I am an Associate Professor in the Department of Computer Science and Software Engineering at the Auburn University. Prior to that, I received my Ph.D. degree in the College of Computing at the Georgia Institute of Technology.

My current research interests lie in several reasearch areas, including Trustworthy Machine Learning, Parallel, Distributed, and Federated Learning, Natural Language Processing, Graph Machine Learning. Our lab has built close collaborative relationships with Microsoft, Amazon, and Sony Research. Our research contributions have been published in top venues of machine learning (ICML, NeurIPS), artificial intelligence (AAAI, IJCAI, TIST), natural language processing (ACL, EMNLP), data mining (KDD, ICDM, SDM, TKDD, DMKD, KAIS), high performance computing (HPDC, SC, TPDS), database systems (VLDB, ICDE, CIKM, TKDE, VLDBJ), Web (WWW, TWEB), and networking (JSAC, TOIT).

Currently, there are several fully funded Ph.D. positions available in deep learning, trustworthy machine learning, federated learning, or natural language processing. In addition, our industrial collaborators are hiring multiple summer interns in the above research fields. Interested students are encouraged to email me your CVs and transcripts.

News

• Jan 2025 One paper accepted by ICC 2025.
• Oct 2024 One paper accepted by TSAS.
• Oct 2024 Invited talk at the Alabama Higher Education AI Exchange.
• Oct 2024 TPC for AISTATS 2025.
• Sep 2024 One paper accepted by EMNLP 2024.
• Sep 2024 One paper accepted by WiOpt 2024.
• Aug 2024 One paper accepted by TIST.
• Aug 2024 TPC for ICLR 2025.
• Jul 2024 Two papers accepted by CIKM 2024.
• Jun 2024 SPC for AAAI 2025.
• Jun 2024 One paper accepted by EDBT 2025.
• May 2024 Received ICDE Best Demo Runner Up Award.
• May 2024 One paper accepted by ICML 2024.
• May 2024 One paper accepted by FGCS.
• May 2024 TPC for ICDM 2024.
• Apr 2024 One paper accepted by IJCAI 2024.
• Apr 2024 TPC for NeurIPS 2024.
• Mar 2024 Received ITE Safety Project Award.
• Mar 2024 Tianshi received Outstanding Doctoral Student Award.
• Mar 2024 Two papers accepted by ICDE 2024.
• Feb 2024 Invited talk at the Florida State University.
• Dec 2023 One paper accepted by ICDE 2024.
• Dec 2023 One paper accepted by SDM 2024.
• Dec 2023 Two papers accepted by AAAI 2024.
• Dec 2023 TPC for ICML 2024 and KDD 2024.
• Dec 2023 SPC for IJCAI 2024.
• Nov 2023 One paper accepted by TKDD.
• Oct 2023 Two papers accepted by EMNLP 2023.
• Oct 2023 Invited talk at the University of Alabama at Birmingham.
• Aug 2023 TPC for ICLR 2024 and SDM 2024.
• Aug 2023 One paper accepted by GLOBECOM 2023.
• Jun 2023 SPC for AAAI 2024.
• Apr 2023 Invited to attend DARPA AI Forward meeting.
• Apr 2023 Two papers accepted by ICML 2023.
• Mar 2023 TPC for NeurIPS 2023.
• Mar 2023 One workshop proposal accepted by KDD 2023.
• Feb 2023 One paper accepted by ICDE 2023.
• Mar 2023 TPC for ICDM 2023.
• Jan 2023 TPC for KDD 2023.
• Jan 2023 One paper accepted by TPDS.
• Dec 2022 TPC for ICML 2023.
• Dec 2022 Review editor for Frontiers in Big Data.
• Nov 2022 TPC for IJCAI 2023 and CVPR 2023.
• Nov 2022 One book chapter accepted by Encyclopedia of Big Data Technologies.
• Nov 2022 Invited talk at the Zhejiang University.
• Oct 2022 Invited talk at the Synced.
• Sep 2022 One paper accepted by NeurIPS 2022.
• Sep 2022 Two papers accepted by ICDM 2022.
• July 2022 SPC for AAAI 2023.
• July 2022 TPC for ICLR 2023 and SDM 2023.
• May 2022 One paper accepted by KDD 2022.
• May 2022 Two papers accepted by ICML 2022.
• Apr 2022 One paper accepted by IJCAI 2022.
• Mar 2022 TPC for NeurIPS 2022 and ICDM 2022.
• Mar 2022 One paper accepted by ICDE 2022.
• Jan 2022 One paper accepted by KAIS.
• Jan 2022 One book chapter accepted by Encyclopedia of Big Data Technologies.
• Dec 2021 SPC for KDD 2022 and IJCAI 2022.
• Dec 2021 One paper accepted by AAAI 2022.
• Sep 2021 One paper accepted by NeurIPS 2021.
• Sep 2021 One paper accepted by Applied Nursing Research.
• Aug 2021 Two papers accepted by EMNLP 2021.
• Aug 2021 One paper accepted by TIST.
• Aug 2021 SPC for AAAI 2022.
• Jul 2021 Sectional Editor in Chief for AIMS ERA.
• Jul 2021 One paper accepted by TKDD.
• Jul 2021 One paper accepted by VLDBJ.
• Jul 2021 One paper accepted by Transportation Research Record.
• Jun 2021 TPC for ICLR 2022.
• May 2021 One paper accepted by KDD 2021.
• May 2021 Two papers accepted by ICML 2021.
• Apr 2021 One paper accepted by IJCAI 2021.
• Apr 2021 One paper accepted by IJCNN 2021.
• Apr 2021 TPC for NeurIPS 2021 and ICDM 2021.
• Mar 2021 Guest editor for Frontiers in Artificial Intelligence and Frontiers in Big Data.
• Mar 2021 TPC for EMNLP 2021.
• Feb 2021 One paper accepted by Frontiers in Artificial Intelligence.
• Jan 2021 One paper accepted by WWW 2021.
• Dec 2020 TPC for ICML 2021, ACL 2021, and KDD 2021.
• Nov 2020 SPC for IJCAI 2021.
• Nov 2020 Invited talk at the Department of Mathematics and Statistics, Auburn University.
• Oct 2020 TPC for NAACL 2021.
• Oct 2020 Two papers accepted by BigData 2020.
• Sep 2020 One paper accepted by NeurIPS 2020.
• Sep 2020 One paper accepted by ICMLA 2020.
• Aug 2020 One paper accepted by ICDM 2020.
• Aug 2020 TPC for AAAI 2021.
• Jun 2020 TPC for NeurIPS 2020.
• May 2020 One paper accepted by TKDE.
• Apr 2020 One paper accepted by TOIT.
• Apr 2020 One paper accepted by IJCAI 2020.
• Apr 2020 TPC for EMNLP 2020 and BigData 2020.
• Apr 2020 One paper accepted by ACL 2020.
• Mar 2020 TPC for AACL-IJCNLP 2020.
• Mar 2020 Invited talk at the University of Alabama at Tuscaloosa.
• Mar 2020 Invited talk at the Kent State University.
• Feb 2020 Invited to visit Baidu Research.
• Jan 2020 TPC for KDD 2020.
• Dec 2019 Invited keynote talk at IEEE BigData 2019.

Selected Publications All Publications»

DBLP   Google Scholar   ResearchGate   Aminer

• ICC'25 Making Computational Task Offloading Decision Based on Swarm Intelligence enabled RL in Internet-of-Things Blockchain
  Zhuo Chen, Jiahuan Yi, Yunpeng Yang, Yang Zhou
  
• EDBT'25 Efficient Enumeration of Large Maximal k-Plexes
  Qihao Cheng, Da Yan, Tianhao Wu, Lyuheng Yuan, Ji Cheng, Zhongyi Huang, Yang Zhou
  
• TSAS'24 Scaling Terrain-Aware Spatial Machine Learning for Flood Mapping on Large Scale Earth Imagery Data
  Saugat Adhikari, Zhe Jiang, Jiao Han, Zelin Xu, Yupu Zhang, Arpan Sainju, Yang Zhou
• EMNLP'24 Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models
  Ji Liu, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Yang Zhou, Patrick Valduriez, Dejing Dou
  
• TIST'24 Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
  Ji Liu, Juncheng Jia, Hong Zhang, Yuhui Yun, Leye Wang, Yang Zhou, Huaiyu Dai, and Dejing Dou
• CIKM'24 Advancing Certified Robustness of Explanation via Gradient Quantization
  Yang Xiao, Zijie Zhang, Yuchen Fang, Da Yan, Yang Zhou, Wei-Shinn Ku, Bo Hui
  
• CIKM'24 DirDense: A Tool for Mining Dense Subgraphs from a Big Directed Graph
  Jalal Khalil, Ahmad Akhlaque, Da Yan, Lyuheng Yuan, Saugat Adhikari, Yang Zhou, Zhe Jiang
  
• ICML'24 Effective Federated Graph Matching
  Yang Zhou, Zijie Zhang, Zeru Zhang, Lingjuan Lyu, Wei-Shinn Ku
  
• IJCAI'24 EvaNet: Elevation-Guided Flood Extent Mapping on Earth Imagery
  Mirza Sami, Da Yan, Saugat Adhikari, Lyuheng Yuan, Jiao Han, Zhe Jiang, Jalal Khalil, Yang Zhou
• ICDE'24 Faster Depth-First Subgraph Matching on GPUs
  Lyuheng Yuan, Da Yan, Jiao Han, Akhlaque Ahmad, Yang Zhou, Zhe Jiang
  
• ICDE'24 G2-AIMD: A Memory-Efficient Subgraph-Centric Framework for Efficient Subgraph Search on GPUs
  Lyuheng Yuan, Akhlaque Ahmad, Da Yan, Jiao Han, Saugat Adhikari, Xiaodong Yu, Yang Zhou
  
• ICDE'24 FSM-Explorer: An Interactive Tool for Frequent Subgraph Pattern Mining from a Big Graph
  Jalal Khalil, Da Yan, Lyuheng Yuan, Jiao Han, Saugat Adhikari, Cheng Long, Yang Zhou
  
• SDM'24 AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices
  Ji Liu, Tianshi Che, Yang Zhou, Ruoming Jin, Huaiyu Dai, Dejing Dou, Patrick Valduriez
  
• AAAI'24 FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update
  Ji Liu, Juncheng Jia, Tianshi Che, Chao Huo, Jiaxiang Ren, Yang Zhou, Huaiyu Dai, Dejing Dou
  
• AAAI'24 Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery
  Zelin Xu, Tingsong Xiao, Wenchong He, Yu Wang, Zhe Jiang, Shigang Chen, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou
  
• TKDD'23 Three-stage Transferable and Generative Crowdsourced Comment Integration Framework Based on Zero- and Few-shot Learning with Domain Distribution Alignment
  Huan Rong, Xin Yu, Tinghuai Ma, Victor S. Sheng, Yang Zhou, Mznah Al-Rodhaan
  
• EMNLP'23 Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization [code]
  Tianshi Che, Ji Liu, Yang Zhou, Jiaxiang Ren, Jiwen Zhou, Victor S. Sheng, Huaiyu Dai, Dejing Dou
  
• EMNLP'23 Exploring the Effectiveness of Multi-Lingual Commonsense Knowledge-Aware Open-Domain Dialogue Response Generation
  Sixing Wu, Jiong Yu, Tianshi Che, Yang Zhou, Wei Zhou
  
• GLOBECOM'23 A Channel Aggregation based Dynamic Pruning Method in Federated Learning
  Zhuo Chen, Xiaoxiang Tan, Zhiyuan Zhou, Yang Zhou
  
• ICML'23 Fast Federated Machine Unlearning with Nonlinear Functional Theory
  Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan
  
• ICML'23 Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing
  Jiaxiang Ren, Yang Zhou, Jiayin Jin, Lingjuan Lyu, Da Yan
  
• KDD'23 International Workshop on Federated Learning for Distributed Data Mining
  Junyuan Hong, Zhuangdi Zhu, Lingjuan Lyu, Yang Zhou, Vishnu Boddeti, Jiayu Zhou
  
• ICDE'23 A Self-play and Sentiment-Emphasized Comment Integration Framework Based on Deep Q-Learning in a Crowdsourcing Scenario
  Huan Rong, Victor S. Sheng, Tinghuai Ma, Yang Zhou, Mznah Al-Rodhaan
  
• TPDS'23 Multi-Job Intelligent Scheduling with Cross-Device Federated Learning
  Ji Liu, Juncheng Jia, Beichen Ma, Chendi Zhou, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou
• Chapter'22 Parallel Graph Processing
  Da Yan, Yang Zhou, Guimu Guo, Hang Liu. Albert Zomaya, Javid Taheri, Sherif Sakr (Eds.)
  Encyclopedia of Big Data Technologies
• NeurIPS'22 Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization
  Zijie Zhang, Yang Zhou, Xin Zhao, Tianshi Che, Lingjuan Lyu
  
• ICDM'22 Federated Fingerprint Learning with Heterogeneous Architectures
  Tianshi Che, Zijie Zhang, Yang Zhou, Xin Zhao, Ji Liu, Zhe Jiang, Da Yan, Ruoming Jin, Dejing Dou
  
• ICDM'22 Center-Based iPSC Colony Counting with Multi-Task Learning
  Mirza Tanzim Sami, Da Yan, Bhadhan Roy Joy, Jalal Khalil, Ricardo Cevallos, Md Emon Hossain, Kejin Hu, Yang Zhou
  
• KDD'22 Quantifying and Reducing Registration Uncertainty of Spatial Vector Labels on Earth Imagery
  Wenchong He, Marcus Kriby, Zhe Jiang, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou
  
• ICML'22 Accelerated Federated Learning with Decoupled Adaptive Optimization
  Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou
• ICML'22 Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing
  Jiayin Jin, Zeru Zhang, Yang Zhou, Lingfei Wu
• IJCAI'22 FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server
  Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai, Dejing Dou
• ICDE'22 Maximal Directed Quasi-Clique Mining
  Guimu Guo, Da Yan, Lyuheng Yuan, Jalal Khalil, Cheng Long, Zhe Jiang, Yang Zhou
• KAIS'22 From Distributed Machine Learning to Federated Learning: A Survey
  Ji Liu, Jizhou Huang, Yang Zhou, Xuhong Li, Shilei Ji, Haoyi Xiong, Dejing Dou
• VLDBJ'22 PrefixFPM: A Parallel Framework for General-Purpose Mining of Frequent and Closed Patterns
  Da Yan, Wenwen Qu, Guimu Guo, Xiaoling Wang, Yang Zhou
• Chapter'22 Think-Like-a-Task Programming Model
  Da Yan, Yang Zhou, Guimu Guo. Albert Zomaya, Javid Taheri, Sherif Sakr (Eds.)
  Encyclopedia of Big Data Technologies
• AAAI'22 Efficient Device Scheduling with Multi-Job Federated Learning
  Chendi Zhou, Ji Liu, Juncheng Jia, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou
  
• TIST'22 Earth Imagery Segmentation on Terrain Surface with Limited Training Labels: A Semi-supervised Approach based on Physics-Guided Graph Co-Training
  Wenchong He, Arpan Sainju, Zhe Jiang, Da Yan, Yang Zhou
• NeurIPS'21 Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory
  Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou
  
• EMNLP'21 Adversarial Attack against Cross-lingual Knowledge Graph Alignment
  Zeru Zhang, Zijie Zhang, Yang Zhou, Lingfei Wu, Sixing Wu, Xiaoying Han, Dejing Dou, Tianshi Che, Da Yan
  
• EMNLP'21 More is Better: Enhancing Open-Domain Dialogue Generation by Using Multi-Source Heterogeneous Knowledge
  Sixing Wu, Ying Li, Minghui Wang, Dawei Zhang, Yang Zhou, Zhonghai Wu
  
• TKDD'21 Unsupervised Adversarial Network Alignment with Reinforcement Learning
  Yang Zhou, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Jingyi Zheng, Zhe Jiang, Da Yan, Dejing Dou
• KDD'21 Towards a Better Understanding of Linear Models for Recommendation
  Ruoming Jin, Dong Li, Jing Gao, Zhi Liu, Li Chen, Yang Zhou
• ICML'21 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
  Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan
• ICML'21 Integrated Defense for Resilient Graph Matching
  Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou
• IJCAI'21 Knowledge-Aware Dialogue Generation via Hierarchical Infobox Accessing and Infobox-Dialogue Interaction Graph Network
  Sixing Wu, Minghui Wang, Dawei Zhang, Yang Zhou, Ying Li, Zhonghai Wu
• WWW'21 Robust Network Alignment via Attack Signal Scaling and Adversarial Perturbation Elimination
  Yang Zhou, Zeru Zhang, Sixing Wu, Victor S. Sheng, Xiaoying Han, Zijie Zhang, Ruoming Jin
• NeurIPS'20 Adversarial Attacks on Deep Graph Matching
  Zijie Zhang, Zeru Zhang, Yang Zhou, Yelong Shen, Ruoming Jin, Dejing Dou
• ICDM'20 Robust Meta Network Embedding against Adversarial Attacks
  Yang Zhou, Jiaxiang Ren, Dejing Dou, Ruoming Jin, Jingyi Zheng, Kisung Lee
• IJCAI'20 TopicKA: Generating Commonsense Knowledge-Aware Dialogue Responses Towards the Recommended Topic Fact
  Sixing Wu, Ying Li, Dawei Zhang, Yang Zhou, Zhonghai Wu
  
• ACL'20 Diverse and Informative Dialogue Generation with Context-Specific Commonsense Knowledge Awareness
  Sixing Wu, Ying Li, Dawei Zhang, Yang Zhou, Zhonghai Wu
• TKDE'20 A Self-play and Sentiment-Emphasized Comment Integration Framework Based on Deep Q-Learning in a Crowdsourcing Scenario
  Huan Rong, Victor S. Sheng, Yang Zhou, Tinghuai Ma, Mznah Al-Rodhaan
  
• TOIT'20 Improving Collaborative Filtering with Social Influence over Heterogeneous Information Networks
  Yang Zhou, Ling Liu, Kisung Lee, Balaji Palanisamy, Qi Zhang
  

Research

• Trustworthy Machine Learning
• Parallel, Distributed, and Federated Learning
• Natural Language Processing
• Graph Machine Learning
• Interdisciplinary Research

Patents

• US Patent Unsupervised Trajectory-based Wrong-way Driving Incident Detection Method for Regular Traffic Videos, Filed: 63136713, 2021.
• US Patent Complex Service Network Ranking and Clustering, Publication: US10210558B2, 2019.
• US Patent Interactive Acquisition of Remote Services, Publication: US9122745B2, 2015.

Talks

• Invited Talk Federated-Learning-Driven Traffic Management for Intelligent Transportation Systems, Alabama Higher Education AI Exchange, 2024.
• Invited Talk Trustworthy and Scalable Machine Learning, Florida State University, 2024.
• Invited Talk Trustworthy Machine Learning: Security, Privacy, and Fairness, University of Alabama at Birmingham, 2023.
• Invited Talk Trustworthy Machine Learning: Security, Privacy, and Fairness, Zhejiang University, 2022.
• Invited Talk FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server, Synced, 2022.
• Invited Talk Adversarial Machine Learning for Robust Prediction, Department of Mathematics and Statistics, Auburn University, 2020.
• Keynote Talk Deep Adversarial Network Embedding, IEEE BigData 2019.
• Invited Talk Deep Collective Information Network Mining, Kent State University, 2019.

Awards More »

• IEEE ICDE Best Demo Runner Up Award, 2024.
• Institute of Transportation Engineers Safety Project Award, 2024.
• Auburn University Outstanding Doctoral Student Award (for Ph.D. student, Tianshi Che), 2024.
• Microsoft KDD Rising Star, Microsoft Academic Search and Microsoft Research Asia, 2016.
• IBM Winner of Invention Day Patent Marathon, IBM Almaden Research, 2013.
• IBM First Patent Application Invention Achievement Award, IBM T.J. Watson Research, 2013.

Services

• Sectional Editor in Chief Section Data Mining and Machine Learning for AIMS ERA.
• Review Editor Frontiers in Big Data.
• Guest Editor Topic Adversarial Machine Learning for Robust Prediction for Frontiers in Artificial Intelligence, Frontiers in Big Data.
• Organizer International Workshop on Federated Learning for Distributed Data Mining, co-located with KDD 2023.
• Publicity Chair CSoNet 2021.
• Area Chair ICWS 2018.
• Session Chair KDD 2021, ICDM 2020, BigData 2018-2019, CIC 2019.
• Senior Program Committee Member IJCAI 2021-2024, AAAI 2022-2025.
• Program Committee Member NeurIPS 2020-2024, ICML 2021-2024, ICLR 2022-2025, AAAI 2019-2025, IJCAI 2019-2024, AISTATS 2025, KDD 2018-2024, ICDM 2017-2024, SDM 2019-2021, 2023-2024, ACL 2020, 2024, EMNLP 2020, 2024, NAACL 2021, EACL 2021, CVPR 2023, CIKM 2019, BigData 2018-2022, 2024, ICMLA 2020, ICWS 2019-2020, CIC 2018, IRI 2019, ICIOT 2018-2019.
• Panelist NSF 2019-2024.
• Journal Referee CSUR 2021, TBD 2022, TC 2024, TCE 2023, TDSC 2014-2016, TIFS 2024, TIST 2020-2021, TKDD 2014-2017, 2020-2021, TKDE 2018-2022, TMLR 2023-2024, TNNLS 2021-2023, TNSE 2017-2024, TOIS 2022, TOIT 2016, 2018-2020, 2022, TSC 2015, 2017-2018, TWEB 2015-2016, VLDBJ 2024, WWWJ 2016, DMKD 2016, KAIS 2020-2021, Machine Learning 2015, Neurocomputing 2021-2022, IEEE Access 2018, DAPD 2017, DKE 2019, 2021, ESWA 2018, FGCS 2018, IoT 2020, JIIS 2020, JOCO 2020, JOCS 2016, 2019, JPDC 2016-2017, Computational Intelligence 2016, GigaScience 2017, PLOS ONE 2017-2018.

Teaching

• COMP2710 Software Construction (Spring 2024).
• COMP3220 Principles of Programming Languages (Spring 2018).
• COMP3270 Introduction to Algorithms (Spring 2019-2022).
• COMP5120/6120 Database Systems I (Fall 2019-2021).
• COMP5130/6130 Data Mining (Fall 2017-2024).
• COMP7270 Advanced Algorithm (Spring 2023-2024).
• CS8803 Big Data Systems and Analytics, Large-scale Parallel and Distributed Graph Processing Frameworks, Guest Lecturer at Georgia Tech (October 2015).
• CS4440 Emerging Database Technologies, Clustering Analysis in Heterogeneous Information Networks, Guest Lecturer at Georgia Tech (April 2015).
• CS4675/CS6675 Advanced Internet Computing and Application Development, Teaching Assistant (Spring 2014).
• CS4365/CS6365 Introduction to Enterprise Computing, Teaching Assistant (Spring 2012).
• CS4400 Introduction to Database Systems, Teaching Assistant (Fall 2011).
• CS4400/CS8803 Introduction to Database Systems, Teaching Assistant (Spring 2011, Summer 2016).