2023

• Gray, K, M Li, R Ahmed, MK Rahman, A Azad, S Kobourov, and K B.rner (2023). A Scalable Method for Readable Tree Layouts. IEEE Transactions on Visualization and Computer Graphics. DOI: https://doi.org/10.1109/TVCG. 2023.3274572.

• Pavlopoulos, GA, FA Baltoumas, S Liu, O Selvitopi, AP Camargo, S Nayfach, A Azad, S Roux, L Call, NN Ivanova, IM Chen, D Paez-Espino, E Karatzas, Novel Metagenom Protein Families Consortium, I Iliopoulos, K Konstantinidis, JM Tiedje, J Pett-Ridge, D Baker, A Visel, CA Ouzounis, S Ovchinnikov, A Buluc, and NC Kyrpides (2023). Discovery, diversity and distribution of functional dark matter through global metagenomics. Nature, 1–9.

• Hassani, E, MT Hussain, and A Azad (2023). Parallel Algorithms for Computing Jaccard Weights on Graphs using Linear Algebra. Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC). IEEE, pp.1–7.

• Ranawaka, I, MK Rahman, and A Azad (2023). Distributed Sparse Random Projection Trees for Constructing K Nearest Neighbor Graphs. Proceedings of the IEEE International Parallel and Distributed Processing Symposium (IPDPS). IEEE.

2022

• Rahman, MK, A Agrawal, and A Azad (2022). MarkovGNN: Graph Neural Networks on Markov Diffusion. Companion Proceedings of the Web Conference 2022 (WWW). ACM, pp.1019–1029. DOI: https ://doi.org /10.1145/3487553.3524713.

• Selvitopi, O, S Ekanayakey, G Guidi, MG Awan, GA Pavlopoulos, A Azad, N Kyrpides, L Oliker, K Yelick, and A Buluc. Extreme-scale many-against-many protein similarity search. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC). IEEE, pp.1–12. ACM Gordon Bell award finalist.

• Wanyan, T, M Lin, E Klang, KM Menon, FF Gulamali, A Azad, Y Zhang, Y Ding, Z Wang, F Wang, B Glicksberg, and Y Peng (2022). Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction. Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB). ACM, pp.1–9. DOI: https://doi.org/10.1145/3535508.3545541.

• Akkas, S and A Azad (2022). JGCL: Joint Self-Supervised and Supervised Graph Contrastive Learning. Companion Proceedings of the Web Conference 2022 (WWW). ACM, pp.1099–1105. DOI: https://doi.org/10 .1145/3487553.3524722.

• Hussain, MT, GS Abhishek, A Bulu., and A Azad (2022). Parallel Algorithms for Adding a Collection of Sparse Matrices. Proceedings of IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, pp.285–294. DOI: 10.1109/IPDPSW55747.2022.00058.

• Hussain, MT, A Khan, A Azad, S Chatterjee, R Brigantic, and M Halappanavar (2022). Disruption-Robust Community Detection Using Consensus Clustering in Complex Networks. Proceedings of the IEEE International Symposium on Technologies for Homeland Security (HST). IEEE, pp.1–6. DOI: 10.1109/HST56032.2022.10024983.

• Majeske, N, X Zhang, M Sabaj, L Gong, C Zhu, and A Azad (2022). Inductive predictions of hydrologic events using a Long Short-Term Memory network and the Soil and Water Assessment Tool. Environmental Modelling & Software 152, 105400. DOI: https://doi.org/10.1016/j.envsoft.2022.105400. Journal Impact Factor : 5.47 (2023).

• Rahman, M, MH Sujon, and A Azad (2022). Scalable force-directed graph representation learning and visualization. Knowledge and Information Systems 64(1), 207–233. DOI: https://doi.org/10.1007/s10115-021-01634-9. Journal Impact Factor : 2.53 (2022).

2021

• Ariful Azad, Oguz Selvitopi, Md Taufique Hussain, John Gilbert, Aydin Buluc, Combinatorial BLAS 2.0: Scaling combinatorial algorithms on distributed-memory systems, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2021.
• Mohammad R Saeedpour-Parizi, Shirin E Hassan, Ariful Azad, Kelly J Baute, Tayebeh Baniasadi, John B Shea, Target position and avoidance margin effects on path planning in obstacle avoidance, Scientific Reports, 11(1), 1-18, 2021.
• Oghenekaro Omodior, M R Saeedpour-Parizi, Md. Khaledur Rahman, Azad, Ariful and Keith Clay, Using convolutional neural networks for tick image recognition-a preliminary exploration, Experimental and Applied Acarology, Springer, Pages 1-16, 2021.
• Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, Benjamin S Glicksberg, Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records. Data Intelligence, 2021. [DOI]
• Anuj Godase, Md. Khaledur Rahman, and Ariful Azad, GNNfam: Utilizing Sparsity in Protein Family Predictions using Graph Neural Networks, ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), August, 2021, Florida, USA. (Virtual due to COVID-19)
• Md. Khaledur Rahman, M. Haque Sujon and Ariful Azad, FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks, The 35th IEEE International Parallel & Distributed Processing Symposium (IEEE IPDPS), May, 2021, Portland, Oregon, USA. (Virtual due to COVID-19)
• Md Taufique Hussain, Oguz Selvitopi, Aydin Buluç, Ariful Azad, Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale, The 35th IEEE International Parallel & Distributed Processing Symposium (IEEE IPDPS), May, 2021, Portland, Oregon, USA (Virtual due to COVID-19). [ArXiv]

2020

• Yongzhe Zhang, Ariful Azad, Aydin Buluç: Parallel algorithms for finding connected components using linear algebra. Journal of Parallel Distributed Computing (JPDC) 144: 14-27, 2020.
• Ariful Azad, Aydin Buluç, Xiaoye S. Li, Xinliang Wang, Johannes Langguth: A Distributed-Memory Algorithm for Computing a Heavy-Weight Perfect Matching on Bipartite Graphs. SIAM Journal of Scientific Computing 42(4): C143-C168, 2020.
• Tingyi Wanyan, Akhil Vaid, Jessica K De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N Nadkarni, Ariful Azad, Ying Ding, Benjamin S Glicksberg, Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit, IEEE Transactions on Big Data,  7(1), 38-44, 2020.
• Katherine Yelick, Aydın Buluç, Muaaz Awan, Ariful Azad, Benjamin Brock, Rob Egan, Saliya Ekanayake, Marquita Ellis, Evangelos Georganas, Giulia Guidi, Steven Hofmeyr, Oguz Selvitopi, Cristina Teodoropol, Leonid Oliker, The parallelism motifs of genomic data analysis. Philosophical Transactions of the Royal Society A, 378(2166), 2020. [pdf][DOI]
• Md. Khaledur Rahman, M. Haque Sujon and Ariful Azad, Force2Vec: Parallel Force-Directed Graph Embedding, The 20th IEEE International Conference on Data Mining (IEEE ICDM), November, 2020, Sorrento, Italy. (Virtual due to COVID-19)
• Oguz Selvitopi, Saliya Ekanayake, Giulia Guidi, Georgios Pavlopoulos, Ariful Azad, Aydin Buluc, Distributed many-to-many protein sequence alignment using sparse matrices, International Conference for High Performance Computing, Networking, Storage and Analysis (SC20), 2020.
• Tingyi Wanyan, Martin Kang, Marcus A. Badgeley, Kipp W. Johnson, Jessica K. De Freitas, Fayzan F. Chaudhry, Akhil Vaid, Shan Zhao, Riccardo Miotto, Girish N. Nadkarni, Fei Wang, Justin Rousseau, Ariful Azad, Ying Ding, Benjamin S. Glicksberg: Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions,  International Conference on Artificial Intelligence in Medicine (AIME), 2020: 14-25.
• Ariful Azad, Mohsen Mahmoudi Aznaveh, Scott Beamer, Mark P. Blanco, Jinhao Chen, Luke D’Alessandro, Roshan Dathathri, Tim Davis, Kevin Deweese, Jesun Firoz, Henry A. Gabb, Gurbinder Gill, Bálint Hegyi, Scott P. Kolodziej, Tze Meng Low, Andrew Lumsdaine, Tugsbayasgalan Manlaibaatar, Timothy G. Mattson, Scott McMillan, Ramesh Peri, Keshav Pingali, Upasana Sridhar, Gábor Szárnyas, Yunming Zhang, Yongzhe Zhang: Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite. IISWC 2020: 216-227.
• Oguz Selvitopi, Md Taufique Hussain, Ariful Azad, Aydin Buluç, Optimizing High Performance Markov Clustering for Pre-Exascale Architectures. IEEE International Parallel & Distributed Processing Symposium (IEEE IPDPS), 2020: 116-126.
• Yongzhe Zhang, Ariful Azad, Zhenjiang Hu, FastSV: A Distributed-Memory Connected Component Algorithm with Fast Convergence. PPSC 2020: 46-57.
• Zhixiang Gu, Jose Moreira, David Edelsohn, Ariful Azad: Bandwidth Optimized Parallel Algorithms for Sparse Matrix-Matrix Multiplication using Propagation Blocking. Symposium on Parallelism in Algorithms and Architectures (ACM SPAA) 2020: 293-303.
• Md. Khaledur Rahman, M. Haque Sujon and Ariful Azad. BatchLayout: A batch parallel force-directed graph layout algorithm in shared memory, In 13th IEEE Pacific Visualization Symposium (IEEE PacificVis), Tianjin, China, April, 2020.

• Yusuke Nagasaka, Satoshi Matsuoka, Ariful Azad, Aydın Buluç. Performance optimization, modeling and analysis of sparse matrix-matrix products on multi-core and many-core processors. Parallel Computing, 2019.
• Md. Khaledur Rahman and Ariful Azad. Evaluating the Community Structures from Network Images using Neural Networks, In 8th Proceedings of International Conference on Complex Networks and their Applications (Complex Networks), Pages 866 – 878, Lisbon, Portugal, December, 2019.
• Ariful Azad and Aydin Buluç. LACC: A Linear-Algebraic Algorithm for Finding Connected Components in Distributed Memory. IEEE Intl. Parallel & Distributed Processing Symposium (IEEE IPDPS), 2019.

2018

• Ariful Azad, Georgios A. Pavlopoulos, Christos A. Ouzounis, Nikos C. Kyrpides, Aydin Buluç. HipMCL: A high-performance parallel implementation of the Markov clustering algorithm for large-scale networks. Nucleic Acids Research, 2018.  [DOI]
• Amir Gholami, Ariful Azad, Peter Jin, Kurt Keutzer, and Aydin Buluç. Integrated model, batch, and domain parallelism in training neural networks. In SPAA’18: 30th ACM Symposium on Parallelism in Algorithms and Architectures (ACM SPAA), 2018.
• Yusuke Nagasaka, Satoshi Matsuoka, Ariful Azad, and Aydin Buluc. High-performance sparse matrix-matrix products on intel KNL and multicore architectures. In 47th International Conference on Parallel Processing Workshops (ICPPW), 2018.
• Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, and Katherine Yelick. Communication-avoiding optimization methods for massive-scale graphical model structure learning. International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.

• Ariful Azad, Aydin Buluç, Alex Pothen. Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting. IEEE Transactions on Parallel and Distributed Systems (TPDS), 28(1): 44-59, 2017.  [pdf][DOI]
• Ariful Azad, Grey Ballard, Aydin Buluç, James Demmel, Laura Grigori, Oded Schwartz, Sivan Toledo, and Samuel Williams. Exploiting multiple levels of parallelism in sparse matrix-matrix multiplication. SIAM Journal on Scientific Computing (SISC), 38(6):C624-C651, 2016. (Impact factor: 2.2) [pdf] [DOI]
• Ariful Azad, Bartek Rajwa, and Alex Pothen. Immunophenotype Discovery, Hierarchical Organization, and Template-based Classification of Flow Cytometry Samples. Frontiers in Oncology, v.6, 2016. [pdf][DOI]
• Ariful Azad, Bartek Rajwa, Alex Pothen. flowVS: Channel-Specific Variance Stabilization in Flow Cytometry. BMC Bioinformatics, 17:291, 2016. (Impact factor: 2.45) [pdf][DOI]
• Ariful Azad and Aydin Buluç. A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs. Parallel Computing, 58:117-130, 2016. (Impact factor: 1.36) [DOI]
• Mahantesh Halappanavar, Alex Pothen, Ariful Azad, Fredrik Manne, Johannes Langguth, and Arif Khan. Codesign Lessons Learned from Implementing Graph Matching on Multithreaded Architectures. Computer, 48(8), 46-55, 2015. (Impact factor: 1.76) [DOI]
• Johannes Langguth, Ariful Azad, Mahantesh Halappanavar, Fredrik Manne. On parallel push–relabel based algorithms for bipartite maximum matching. Parallel Computing, 40(7), 289-308, 2014. (Impact factor: 1.36) [DOI]
• Nima Aghaeepour, Greg Finak, FlowCAP Consortium, DREAM Consortium, Holger Hoos, Tim R Mosmann, Ryan Brinkman, Raphael Gottardo, and Richard H Scheuermann. Critical Assessment of Automated Flow Cytometry Analysis Techniques. Nature Methods, 10, 228–238, 2013. (Ariful Azad being a member of the FlowCAP consortium). (Impact factor: 25.1) [DOI]
• Ariful Azad, Saumyadipta Pyne, Alex Pothen. Matching phosphorylation response patterns of antigen-receptor-stimulated T cells via flow cytometry. BMC Bioinformatics, 13 (Suppl 2), S10, 2012. (Impact factor: 2.45) [DOI]