About me
Yiyang Lu
Ph.D. Candidate in Computer Science, William&Mary.
Co-Advisors: Prof. Jie Ren, Prof. Evgenia Smirni
Research Interest: HPC system operation, Reliability, GPUs, Autonomous Vehicle Safety, Fault Correction, Machine Learning, Anomaly Detection, Time Series Analysis, Data Analysis
Education
- University of Electronic Science and Technology of China, Bachelor
2016 - 2020 - William & Mary, Ph.D.
2021- Now
Publications
Dataset and Benchmark for Learning on Large-Scale HPC Infrastructure (SUBMITTED)
Yiyang Lu , Woong Shin, Ahmad Maroof Karimi, Feiyi Wang, Evgenia Smirni, Jie Ren.
Unveiling HPC Secrets: A Fundamental ML Model for Telemetry Analysis and Beyond (SUBMITTED)
Yiyang Lu , Jie Ren, Evgenia Smirni.
Strategic Resilience Evaluation of Neural Networks within Autonomous Vehicle Software
Anna Schmedding, Philip Schowitz, Xugui Zhou, Yiyang Lu, Lishan Yang, Homa Alemzadeh and Evgenia Smirni.
SAFECOMP2024: 43rd International Conference on Computer Safety, Reliability and Security. SAFECOMP 2024
Dataset for Investigating Anomalies in Compute Clusters
Diana McSpadden, Yasir Alanazi, Bryan Hess, Laura Hild, Mark Jones, Yiyang Lu, Ahmed Mohammed, Wesley Moore, Jie Ren, Malachi Schram, Evgenia Smirni
Investigating Anomalies in Compute Clusters: An Unsupervised Learning Approach
Yiyang Lu , Jie Ren, Yasir Alanazi, Ahmed Mohammed, Diana McSpadden, Laura Hild, Mark Jones, Wesley Moore, Malachi Schram, Bryan Hess, Evgenia Smirni.
SC '23 Research Posters: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, November 2023. SC 23
Measuring children’s eating behavior with a wearable device
Shengjie Bi, Yiyang Lu , Nicole Tobias, Ella Ryan, Travis Masterson, Sougata Sen, Ryan Halter, Jacob Sorber, Diane Gilbert-Diamond, and David Kotz.
Proceedings of the IEEE International Conference on Healthcare Informatics, December 2020. ICHI 2020
Research Experience
- Oak Ridge National Laboratory (ORNL): Graduate Research Intern
2025 -
William & Mary: Research assistant
2023 - Now- HPC telemetry analysis
- Analyzed a large amount of real-world production telemetry data from OLCF, JLab clusters.
- Proposed a predictive framework that adapts to diverse tasks, including anomaly detection and workload prediction.
- Developed a method to reveal telemetry relationships, offering a holistic view of system behavior.
- Analyzed the change of telemetry relationships relative to workload changes.
- Resilience Evaluation of Autonomous Vehicle Models
- Performed strategic resilience evaluation on an L4 autonomous driving system.
- Examined the effectiveness of mitigation on critical faults in autonomous vehicles.
- HPC telemetry analysis
-
Li Xiaojian's Group in SIAT CAS: Research assistant for "Brain-Computer Interface"
2020 - David Kotz's Group in Dartmouth College: Research assistant for "Wearable Technology"
2019
Industry Experience
- ByteDance: Research & Development Intern for "Network Traffic Analysis"
2021
Awards
- William&Mary Summer Graduate Research Fellowship (2021)
- UESTC Outstanding Student Scholarship (2016-2017, 2017-2018)
Professional Service
- Sigmetrics'25: Special Interest Group on Measurement and Evaluation 2025 (subreviewer)
- Sigmetrics'24: Special Interest Group on Measurement and Evaluation 2024 (subreviewer)
- MSN 2022: The 18th International Conference on Mobility, Sensing and Networking (subreviewer)
Teaching Assistant
- CSCI241 Data Structures (Fall 2022)
- CSCI534 Nework Systems and Design (Spring 2022)
- CSCI243 Discrete Structures of CSCI (Fall 2021)
Tools
- Programming Languages: Python, Embeded C, Java, Go
- Data analysis: PyTorch, NumPy, Pandas, Pyspark, Tsfresh, Librosa, Optuna, Matplotlib, Plotly, PyG, Networkx
- Simulators: Carla, Apollo
- Databases: Spark, Hive, Elasticsearch, ClickHouse