Da Zheng - RankMe

90 papers A* 13A 10B 2Journal 55Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LLaDA2.1: Speeding Up Text Diffusion via Token Editing. CoRR Tiwei Bie, Maosong Cao, Xiang Cao, Bingsen Chen, Fuyuan Chen, Kun Chen, Lun Du, Daozhuo Feng, Haibo Feng, Mingliang Gong, Zhuocheng Gong, Yanmei Gu, Jian Guan, Kaiyuan Guan, Hongliang He, Zenan Huang, Juyong Jiang, Zhonghui Jiang, Zhenzhong Lan, Chengxi Li, Jianguo Li, Zehuan Li, Huabin Liu, Lin Liu, Guoshan Lu, Yuan Lu, Yuxin Ma, Xingyu Mou, Zhenxuan Pan, Kaida Qiu, Yuji Ren, Jianfeng Tan, Yiding Tian, Zian Wang, Lanning Wei, Tao Wu, Yipeng Xing, Wentao Ye, Liangyu Zha, Tianze Zhang, Xiaolu Zhang, Junbo Zhao, Da Zheng, Hao Zhong, Wanli Zhong, Jun Zhou, Liwang Zhu, Muzhi Zhu, Yihong Zhuang
2026	A*	`conf`	Why Do Open-Source LLMs Struggle with Data Analysis? A Systematic Empirical Study. AAAI Yuqi Zhu, Yi Zhong, Jintian Zhang, Ziheng Zhang, Shuofei Qiao, Yujie Luo, Lun Du, Da Zheng, Ningyu Zhang, Huajun Chen
2025	J	`jnl`	AutoMind: Adaptive Knowledgeable Agent for Automated Data Science. CoRR Yixin Ou, Yujie Luo, Jingsheng Zheng, Lanning Wei, Shuofei Qiao, Jintian Zhang, Da Zheng, Huajun Chen, Ningyu Zhang
2025	J	`jnl`	EvolProver: Advancing Automated Theorem Proving by Evolving Formalized Problems via Symmetry and Difficulty. CoRR Yuchen Tian, Ruiyuan Huang, Xuanwu Wang, Jing Ma, Zengfeng Huang, Ziyang Luo, Hongzhan Lin, Da Zheng, Lun Du
2025	J	`jnl`	Executable Knowledge Graphs for Replicating AI Research. CoRR Yujie Luo, Zhuoyun Yu, Xuehai Wang, Yuqi Zhu, Ningyu Zhang, Lanning Wei, Lun Du, Da Zheng, Huajun Chen
2025	J	`jnl`	InnoGym: Benchmarking the Innovation Potential of AI Agents. CoRR Jintian Zhang, Kewei Xu, Jingsheng Zheng, Zhuoyun Yu, Yuqi Zhu, Yujie Luo, Lanning Wei, Shuofei Qiao, Lun Du, Da Zheng, Shumin Deng, Huajun Chen, Ningyu Zhang
2025	J	`jnl`	Knowledge Augmented Complex Problem Solving with Large Language Models: A Survey. CoRR Da Zheng, Lun Du, Junwei Su, Yuchen Tian, Yuqi Zhu, Jintian Zhang, Lanning Wei, Ningyu Zhang, Huajun Chen
2025	J	`jnl`	LLaDA-MoE: A Sparse MoE Diffusion Language Model. CoRR Fengqi Zhu, Zebin You, Yipeng Xing, Zenan Huang, Lin Liu, Yihong Zhuang, Guoshan Lu, Kangyu Wang, Xudong Wang, Lanning Wei, Hongrui Guo, Jiaqi Hu, Wentao Ye, Tieyuan Chen, Chenchen Li, Chengfu Tang, Haibo Feng, Jun Hu, Jun Zhou, Xiaolu Zhang, Zhenzhong Lan, Junbo Zhao, Da Zheng, Chongxuan Li, Jianguo Li, Ji-Rong Wen
2025	J	`jnl`	LLaDA2.0: Scaling Up Diffusion Language Models to 100B. CoRR Tiwei Bie, Maosong Cao, Kun Chen, Lun Du, Mingliang Gong, Zhuochen Gong, Yanmei Gu, Jiaqi Hu, Zenan Huang, Zhenzhong Lan, Chengxi Li, Chongxuan Li, Jianguo Li, Zehuan Li, Huabin Liu, Lin Liu, Guoshan Lu, Xiaocheng Lu, Yuxin Ma, Jianfeng Tan, Lanning Wei, Ji-Rong Wen, Yipeng Xing, Xiaolu Zhang, Junbo Zhao, Da Zheng, Jun Zhou, Junlin Zhou, Zhanchao Zhou, Liwang Zhu, Yihong Zhuang
2025	A*	`conf`	LightThinker: Thinking Step-by-Step Compression. EMNLP Jintian Zhang, Yuqi Zhu, Mengshu Sun, Yujie Luo, Shuofei Qiao, Lun Du, Da Zheng, Huajun Chen, Ningyu Zhang
2025	J	`jnl`	LightThinker: Thinking Step-by-Step Compression. CoRR Jintian Zhang, Yuqi Zhu, Mengshu Sun, Yujie Luo, Shuofei Qiao, Lun Du, Da Zheng, Huajun Chen, Ningyu Zhang
2025	—	`conf`	OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System. WWW (Companion Volume) Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, Haofen Wang, Huajun Chen
2025	J	`jnl`	Reflective Paper-to-Code Reproduction Enabled by Fine-Grained Verification. CoRR Mingyang Zhou, Quanming Yao, Lun Du, Lanning Wei, Da Zheng
2025	—	`conf`	Retrieval-Augmented Language Models are Mimetic Theorem Provers. EMNLP (Findings) Wenjie Yang, Ruiyuan Huang, Jiaxing Guo, Zicheng Lyu, Tongshan Xu, Shengzhong Zhang, Lun Du, Da Zheng, Zengfeng Huang
2025	J	`jnl`	Right Is Not Enough: The Pitfalls of Outcome Supervision in Training LLMs for Math Reasoning. CoRR Jiaxing Guo, Wenjie Yang, Shengzhong Zhang, Tongshan Xu, Lun Du, Da Zheng, Zengfeng Huang
2025	J	`jnl`	Why Do Open-Source LLMs Struggle with Data Analysis? A Systematic Empirical Study. CoRR Yuqi Zhu, Yi Zhong, Jintian Zhang, Ziheng Zhang, Shuofei Qiao, Yujie Luo, Lun Du, Da Zheng, Huajun Chen, Ningyu Zhang
2025	J	`jnl`	dInfer: An Efficient Inference Framework for Diffusion Language Models. CoRR Yuxin Ma, Lun Du, Lanning Wei, Kun Chen, Qian Xu, Kangyu Wang, Guofeng Feng, Guoshan Lu, Lin Liu, Xiaojing Qi, Xinyuan Zhang, Zhen Tao, Haibo Feng, Ziyun Jiang, Ying Xu, Zenan Huang, Yihong Zhuang, Haokai Xu, Jiaqi Hu, Zhenzhong Lan, Junbo Zhao, Jianguo Li, Da Zheng
2024	A*	`conf`	GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. KDD Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis
2024	J	`jnl`	GraphStorm: all-in-one graph machine learning framework for industry applications. CoRR Da Zheng, Xiang Song, Qi Zhu, Jiani Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis
2024	—	`conf`	Hector: An Efficient Programming and Compilation Framework for Implementing Relational Graph Neural Networks in GPU Architectures. ASPLOS (3) Kun Wu, Mert Hidayetoglu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-Mei Hwu
2024	J	`jnl`	Hierarchical Compression of Text-Rich Graphs via Large Language Models. CoRR Shichang Zhang, Da Zheng, Jiani Zhang, Qi Zhu, Xiang Song, Soji Adeshina, Christos Faloutsos, George Karypis, Yizhou Sun
2024	A*	`conf`	NetInfoF Framework: Measuring and Exploiting Network Usable Information. ICLR Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos
2024	J	`jnl`	NetInfoF Framework: Measuring and Exploiting Network Usable Information. CoRR Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos
2024	J	`jnl`	OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System. CoRR Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, Haofen Wang, Huajun Chen
2024	J	`jnl`	Parameter-Efficient Tuning Large Language Models for Graph Representation Learning. CoRR Qi Zhu, Da Zheng, Xiang Song, Shichang Zhang, Bowen Jin, Yizhou Sun, George Karypis
2024	—	`conf`	RAP: Resource-aware Automated GPU Sharing for Multi-GPU Recommendation Model Training and Input Preprocessing. ASPLOS (2) Zheng Wang, Yuke Wang, Jiaqi Deng, Da Zheng, Ang Li, Yufei Ding
2024	A	`conf`	Revisit Orthogonality in Graph-Regularized MLPs. CIKM Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu
2024	J	`jnl`	TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting. IEEE Trans. Neural Networks Learn. Syst. Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis
2023	B	`conf`	DSP: Efficient GNN Training with Multiple GPUs. PPoPP Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis
2023	A	`conf`	DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. SC Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna
2023	J	`jnl`	DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. CoRR Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna
2023	A*	`conf`	Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. KDD Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi
2023	J	`jnl`	Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. CoRR Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi
2023	A*	`conf`	GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes. KDD Jian Zhang, Da Zheng, Xiang Song, Theodore Vasiloudis, Israt Nisa, Jim Lu
2023	—	`conf`	Optimizing Irregular Dense Operators of Heterogeneous GNN Models on GPU. IPDPS Workshops Israt Nisa, Minjie Wang, Da Zheng, Qiang Fu, Ümit V. Çatalyürek, George Karypis
2023	J	`jnl`	OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization. CoRR Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu
2023	J	`jnl`	PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks. CoRR Kun Wu, Mert Hidayetoglu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-mei W. Hwu
2023	A*	`conf`	PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction. WWW Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun
2023	J	`jnl`	PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction. CoRR Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun
2023	A	`conf`	TANGO: re-thinking quantization for graph neural network training on GPUs. SC Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu
2023	J	`jnl`	Tango: rethinking quantization for graph neural network training on GPUs. CoRR Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu
2023	—	`conf`	Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. ECML/PKDD (3) Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis
2023	J	`jnl`	Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. CoRR Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis
2022	A*	`conf`	Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs. KDD Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis
2022	J	`jnl`	Efficient and effective training of language and graph neural network models. CoRR Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis
2022	J	`jnl`	From Local to Global: Spectral-Inspired Graph Neural Networks. CoRR Ningyuan Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman
2022	A*	`conf`	Nimble GNN Embedding with Tensor-Train Decomposition. KDD Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc
2022	J	`jnl`	Nimble GNN Embedding with Tensor-Train Decomposition. CoRR Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc
2022	J	`jnl`	TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs. CoRR Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis
2022	J	`jnl`	TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs. Proc. VLDB Endow. Hongkuan Zhou, Da Zheng, Israt Nisa, Vassilis N. Ioannidis, Xiang Song, George Karypis
2021	J	`jnl`	Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs. CoRR Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, Qidong Su, Minjie Wang, Chao Ma, George Karypis
2021	J	`jnl`	Dr. Top-k: Delegate-Centric Top-k on GPUs. CoRR Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
2021	A	`conf`	Dr. Top-k: delegate-centric Top-k on GPUs. SC Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
2021	A*	`conf`	Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs. KDD Jialin Dong, Da Zheng, Lin F. Yang, George Karypis
2021	J	`jnl`	Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs. CoRR Jialin Dong, Da Zheng, Lin F. Yang, George Karypis
2021	A	`conf`	Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks. SDM Balasubramaniam Srinivasan, Da Zheng, George Karypis
2021	J	`jnl`	Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks. CoRR Balasubramaniam Srinivasan, Da Zheng, George Karypis
2021	A	`conf`	Scalable Graph Neural Networks with Deep Graph Library. WSDM Da Zheng, Minjie Wang, Quan Gan, Xiang Song, Zheng Zhang, George Karypis
2021	—	`conf`	Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs. IEEE BigData Saurav Manchanda, Da Zheng, George Karypis
2021	J	`jnl`	Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs. CoRR Saurav Manchanda, Da Zheng, George Karypis
2021	J	`jnl`	TraverseNet: Unifying Space and Time in Message Passing. CoRR Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis
2020	A*	`conf`	Collective Multi-type Entity Alignment Between Knowledge Graphs. WWW Qi Zhu, Hao Wei, Bunyamin Sisman, Da Zheng, Christos Faloutsos, Xin Luna Dong, Jiawei Han
2020	A*	`conf`	DGL-KE: Training Knowledge Graph Embeddings at Scale. SIGIR Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis
2020	J	`jnl`	DGL-KE: Training Knowledge Graph Embeddings at Scale. CoRR Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis
2020	—	`conf`	DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. IA3@SC Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis
2020	J	`jnl`	DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis
2020	J	`jnl`	FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems. CoRR Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
2020	A	`conf`	FeatGraph: a flexible and efficient backend for graph neural network systems. SC Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
2020	J	`jnl`	Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing. CoRR Vassilis N. Ioannidis, Da Zheng, George Karypis
2020	—	`conf`	Learning Graph Neural Networks with Deep Graph Library. WWW (Companion Volume) Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis
2020	J	`jnl`	PanRep: Universal node embeddings for heterogeneous graphs. CoRR Vassilis N. Ioannidis, Da Zheng, George Karypis
2020	A*	`conf`	Scalable Graph Neural Networks with Deep Graph Library. KDD Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis
2019	J	`jnl`	Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. CoRR Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, Zheng Zhang
2019	J	`jnl`	Graphyti: A Semi-External Memory Graph Library for FlashGraph. CoRR Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
2019	J	`jnl`	clusterNOR: A NUMA-Optimized Clustering Framework. CoRR Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
2018	J	`jnl`	Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers. CoRR Hang Liu, Yufei Ding, Da Zheng, Seung Woo Son, Da Yan
2018	B	`conf`	FlashR: parallelize and scale R for machine learning using SSDs. PPoPP Da Zheng, Disa Mhembere, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
2017	J	`jnl`	Semi-External Memory Sparse Matrix Multiplication for Billion-Node Graphs. IEEE Trans. Parallel Distributed Syst. Da Zheng, Disa Mhembere, Vince Lyzinski, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
2017	A	`conf`	knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library. HPDC Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
2016	J	`jnl`	An SSD-based eigensolver for spectral analysis on billion-node graphs. CoRR Da Zheng, Randal C. Burns, Joshua T. Vogelstein, Carey E. Priebe, Alexander S. Szalay
2016	J	`jnl`	FlashMatrix: Parallel, Scalable Data Analysis with Generalized Matrix Operations using Commodity SSDs. CoRR Da Zheng, Disa Mhembere, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
2016	J	`jnl`	NUMA-optimized In-memory and Semi-external-memory Parameterized Clustering. CoRR Disa Mhembere, Da Zheng, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
2016	J	`jnl`	Semi-External Memory Sparse Matrix Multiplication on Billion-node Graphs in a Multicore Architecture. CoRR Da Zheng, Disa Mhembere, Vince Lyzinski, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns
2015	A	`conf`	FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs. FAST Da Zheng, Disa Mhembere, Randal C. Burns, Joshua T. Vogelstein, Carey E. Priebe, Alexander S. Szalay
2015	J	`jnl`	Optimize Unsynchronized Garbage Collection in an SSD Array. CoRR Da Zheng, Randal C. Burns, Alexander S. Szalay
2014	J	`jnl`	Active Community Detection in Massive Graphs. CoRR Heng Wang, Da Zheng, Randal C. Burns, Carey E. Priebe
2014	J	`jnl`	FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs. CoRR Da Zheng, Disa Mhembere, Randal C. Burns, Alexander S. Szalay
2014	J	`jnl`	Hadoop in Low-Power Processors. CoRR Da Zheng, Alexander S. Szalay, Andreas Terzis
2013	A	`conf`	Toward millions of file system IOPS on low-cost, commodity hardware. SC Da Zheng, Randal C. Burns, Alexander S. Szalay
2012	—	`conf`	A Parallel Page Cache: IOPS and Caching for Multicore Systems. HotStorage Da Zheng, Randal C. Burns, Alexander S. Szalay