunzhe Hao, Jiaming Xu, Bo Xu
[Paper] [Code] [Dataset]
IEEE SLT 2022

🕶️ Awesome List

  • awesome-time-series-analysis: A curated list of awesome time-series papers, benchmarks, datasets, tutorials. [Link]
  • Dive-into-Big-Model-Training: A continuously updated paper list of big model training. [Link]

  • 💼 Experience

    Bosch Bosch Research
    May. 2025 - Aug. 2025
    Research Intern (Supervisor: Sam Heshmati)
    LLM-based time-series analysis and time-series foundation model
    CUHKSZ The Chinese University of Hong Kong, Shenzhen
    Jul. 2022 - Jun. 2023
    Research Assistant (Advisor: Prof. Haizhou Li)
    Audio-visual SSL and speaker extraction
    JDT JDT, JD.com Inc
    Mar. 2022 - Jul. 2022
    Algorithm Engineer Intern (Supervisor: Cong Guo)
    Machine learning platform and training parallelism
    CASIA Institute of Automation, Chinese Academy of Sciences
    Jun. 2021 - Jan. 2022
    Research Intern (Advisor: Prof. Jiaming Xu)
    Lightweight multi-modal auditory frontend model computation and optimization

    🏆 Academic Awards

    🏄 Extra Curricular Activaties

    SA Tianjin University Student Ambassador Association
    Dec. 2020 - Feb. 2022
    President
    Attend international exchange events and organize foreign affairs reception