yupinglu89@gmail.com | YupingLu | @YupingLu | yupinglu | Dissertation
Education
University of Tennessee, Knoxville
- Research Interests: Machine Learning | Graph Algorithms | Bioinformatics
- PhD in Computer Science (August 2019) | GPA: 3.91
- Advisor: Dr. Michael A. Langston
Nanjing Agricultural University
- BEng in Computer Science (May 2011) | GPA: 3.64
- Advisor: Dr. Huanliang Xu
Technical Skills
- Programming languages: C/C++, Python, SQL, openCypher, R, PHP, HTML+CSS+Javascript
- Tools: PyTorch, LLM, PyG, DGL, Jupyter, NumPy, Pandas, Conda, Git, Redis, LaTeX
- Cloud Computing: AWS, GCP, Docker, Kubernetes
- HPC experience: ORNL CADES, LBNL NERSC, OpenMPI
Honors
- Klaus Halbach Award, ALS, Berkeley Lab (2021)
- GSS Travel Award, University of Tennessee, Knoxville (2018)
- Department Excellence Award, University of Tennessee, Knoxville (2013)
- Outstanding Graduate and Several Scholarships, Nanjing Agricultural University (2007-2011)
Ages ago, in another city, on another bus, I sat so at the windows, looking outward, investing for each flying face which trapped my brief attention some life, some destiny, in which I played a part.
Experience
Walmart Global Tech - Bentonville, AR [03/2024 ~ present]
Senior Data Scientist - [06/2025 ~ present]
Senior Data Scientist - [06/2025 ~ present]
- Implemented a framework for feature generation on large-scale data.
- Improved category forecasting with a tree-based model.
- Published a paper on estimating treatment effects when a control group is unobservable.
- Implemented a parallel framework for daily forecasting.
- Created end-to-end data pipelines for daily forecasts.
- Developed a web app to visualize daily forecast results.
Machine Learning Engineer at Katana Graph - Lakewood, CO [10/2021 ~ 06/2023]
- Manager: Dr. Bo Wu
- Implemented Graph Neural Network (GNN) algorithms and infrastructure
- Developed a distributed full-neighbor subgraph sampler for use with PyG and DGL.
- Created end-to-end ML pipelines on Katana's distributed Graph AI platform.
- Updated the PyTorch Conda package to work with the Katana environment.
- Built a UI prototype for Katana's Graph AI platform.
- Tested Katana's AI libraries and filed bug reports for fixes.
Postdoctoral Scholar at Berkeley Lab - Berkeley, CA [09/2019 ~ 09/2021]
- Supervisor: Dr. Simon C. Leemann
- Improved algorithms for Lattice Optimization using Deep Learning.
- Achieved orders-of-magnitude speedups on HPC clusters.
Oak Ridge National Laboratory - Oak Ridge, TN [10/2017 ~ 08/2019]
Graduate Research Assistant, the Atmospheric Radiation Measurement (ARM) Data Center - [10/2017 ~ 08/2019]
Graduate Research Assistant, the Atmospheric Radiation Measurement (ARM) Data Center - [10/2017 ~ 08/2019]
- Mentor: Dr. Jitendra Kumar
- Classified radar data using convolutional neural networks.
- Detected outliers in streaming time-series radar data.
- Mentor: Dr. George Ostrouchov
- Developed pbdR tools for singularity container.
- Implemented an R package pbdADIOS to connect R with ADIOS.
University of Tennessee, Knoxville - Knoxville, TN [08/2013 ~ 10/2017]
Graduate Research Assistant, the Office of Information Technology - [07/2014 ~ 10/2017]
Graduate Research Assistant, the Office of Information Technology - [07/2014 ~ 10/2017]
- Supervisor: Mr. John B. Rose
- University web server configuration and optimization.
- Google Search Appliance administration and implementation.
Publications
Conference Papers
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Time Series Treatment Effects Analysis with Always-Missing Controls
Juan Shu, Qiyu Han, George Chen, Xihao Cao, Kangming Luo, Dan Pallotta, Shivam Agrawal, Yuping Lu, Xiaoyu Zhang, Jawad Mansoor, Jyoti Anand
PAKDD 2025 (2025) | Paper | Web -
Enhancing the MOGA Optimization Process at ALS-U with Machine Learning
Yuping Lu, Simon C. Leemann, Changchun Sun, Michael P. Ehrlichman, Thorsten Hellert, Hiroshi Nishimura, Marco Venturini
IPAC 21 (2021) | Paper | Web -
Clique Selection and its Effect on Paraclique Enrichment: An Experimental Study
Yuping Lu, Charles A. Phillips, Elissa J. Chesler, Michael A. Langston
Proceedings of the 12th International Conference on Bioinformatics and Computational Biology (2020) | Paper | Web -
Detecting Outliers in Streaming Time Series Data from ARM Distributed Sensors
Yuping Lu, Jitendra Kumar, Nathan Collier, Bhargavi Krishna, Michael A. Langston
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops (ICDMW 2018) | Paper | Web
Journal Papers
-
Demonstration of Machine Learning-enhanced Multi-objective Optimization of Ultrahigh-brightness Lattices for 4th-generation Synchrotron Light Sources
Yuping Lu, Simon C. Leemann, Changchun Sun, Michael P. Ehrlichman, Hiroshi Nishimura, Marco Venturini, Thorsten Hellert
Nuclear Inst. and Methods in Physics Research, A — (2023): 168192 doi:10.1016/j.nima.2023.168192 | Paper | Web -
Biclique: an R Package for Maximal Biclique Enumeration in Bipartite Graphs
Yuping Lu, Charles A. Phillips, Michael A. Langston
BMC Research Notes — 13, 88 (2020) doi:10.1186/s13104-020-04955-0 | Paper | Web -
A Robustness Metric for Biological Data Clustering Algorithms
Yuping Lu, Charles A. Phillips, Michael A. Langston
BMC Bioinformatics — 20, 503 (2019) doi:10.1186/s12859-019-3089-6 | Paper | Web -
Digital Gene Expression Profiling of the Phytophthora Sojae Transcriptome
Wenwu Ye, Xiaoli Wang, Kai Tao, Yuping Lu, Tingting Dai, Suomeng Dong, Daolong Dou, Mark Gijzen, Yuanchao Wang
Molecular Plant-Microbe Interactions — 24(12):1530–1539, December 2011 | Paper | Web
Posters & Short Papers
-
Enhancing the MOGA Optimization Process at ALS-U with Machine Learning
Yuping Lu, Simon C. Leemann, Changchun Sun, Michael P. Ehrlichman, Thorsten Hellert, Hiroshi Nishimura, Marco Venturini
IPAC 21 — Campinas, Brazil, May 24, 2021 | Poster -
Improving Multi-objective Genetic Algorithm for Lattice Optimization with Machine Learning
Yuping Lu, Changchun Sun, and Simon C. Leemann
ALS User Meeting 2020 — Berkeley, California, August 25, 2020 | Poster -
Beam Based Optimization and Machine Learning for Synchrotrons
Charles Nathan Melton, Yuping Lu, Shuai Liu, Hiroshi Nishimura, Matthew Marcus, Changchun Sun, Alexander Hexemer, Simon C. Leemann
ALS User Meeting 2019 — Berkeley, California, October 1, 2019 | Poster -
Convolutional Neural Networks for Hydrometeor Classification Using Dual Polarization Doppler Radars
Yuping Lu, Jitendra Kumar
2019 ARM/ASR PI Meeting — Rockville, MD, June 11, 2019 | Poster -
Enrichment vs Robustness: A Comparison of Transcriptomic Data Clustering Metrics
Yuping Lu, Charles A Phillips, Michael A Langston
BMC Bioinformatics — 17(Suppl 10):P10, August 2016 | Paper | Web
Talks
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Deep Convolutional Neural Networks for Hydrometeor Classification using Dual Polarization Doppler Radars
2019 ARM/ASR PI Meeting, Rockville, MD, June 10, 2019 | Slides -
A Robustness Metric for Biological Data Clustering Algorithms
ISBRA 2018, Beijing, China, June 10, 2018 | Slides