Source Viewer 3D (sv3D) - A Framework for Software Visualization. - Jonathan I. Maletic; Andrian Marcus; Louis Feng (ICSE, 2003)

Comprehension of Software Analysis Data Using 3D Visualization. - Andrian Marcus; Louis Feng; Jonathan I. Maletic (IWPC, 2003)

3D Representations for Software Visualization. - Andrian Marcus; Louis Feng; Jonathan I. Maletic (SOFTVIS, 2003)

Source Viewer 3D (sv3D): A System for Visualizing Multi Dimensional Software Analysis Data. - Andrian Marcus; Louis Feng; Jonathan I. Maletic (VISSOFT, 2003)

Physically Based Methods for Tensor Field Visualization. - Ingrid Hotz; Louis Feng; Hans Hagen; Bernd Hamann; Kenneth I. Joy; Boris Jeremic (IEEE Visualization, 2004)

Shell maps. - Serban D. Porumbescu; Brian Budge; Louis Feng; Kenneth I. Joy (ACM Trans. Graph., 2005)

Tensor Field Visualization Using a Metric Interpretation. - Ingrid Hotz; Louis Feng; Hans Hagen; Bernd Hamann; Kenneth I. Joy (Visualization and Processing of Tensor Fields, 2006)

Anisotropic Noise Samples. - Louis Feng; Ingrid Hotz; Bernd Hamann; Kenneth I. Joy (IEEE Trans. Vis. Comput. Graph., 2008)

Tensor-Fields Visualization Using a Fabric-like Texture Applied to Arbitrary Two-dimensional Surfaces. - Ingrid Hotz; Louis Feng; Bernd Hamann; Kenneth I. Joy (Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration, 2009)

Embree ray tracing kernels for CPUs and the Xeon Phi architecture. - Sven Woop; Louis Feng; Ingo Wald; Carsten Benthin (SIGGRAPH Talks, 2013)

Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. - Xiaocong Du; Bhargav Bhushanam; Jiecao Yu; Dhruv Choudhary; Tianxiang Gao; Sherman Wong; Louis Feng; Jongsoo Park; Yu Cao 001; Arun Kejariwal (ICMLA, 2021)

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. - Zhongyi Lin; Louis Feng; Ehsan K. Ardestani; Jaewon Lee; John Lundell; Changkyu Kim; Arun Kejariwal; John D. Owens (HIPC, 2022)

AutoShard: Automated Embedding Table Sharding for Recommender Systems. - Daochen Zha; Louis Feng; Bhargav Bhushanam; Dhruv Choudhary; Jade Nie; Yuandong Tian; Jay Chae; Yinbin Ma; Arun Kejariwal; Xia Hu 001 (KDD, 2022)

DreamShard: Generalizable Embedding Table Placement for Recommender Systems. - Daochen Zha; Louis Feng; Qiaoyu Tan; Zirui Liu 001; Kwei-Herng Lai; Bhargav Bhushanam; Yuandong Tian; Arun Kejariwal; Xia Hu 001 (NeurIPS, 2022)

Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks. - Mingyu Liang; Wenyin Fu; Louis Feng; Zhongyi Lin; Pavani Panakanti; Shengbao Zheng; Srinivas Sridharan 002; Christina Delimitrou (ISCA, 2023)

Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. - Daochen Zha; Louis Feng; Liang Luo; Bhargav Bhushanam; Zirui Liu 001; Yusuo Hu; Jade Nie; Yuzhen Huang; Yuandong Tian; Arun Kejariwal; Xia Hu 001 (MLSys, 2023)

Mystique: Accurate and Scalable Production AI Benchmarks Generation. - Mingyu Liang; Wenyin Fu; Louis Feng; Zhongyi Lin; Pavani Panakanti; Srinivas Sridharan 002; Christina Delimitrou (CoRR, 2023)

Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces. - Srinivas Sridharan 002; Taekyung Heo; Louis Feng; Zhaodong Wang; Matt Bergeron; Wenyin Fu; Shengbao Zheng; Brian Coutinho; Saeed Rashidi; Changhai Man; Tushar Krishna (CoRR, 2023)

MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations. - Shaochen (Henry) Zhong; Yifan Lu; Lize Shao; Bhargav Bhushanam; Xiaocong Du; Yixin Wan; Yucheng Shi; Daochen Zha; Yiwei Wang; Ninghao Liu; Kaixiong Zhou; Shuai Xu; et al. (ICLR, 2025)

Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms. - Zhongyi Lin; Ning Sun; Pallab Bhattacharya; Xizhou Feng; Louis Feng; John D. Owens (IEEE Trans. Parallel Distributed Syst., 2025)

Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training. - Mingyu Liang; Hiwot Tadese Kassa; Wenyin Fu; Brian Coutinho; Louis Feng; Christina Delimitrou (CoRR, 2025)