Books : [DBLP] [Google Scholar] [Blog]

  1. Arijit Khan, Yuan Ye, and Lei Chen, "On Uncertain Graphs", [link], in Morgan & Claypool Publishers, Synthesis Lectures on Data Management, 2018.

 

Book Chapters :

  1. Yinghui Wu and Arijit Khan, "Graph Pattern Matching", [link], in Sherif Sakr and Albert Zomaya (eds.), Encyclopedia of Big Data Technologies, Springer, 2019.
  2. Arijit Khan and Sayan Ranu, "Big-Graphs: Querying, Mining, and Beyond", [link], in Sherif Sakr and Albert Zomaya (eds.), Springer Handbook of Big Data Technologies, Springer, 2017.

 

Articles :

  1. Zhifeng Bao, Panagiotis Bouros, Reynold Cheng, Byron Choi, Anton Dignös, Wei Ding, Yixiang Fang, Boyang Han, Jilin Hu, Arijit Khan, Wenqing Lin, Xuemin Lin, Cheng Long, Nikos Mamoulis, Jian Pei, Matthias Renz, Shashi Shekhar, Jieming Shi, Eleni Tzirita Zacharatou, Sibo Wang, Xiao Wang, Xue Wang, Raymond Chi-Wing Wong, Da Yan, Xifeng Yan, Bin Yang, Dezhong Yao, Ce Zhang, Peilin Zhao, Rong Zhu, "A Summary of ICDE 2022 Research Session Panels", [link], in Bulletin of the Technical Committee on Data Engineering, 47(4), 4-17, 2023.
  2. Arijit Khan and Yinghui Wu, "Graph Pattern Matching Queries - Approximation and User-friendliness", [link], in ACM SIGMOD Blog, 2017.

 

Selected Journal and Conference Papers :

2024

  1. SIGMOD 2024: Tingyang Chen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu Ke, and Yunjun Gao, "View-based Explanations for Graph Neural Networks", [paper], [Extended Version], [Blog], [Code], in Proc. of ACM International Conference on Management of Data 2024.
  2. SIGMOD 2024 (Demo): Tingyang Chen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu Ke, and Yunjun Gao, "User-friendly, Interactive, and Configurable Explanations for Graph Neural Networks with Graph Views," [paper], [Video], [Code] , in Proc. of ACM International Conference on Management of Data 2024.
  3. ICDE 2024: Dazhuo Qiu, Mengying Wang, Arijit Khan, and Yinghui Wu, "Generating Robust Counterfactual Witnesses for Graph Neural Networks", [paper], [Blog], [Code] , in Proc. of IEEE International Conference on Data Engineering 2024.
  4. ICDE 2024 (Lightning Talk): Arijit Khan, "Synergies between Graph Data Management and Machine Learning in Graph Data Pipeline", [paper], in Proc. of IEEE International Conference on Data Engineering 2024.
  5. TKDE 2024: Peng Fang, Zhenli Li, Arijit Khan, Siqiang Luo, Fang Wang, Zhan Shi, and Dan Feng, "Information-Oriented Random Walks and Pipeline Optimization for Distributed Graph Embedding", [link], in IEEE Transactions on Knowledge and Data Engineering Journal 2024, [Impact Factor=4.56].
  6. DSAA 2024: Naheed Anjum Arafat, Ehsan Bonabi Mobaraki, Arijit Khan, Yllka Velaj, and Francesco Bonchi, "Estimate and Reduce Uncertainty in Uncertain Graphs", [paper], [Code], in IEEE International Conference on Data Science and Advanced Analytics 2024, [Acceptance Rate: 29/112 (26%)].
  7. Frontiers in Blockchain 2024: Jason Zhu, Arijit Khan, and Cuneyt Gurcan Akcora, "Data Depth and Core-based Trend Detection on Blockchain Networks", [link], [Code], in Frontiers in Blockchain, section Blockchain Economics, 2024.
  8. Nature Scientific Reports 2024: Lin Zhao, Chai Kiat Yeo, Arijit Khan, Robby Luo, and Ling Peng Jin, "Identifying Shader Sub-Patterns for GPU Performance Tuning and Architecture Design", [link], [Code], in Scientific Reports - Nature, 2024.

2023

  1. VLDB 2023: Naheed Anjum Arafat, Arijit Khan, Arpit Kumar Rai, and Bishwamittra Ghosh, "Neighborhood-based Hypergraph Core Decomposition", [paper], [Extended Version], [Blog], [Code], in Proc. of International Conference on Very Large Databases 2023.
  2. VLDB 2023: Peng Fang, Arijit Khan, Siqiang Luo, Fang Wang, Dan Feng, Zhenli Li, Wei Yin, and Yuchao Cao, "Distributed Graph Embedding with Information-Oriented Random Walks", [paper], [Extended Version], [Blog], [Code], in Proc. of International Conference on Very Large Databases 2023.
  3. ICDE 2023: Arkaprava Saha, Xiangyu Ke, Arijit Khan, and Laks V.S. Lakshmanan, "Voting-based Opinion Maximization", [paper], [Extended Version], [Blog], [Code], in Proc. of IEEE International Conference on Data Engineering 2023.
  4. ICDE 2023: Arkaprava Saha, Xiangyu Ke, Arijit Khan, and Cheng Long, "Most Probable Densest Subgraphs", [paper], [Extended Version], [Blog], [Code], in Proc. of IEEE International Conference on Data Engineering 2023.
  5. SIGMOD Record 2023: Arijit Khan, "Knowledge Graphs Querying", [paper], in ACM SIGMOD Record 2023.
  6. DSAA 2023 (Tutorial): Arijit Khan and Ehsan B. Mobaraki, "Interpretability Methods for Graph Neural Networks", [paper], [talk], in IEEE International Conference on Data Science and Advanced Analytics.

 

2022

  1. ICDE 2022: Yuxiang Wang, Arijit Khan, Xiaoliang Xu, Jiahui Jin, Qifan Hong, and Tao Fu, "Aggregate Queries on Knowledge Graphs: Fast Approximation with Semantic-aware Sampling", [paper], [Extended Version], [Blog], [Code], in Proc. of IEEE International Conference on Data Engineering 2022.
  2. CIKM 2022 (Tutorial): Arijit Khan and Cuneyt Gurcan Akcora, "Graph-based Management and Mining of Blockchain Data", [paper], [talk] , in Proc. of the ACM International Conference on Information and Knowledge Management 2022, [Acceptance Rate: 7/21 (33%)].
  3. CIKM 2022 (Demo): Yuxiang Wang, Arijit Khan, Xiaoliang Xu, Shuzhan Ye, Shihuang Pan, and Yuhan Zhou, "Approximate and Interactive Processing of Aggregate Queries on Knowledge Graphs: A Demonstration", [paper], [Code], [Video], in Proc. of the ACM International Conference on Information and Knowledge Management 2022.
  4. WSDM 2022 (Demo): Voon Hou Su, Sourav Sen Gupta, and Arijit Khan, "Automating ETL and Mining of Ethereum Blockchain Network", [paper], [Code], [Video], in Proc. of the Web Search and Data Mining Conference 2022.
  5. TKDE 2022: Xiangyu Ke, Arijit Khan, Mohammad Al Hasan, and Rojin Rezvansangsari, "Reliability Maximization in Uncertain Graphs", [ArXiv], [Blog], in IEEE Transactions on Knowledge and Data Engineering Journal 2022, [Impact Factor=4.56].
  6. TKDD 2022: Xiangyu Ke, Arijit Khan, and Francesco Bonchi, "Multi-relation Graph Summarization", [paper], [Blog], in ACM Transactions on on Knowledge Discovery from Data Journal 2022, [Impact Factor=2.71].
  7. KBS 2022: Tianxing Wu, Arijit Khan, Melvin Yong, Guilin Qi, and Meng Wang, "Efficiently Embedding Dynamic Knowledge Graphs", [link], [Code], in Knowledge-based Systems Journal 2022, [Impact Factor=8.038].
  8. IEEE Blockchain 2022 (Short Paper): Arijit Khan, "Graph Analysis of the Ethereum Blockchain Data: A Survey of Datasets, Techniques, and Future Direction", [paper], [Blog], in Proc. of IEEE International Conference on Blockchain 2022, [Acceptance Rate: 14/139 (10.07%)][Featured in Research Pulse #72 by the Smart Contract Research Forum (SCRF)].
  9. COMPLEX NETWORKS 2022: Lin Zhao, Arijit Khan, Robby Luo, and Chai Kiat Yeo, "Graph Mining and Machine Learning for Shader Codes Analysis to Accelerate GPU Tuning", [paper], [Code], [Video], in Proc. of International Conference on Complex Networks and their Applications 2022.

 

2021

  1. VLDB 2021: Arkaprava Saha, Ruben Brokkelkamp, Yllka Velaj, Arijit Khan, and Francesco Bonchi, "Shortest Paths and Centrality in Uncertain Networks", [paper], [Blog], [Code], in Proc. of International Conference on Very Large Databases 2021, [Acceptance Rate: 24%].
  2. WebConf 2021: Lin Zhao, Sourav Sen Gupta, Arijit Khan, and Robby Luo, "Temporal Analysis of the Entire Ethereum Blockchain Network", [paper], [Blog], [Code], in Proc. of The Web Conference 2021, [Acceptance Rate: 357/1736 (20.6%)].
  3. ICDE 2021 (Extended Abstract): Xiangyu Ke, Arijit Khan, Mohammad Al Hasan, and Rojin Rezvansangsari, "Reliability Maximization in Uncertain Graphs", [paper], in Proc. of IEEE International Conference on Data Engineering 2021.
  4. COMPLEX NETWORKS 2021: Luo Fei, Tianxing Wu, and Arijit Khan, "Online Updates of Knowledge Graph Embedding", [paper], [Blog], in Proc. of International Conference on Complex Networks and their Applications 2021.
  5. IEEE BigData 2021: Jhalak Gupta and Arijit Khan, "Graph Classification with Minimum DFS Code: Improving Graph Neural Network Expressivity", [paper], [Blog], [Code], in Proc. of IEEE International Conference on Big Data 2021, [presented in Machine Learning on Big Data (MLBD 2021), special session of IEEE BigData 2021].

 

2020

  1. SIGMOD 2020: Junghoon Kim, Tao Guo, Kaiyu Feng, Gao Cong, Arijit Khan, and Farhana Choudhury, "Densely Connected User Community and Location Cluster Search in Location-Based Social Networks", [paper], in Proc. of ACM International Conference on Management of Data 2020, [Acceptance Rate: 27%].
  2. VLDB 2020: Arneish Prateek, Arijit Khan, Akshit Goyal, and Sayan Ranu, "Mining Top-k Pairs of Correlated Subgraphs in a Large Network", [paper], [Blog], [Code], in Proc. of International Conference on Very Large Databases 2020, [Acceptance Rate: 24.91%].
  3. ICDE 2020: Yuxiang Wang, Arijit Khan, Tianxing Wu, Jiahui Jin, and Haijiang Yan, "Semantic Guided and Response Times Bounded Top-k Similarity Search over Knowledge Graphs", [paper], [Extended Version], [Blog], [Code], in Proc. of IEEE International Conference on Data Engineering 2020.
  4. WebConf 2020: Xi Tong Lee, Arijit Khan, Sourav Sen Gupta, Yu Hann Ong, and Xuan Liu, "Measurements, Analyses, and Insights on the Entire Ethereum Blockchain Network", [paper], [Blog], [Dataset], in Proc. of The Web Conference 2020, [Acceptance Rate: 217/1129 (19%)].
  5. TKDE 2020: Tenindra Abeywickrama, Muhammad Aamir Cheema, and Arijit Khan, "K-SPIN: Efficiently Processing Spatial Keyword Queries on Road Networks", [link], in IEEE Transactions on Knowledge and Data Engineering Journal 2020, [Impact Factor=4.56].
  6. ICDE 2020 (Extended Abstract): Tenindra Abeywickrama, Muhammad Aamir Cheema, and Arijit Khan, "K-SPIN: Efficiently Processing Spatial Keyword Queries on Road Networks", [paper], in Proc. of IEEE International Conference on Data Engineering 2020.
  7. IEEE BigData 2020: Kenneth Teo Tian Shun, Eko Edita Limanta, and Arijit Khan, "An Evaluation of Backpropagation Interpretability for Graph Classification with Deep Learning", [paper], [Code], [Blog], in Proc. of IEEE International Conference on Big Data 2020, [Acceptance Rate: 83/535 (15.5%)].

 

2019

  1. SIGMOD 2019: Francesco Bonchi, Arijit Khan, and Lorenzo Severini, "Distance-generalized Core Decomposition", [Paper], [Blog] in Proc. of ACM International Conference on Management of Data 2019, [Acceptance Rate: 88/430 (20%)].
  2. VLDB 2019: Xiangyu Ke, Arijit Khan, and Leroy Lim Hong Quan, "An In-Depth Comparison of s-t Reliability Algorithms over Uncertain Graphs", [paper], [Extended Version], [Blog], [Code], in Proc. of International Conference on Very Large Databases 2019.
  3. IEEE BigData 2019 (Short Paper): Kaivalya Rawal and Arijit Khan, "Maximizing Contrasting Opinions in Signed Social Networks", [paper], [Extended Version], [Blog], [Code], in Proc. of IEEE International Conference on Big Data 2019, [Acceptance Rate: 105/550 (19%)].

 

2018

  1. SIGMOD 2018: Xiangyu Ke, Arijit Khan, and Gao Cong, "Finding Seeds and Relevant Tags Jointly: For Targeted Influence Maximization in Social Networks", [paper], [Blog], [Dataset], in Proc. of ACM International Conference on Management of Data 2018, [Acceptance Rate: 90/461 (20%)].
  2. VLDB 2018 (Demo): Xiangyu Ke, Michelle Teo, Arijit Khan, and Vijaya Krishna Yalavarthi, "A Demonstration of PERC: Probabilistic Entity Resolution With Crowd Errors", [paper], [Blog] [Video], in Proc. of International Conference on Very Large Databases 2018.
  3. USENIX ATC 2018: Arijit Khan, Gustavo Segovia, and Donald Kossmann, "On Smart Query Routing: For Distributed Graph Querying with Decoupled Storage", [paper], [Extended Version], [Talk], [Blog], in Proc. of USENIX Annual Technical Conference 2018, [Acceptance Rate: 76/378 (20%)].
  4. TKDE 2018: Arijit Khan, Francesco Bonchi, Francesco Gullo, and Andreas Nufer, "Conditional Reliability in Uncertain Graphs", [arXiv], in IEEE Transactions on Knowledge and Data Engineering Journal 2018, [Impact Factor=4.56].
  5. ICDE 2018: Shanshan Feng, Gao Cong, Arijit Khan, Xiucheng Li, Yong Liu, and Yeow Meng Chee, "Inf2vec: Latent Representation Model for Social Influence Embedding", [paper], in Proc. of IEEE International Conference on Data Engineering 2018.
  6. IEEE BigData 2018: Siyuan Liu and Arijit Khan, "An Empirical Analysis on Expressibility of Vertex Centric Graph Processing Paradigm", [paper], [Blog], in Proc. of IEEE International Conference on Big Data 2018, [Acceptance Rate: 98/518 (19%)]
  7. IEEE BigData 2018 (Short Paper): Vijaya Krishna Yalavarthi and Arijit Khan, "Steering Top-k Influencers in Dynamic Graphs via Local Updates", [paper], [Extended Version], [Code], in Proc. of IEEE International Conference on Big Data 2018, [Acceptance Rate: 103/518 (20%)].

 

2017

  1. VLDB 2017 (Tutorial): Arijit Khan, Sourav S. Bhowmick, and Francesco Bonchi, "Summarizing Static and Dynamic Big Graphs", [paper], [Talk], in Proc. of International Conference on Very Large Databases 2017, [Acceptance Rate: 8/16 (50%)].
  2. CIKM 2017: Vijaya Krishna Yalavarthi, Xiangyu Ke, and Arijit Khan, "Select Your Questions Wisely: For Entity Resolution With Crowd Errors", [paper], [Blog] [Code], in Proc. of ACM International Conference on Information and Knowledge Management 2017, [Acceptance Rate: 171/820 (21%)].
  3. SNAM 2017: Arijit Khan and Charu C. Aggarwal, "Toward Query-Friendly Compression of Rapid Graph Streams"[link], in Springer Social Network Analysis and Mining Journal 2017 (invited and peer-reviewed), [Impact Factor=1.61].
  4. EDBT 2017 (Short Paper): Arijit Khan, "Vertex-Centric Graph Processing: Good, Bad, and the Ugly", [paper], in Proc. of International Conference on Extending Database Technology 2017, [Acceptance Rate: 22/93 (24%)].

 

2016

  1. SIGMOD 2016: Pratanu Roy, Arijit Khan, and Gustavo Alonso, "Augmented Sketch: Faster and More Accurate Stream Processing", [paper], [Talk], in Proc. of ACM International Conference on Management of Data 2016, [Acceptance Rate: 20%].
  2. ICDE 2016: Arijit Khan, Benjamin Zehnder, and Donald Kossmann, "Revenue Maximization by Viral Marketing: A Social Network Host's Perspective", [paper], [Extended Version], [Talk], [Code], in Proc. of IEEE International Conference on Data Engineering 2016.
  3. ICDE 2016 (Extended Abstract): Nandish Jayaram, Arijit Khan, Chengkai Li, Xifeng Yan, and Ramez Elmasri, "Querying Knowledge Graphs by Example Entity Tuples", [paper], in Proc. of IEEE International Conference on Data Engineering 2016.
  4. CIKM 2016 (Short Paper): Arijit Khan, "Towards Time-Discounted Influence Maximization", [paper], in Proc. of ACM International Conference on Information and Knowledge Management 2016, [Acceptance Rate: 300/925 (32%)].
  5. ASONAM 2016: Arijit Khan and Charu C. Aggarwal, "Query-Friendly Compression of Graph Streams", [paper], [Talk], in Proc. of IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2016, [Acceptance Rate: 43/316 (14%)].

 

2015

  1. TKDE 2015: Nandish Jayaram, Arijit Khan, Chengkai Li, Xifeng Yan, and Ramez Elmasri, "Querying Knowledge Graphs by Example Entity Tuples", [paper], in IEEE Transactions on Knowledge and Data Engineering Journal 2015, [Impact Factor=4.56].
  2. VLDB 2015 (Tutorial): Arijit Khan, Lei Chen, "On Uncertain Graphs Modeling and Queries", [paper], [talk], in Proc. of International Conference on Very Large Databases 2015, [Acceptance Rate: 6/20 (30%)].
  3. CIKM 2015 (Short Paper): Arijit Khan, Francesco Gullo, Thomas Wohler, and Francesco Bonchi, "Top-k Reliable Edge Colors in Uncertain Graphs", [paper], in Proc. of ACM International Conference on Information and Knowledge Management 2015, [Acceptance Rate: 25%].
  4. SSDBM 2015: Arijit Khan, Vishwakarma Singh, "Answering Top-k Representative Queries with Binary Constraints", [paper] , in Proc. of International Conference on Scientific and Statistical Database Management 2015, [Acceptance Rate: 26/71 (37%)].

 

2014

  1. SIGMOD 2014: Arijit Khan, Pouya Yanki, Bojana Dimcheva, and Donald Kossmann, "Towards Indexing Functions: Answering Scalar Product Queries", [paper], [talk], [Code], in Proc. of ACM International Conference on Management of Data 2014, [Acceptance Rate: 107/421 (25.41%)].
  2. VLDB 2014 (Tutorial): Arijit Khan, Sameh Elnikety, "Systems for Big-Graphs", [paper], [talk], in Proc. of International Conference on Very Large Databases 2014.
  3. EDBT 2014: Arijit Khan, Francesco Bonchi, Aris Gionis, and Francesco Gullo, "Fast Reliability Search in Uncertain Graphs", [paper], [talk], [Code], in Proc. of International Conference on Extending Database Technology 2014, [Acceptance Rate: 20%].
  4. ICDE 2014 (Demo): Nandish Jayaram, Mahesh Gupta, Arijit Khan, Chengkai Li, Xifeng Yan, and Ramez Elmasri, "GQBE: Querying Knowledge Graphs by Example Entity Tuples", [paper], in Proc. of IEEE International Conference on Data Engineering 2014, [Acceptance Rate: 28/65 (43.1%)].

 

2013

  1. VLDB 2013: Arijit Khan, Yinghui Wu, Charu C. Aggarwal, and Xifeng Yan, "NeMa: Fast Graph Search with Label Similarity", [paper], [talk],[Code], in Proc. of International Conference on Very Large Data Bases 2013, [Acceptance Rate: 22.7%].

 

2012

  1. SIGMOD 2012: Shengqi Yang, Xifeng Yan, Bo Zong, and Arijit Khan, "Towards Effective Partition Management for Large Graphs", [paper], in Proc. of ACM International Conference on Management of Data 2012, [Acceptance Rate: 48/289 (16.6%)].
  2. ICDE 2012 (Tutorial): Arijit Khan, Yinghui Wu, and Xifeng Yan, "Emerging Graph Queries In Linked Data", [paper], [talk], in Proc. of IEEE International Conference on Data Engineering 2012.
  3. CIKM 2012: Nan Li, Xifeng Yan, Zhen Wen, and Arijit Khan, "Density Index and Proximity Search in Large Graphs", [paper], in Proc. of ACM International Conference on Information and Knowledge Management 2012, [Acceptance Rate: 146/1088 (13.4%)].

 

2011

  1. SIGMOD 2011: Arijit Khan, Nan Li, Xifeng Yan, Ziyu Guan, Supriyo Chakraborty and Shu Tao, "Neighborhood Based Fast Graph Search in Large Networks", [paper], [talk], , in Proc. of ACM International Conference on Management of Data 2011, [Acceptance Rate: 87/375 (23%)]. SIGMOD'11 Repeatability and Workability Result: Repeatable & Workable.
  2. SDM 2011: Charu C. Aggarwal, Arijit Khan, and Xifeng Yan, "On Flow Authority Discovery in Social Networks", [paper],[talk],[Code], in Proc. of SIAM International Conference of Data Mining 2011, [Acceptance Rate: 25.1%].

 

2010

  1. SIGMOD 2010: Arijit Khan, Xifeng Yan, and Kun-Lung Wu, "Towards Proximity Pattern Mining in Large Graphs", [paper],[talk],[Code] , in Proc. of ACM International Conference on Management of Data 2010, [Acceptance Rate: 20.8%]. SIGMOD'10 Repeatabilty & Workability Result .

 

Editorials and Front Matters :

  1. Angela Bonifati, Yongluan Zhou, Marcos Antonio Vaz Salles, Alexander Bhm, Dan Olteanu, George H. L. Fletcher, Arijit Khan, and Bin Yang (eds.), "Proceedings of the 23nd International Conference on Extending Database Technology", EDBT 2020, in OpenProceedings.org 2020.
  2. Fusheng Wang, Gang Luo, Chunhua Weng, Arijit Khan, Prasenjit Mitra, and Cong Yu (eds.), "Biomedical Data Management and Graph Online Querying", [front matter], VLDB 2015 Workshops, Big-O(Q) and DMAH, in Lecture Notes in Computer Science, Springer.

 

Selected Workshop Papers :

  1. SEAGraph 2024: Tingyang Chen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu Ke, and Yunjun Gao, "View-based Explanations for Graph Neural Networks (Extended Abstract)", [paper], in Proc. of International Workshop on Search, Exploration, and Analysis in Heterogenous Datastore, Graph Data Edition 2024, co-located with IEEE International Conference in Data Engineering 2024 (ICDE 2024).
  2. D3A 2024: Arijit Khan, "Explainability Methods for GNNs: Towards Usability, Robustness, and Benchmarking", (Poster), in Danish Digitalization, Data Science and AI conference 2024 (D3A’24).
  3. GRADES-NDA 2023: Ehsan B. Mobaraki and Arijit Khan, "Interpretability Methods for Graph Neural Networks", (Demo), [paper], [Video], in Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) (GRADES & NDA'23), co-located with International Conference on Management of Data 2023 (SIGMOD 2023).
  4. GRADES-NDA 2022: Lin Zhao, Arijit Khan, and Robby Luo, "ShaderNet: Graph-based Shader Code Analysis to Accelerate GPU’s Performance Improvement", (Demo), [paper], [Webpage], [Video], in Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) (GRADES & NDA'22), co-located with International Conference on Management of Data 2022 (SIGMOD 2022).
  5. SIAM NS 2018: Arijit Khan, "Conditional Reliability and Influence Maximization over Social Networks", in SIAM Workshop on Network Science 2018.
  6. GRADES 2014: Nandish Jayaram, Arijit Khan, Chengkai Li, Xifeng Yan, and Ramez Elmasri, "Towards a Query-by-Example System for Knowledge Graphs", in Workshop on Graph Data Management Experiences and Systems 2014 [co-located with ACM International Conference on Management of Data 2014 (SIGMOD 2014)].
  7. CloudMan 2012: Arijit Khan, Xifeng Yan, Shu Tao, and Nikos Anerousis, "Workload Characterization and Prediction in the Cloud: A Multiple Time Series Approach", in Workshop on Cloud Management 2012 [co-located with IEEE/IFIP Network Operations and Management Symposium 2012 (NOMS 2012)].
  8. GDM 2012: Arijit Khan, Vishwakarma Singh, and Jian Wu, "Find Skyline Nodes in Large Networks", in Workshop on Graph Data Management: Techniques and Applications 2012 [co-located with IEEE International Conference in Data Engineering 2012 (ICDE 2012)].
  9. WISARD 2008: Arijit Khan and Lawrence Jenkins, "Undersea Wireless Sensor Network for Ocean Pollution Prevention", in Workshop on WIreless Systems: Advanced Research  and Development 2008 [co-located with International Conference on COMmunication System softWAre and MiddlewaRE 2008 (COMSWARE 2008)].