ramki.bib

@inproceedings{das2011fast,
  title={Fast rule mining over multi-dimensional windows},
  author={Das, Mahashweta and Deshpande, Prasad M and Kannan, Ramakrishnan},
  booktitle={Proceedings of the 2011 SIAM International Conference on Data Mining},
  pages={582--593},
  year={2011},
  organization={Society for Industrial and Applied Mathematics}
}

@inproceedings{ghoting2011nimble,
  title={NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce},
  author={Ghoting, Amol and Kambadur, Prabhanjan and Pednault, Edwin and Kannan, Ramakrishnan},
  booktitle={Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining},
  pages={334--342},
  year={2011}
}

@inproceedings{kannan2012bounded,
  title={Bounded matrix low rank approximation},
  author={Kannan, Ramakrishnan and Ishteva, Mariya and Park, Haesun},
  booktitle={Data Mining (ICDM), 2012 IEEE 12th International Conference on},
  pages={319--328},
  year={2012},
  organization={IEEE}
}

@article{kannan2014bounded,
  title={Bounded matrix factorization for recommender system},
  author={Kannan, Ramakrishnan and Ishteva, Mariya and Park, Haesun},
  journal={Knowledge and information systems},
  volume={39},
  number={3},
  pages={491--511},
  year={2014},
  publisher={Springer London}
}

@inproceedings{choo2014visirr,
  title={VisIRR: Visual analytics for information retrieval and recommendation with large-scale document data},
  author={Choo, Jaegul and Lee, Changhyun and Kim, Hannah and Lee, Hanseung and Liu, Zhicheng and Kannan, Ramakrishnan and Stolper, Charles D and Stasko, John and Drake, Barry L and Park, Haesun},
  booktitle={2014 IEEE conference on visual analytics science and technology (VAST)},
  pages={243--244},
  year={2014},
  organization={IEEE}
}

@article{fairbanks2015behavioral,
  title={Behavioral clusters in dynamic graphs},
  author={Fairbanks, James P and Kannan, Ramakrishnan and Park, Haesun and Bader, David A},
  journal={Parallel Computing},
  volume={47},
  pages={38--50},
  year={2015},
  publisher={North-Holland}
}

@inproceedings{kannan2016high,
  title={A High-performance Parallel Algorithm for Nonnegative Matrix Factorization},
  author={Kannan, Ramakrishnan and Ballard, Grey and Park, Haesun},
  booktitle={Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming},
  pages={9--1},
  year={2016},
  organization={ACM}
}

@phdthesis{kannan2016scalable,
  title={Scalable and distributed constrained low rank approximations},
  author={Kannan, Ramakrishnan},
  year={2016},
  school={Georgia Institute of Technology}
}

@article{kannan2017mpi,
  title={MPI-FAUN: An MPI-based framework for alternating-updating nonnegative matrix factorization},
  author={Kannan, Ramakrishnan and Ballard, Grey and Park, Haesun},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  volume={30},
  number={3},
  pages={544--558},
  year={2017},
  publisher={IEEE}
}

@techreport{kannan2016hpc,
  title={HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization},
  author={Kannan, Ramakrishnan and Sukumar, Sreenivas R and Ballard, Grey M and Park, Haesun},
  year={2016},
  institution={Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States)}
}

@inproceedings{sukumar2016mini,
  title={Mini-apps for high performance data analysis},
  author={Sukumar, Sreenivas R and Matheson, Michael A and Kannan, Ramakrishnan and Lim, Seung-Hwan},
  booktitle={2016 IEEE International Conference on Big Data (Big Data)},
  pages={1483--1492},
  year={2016},
  organization={IEEE}
}

@inproceedings{sukumar2016kernels,
  title={Kernels for scalable data analysis in science: Towards an architecture-portable future},
  author={Sukumar, Sreenivas R and Kannan, Ramakrishnan and Lim, Seung-Hwan and Matheson, Michael A},
  booktitle={2016 IEEE International Conference on Big Data (Big Data)},
  pages={1026--1031},
  year={2016},
  organization={IEEE}
}

@article{choo2018visirr,
  title={VisIRR: A visual analytics system for information retrieval and recommendation for large-scale document data},
  author={Choo, Jaegul and Kim, Hannah and Clarkson, Edward and Liu, Zhicheng and Lee, Changhyun and Li, Fuxin and Lee, Hanseung and Kannan, Ramakrishnan and Stolper, Charles D and Stasko, John and others},
  journal={ACM Transactions on Knowledge Discovery from Data (TKDD)},
  volume={12},
  number={1},
  pages={1--20},
  year={2018},
  publisher={ACM New York, NY, USA}
}

@inproceedings{kannan2017outlier,
  title={Outlier detection for text data},
  author={Kannan, Ramakrishnan and Woo, Hyenkyun and Aggarwal, Charu C and Park, Haesun},
  booktitle={Proceedings of the 2017 siam international conference on data mining},
  pages={489--497},
  year={2017},
  organization={Society for Industrial and Applied Mathematics}
}

@inproceedings{xu2017scaling,
  title={Scaling up data-parallel analytics platforms: Linear algebraic operation cases},
  author={Xu, Luna and Lim, Seung-Hwan and Li, Min and Butt, Ali R and Kannan, Ramakrishnan},
  booktitle={2017 IEEE International Conference on Big Data (Big Data)},
  pages={273--282},
  year={2017},
  organization={IEEE}
}

@inproceedings{shin2017stexnmf,
  title={Stexnmf: Spatio-temporally exclusive topic discovery for anomalous event detection},
  author={Shin, Sungbok and Choi, Minsuk and Choi, Jinho and Langevin, Scott and Bethune, Christopher and Horne, Philippe and Kronenfeld, Nathan and Kannan, Ramakrishnan and Drake, Barry and Park, Haesun and others},
  booktitle={2017 IEEE International conference on data mining (ICDM)},
  pages={435--444},
  year={2017},
  organization={IEEE}
}

@inproceedings{choi2018topicontiles,
  title={Topicontiles: Tile-based spatio-temporal event analytics via exclusive topic modeling on social media},
  author={Choi, Minsuk and Shin, Sungbok and Choi, Jinho and Langevin, Scott and Bethune, Christopher and Horne, Philippe and Kronenfeld, Nathan and Kannan, Ramakrishnan and Drake, Barry and Park, Haesun and others},
  booktitle={Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems},
  pages={1--11},
  year={2018}
}

@article{kannan2018deep,
  title={Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform},
  author={Kannan, R and Ievlev, AV and Laanait, N and Ziatdinov, MA and Vasudevan, RK and Jesse, S and Kalinin, SV},
  journal={Advanced structural and chemical imaging},
  volume={4},
  number={1},
  pages={1--20},
  year={2018},
  publisher={SpringerOpen}
}

@inproceedings{ballard2018parallel,
  title={Parallel nonnegative cp decomposition of dense tensors},
  author={Ballard, Grey and Hayashi, Koby and Ramakrishnan, Kannan},
  booktitle={2018 IEEE 25th International Conference on High Performance Computing (HiPC)},
  pages={22--31},
  year={2018},
  organization={IEEE}
}

@inproceedings{kaya2018partitioning,
  title={Partitioning and communication strategies for sparse non-negative matrix factorization},
  author={Kaya, Oguz and Kannan, Ramakrishnan and Ballard, Grey},
  booktitle={Proceedings of the 47th International Conference on Parallel Processing},
  pages={1--10},
  year={2018}
}

@inproceedings{xu2018heterogeneity,
  title={A heterogeneity-aware task scheduler for spark},
  author={Xu, Luna and Butt, Ali R and Lim, Seung-Hwan and Kannan, Ramakrishnan},
  booktitle={2018 IEEE International Conference on Cluster Computing (CLUSTER)},
  pages={245--256},
  year={2018},
  organization={IEEE}
}

@inproceedings{young2018hyperspace,
  title={Hyperspace: Distributed bayesian hyperparameter optimization},
  author={Young, M Todd and Hinkle, Jacob and Ramanathan, Arvind and Kannan, Ramakrishnan},
  booktitle={2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)},
  pages={339--347},
  year={2018},
  organization={IEEE}
}

@inproceedings{sao2019communication,
  title={A communication-avoiding 3D sparse triangular solver},
  author={Sao, Piyush and Kannan, Ramakrishnan and Li, Xiaoye Sherry and Vuduc, Richard},
  booktitle={Proceedings of the ACM International Conference on Supercomputing},
  pages={127--137},
  year={2019}
}

@article{blum2019machine,
  title={Machine Learning for Challenging EELS and EDS Spectral Decomposition},
  author={Blum, Thomas and Graves, Jeffery and Zachman, Michael and Kannan, Ramakrishnan and Pan, Xiaoqing and Chi, Miaofang},
  journal={Microscopy and Microanalysis},
  volume={25},
  number={S2},
  pages={180--181},
  year={2019},
  publisher={Cambridge University Press}
}

@article{eswar2019planc,
  title={PLANC: Parallel low rank approximation with non-negativity constraints},
  author={Eswar, Srinivas and Hayashi, Koby and Ballard, Grey and Kannan, Ramakrishnan and Matheson, Michael A and Park, Haesun},
  journal={arXiv preprint arXiv:1909.01149},
  year={2019}
}

@inproceedings{kannan2019planc,
  title={PLANC: Parallel Low Rank Approximations with Non-negativity Constraints},
  author={Kannan, Ramakrishnan and Matheson, Michael and Grey Ballard, Srinivas and Eswar, Koby Hayashi and Park, Haesun},
  booktitle={Workshop on Compiler Techniques for Sparse Tensor Algebra},
  year={2019}
}

@inproceedings{sao2019multifrontal,
  title={Multifrontal Non-negative Matrix Factorization},
  author={Sao, Piyush and Kannan, Ramakrishnan},
  booktitle={International Conference on Parallel Processing and Applied Mathematics},
  pages={543--554},
  year={2019},
  organization={Springer, Cham}
}

@article{young2020distributed,
  title={Distributed Bayesian optimization of deep reinforcement learning algorithms},
  author={Young, M Todd and Hinkle, Jacob D and Kannan, Ramakrishnan and Ramanathan, Arvind},
  journal={Journal of Parallel and Distributed Computing},
  volume={139},
  pages={43--52},
  year={2020},
  publisher={Academic Press}
}

@inproceedings{sao2020supernodal,
  title={A supernodal all-pairs shortest path algorithm},
  author={Sao, Piyush and Kannan, Ramakrishnan and Gera, Prasun and Vuduc, Richard},
  booktitle={Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming},
  pages={250--261},
  year={2020}
}

@inproceedings{hasan2019scalable,
  title={A Scalable Graph Analytics Framework for Programming with Big Data in R (pbdR)},
  author={Hasan, SM Shamimul and Schmidt, Drew and Kannan, Ramakrishnan and Imam, Neena},
  booktitle={2019 IEEE International Conference on Big Data (Big Data)},
  pages={4783--4792},
  year={2019},
  organization={IEEE}
}

@inproceedings{garcia2019learning,
  title={Learning to predict material structure from neutron scattering data},
  author={Garcia-Cardona, Cristina and Kannan, Ramakrishnan and Johnston, Travis and Proffen, Thomas and Page, Katharine and Seal, Sudip K},
  booktitle={2019 IEEE International Conference on Big Data (Big Data)},
  pages={4490--4497},
  year={2019},
  organization={IEEE}
}

@article{kelley2020tensor,
  title={Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy},
  author={Kelley, Kyle P and Li, Linglong and Ren, Yao and Ehara, Yoshitaka and Funakubo, Hiroshi and Somnath, Suhas and Jesse, Stephen and Cao, Ye and Kannan, Ramakrishnan and Vasudevan, Rama K and others},
  journal={npj Computational Materials},
  volume={6},
  number={1},
  pages={1--8},
  year={2020},
  publisher={Nature Publishing Group}
}

@inproceedings{pasricha2021tensorized,
  title={Tensorized Feature Spaces for Feature Explosion},
  author={Pasricha, Ravdeep S and Devineni, Pravallika and Papalexakis, Evangelos E and Kannan, Ramakrishnan},
  booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},
  pages={6298--6304},
  year={2021},
  organization={IEEE}
}

@techreport{hasan2020scalable,
  title={A Scalable Parallel Hypergraph Generator (HyGen)},
  author={Hasan, SM and Imam, Neena and Kannan, Ramakrishnan-Ramki and others},
  year={2020},
  institution={Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States)}
}

@inproceedings{eswar2020distributed,
  title={Distributed-memory parallel symmetric nonnegative matrix factorization},
  author={Eswar, Srinivas and Hayashi, Koby and Ballard, Grey and Kannan, Ramakrishnan and Vuduc, Richard and Park, Haesun},
  booktitle={SC20: International Conference for High Performance Computing, Networking, Storage and Analysis},
  pages={1--14},
  year={2020},
  organization={IEEE}
}

@inproceedings{kannan2020scalable,
  title={Scalable knowledge graph analytics at 136 petaflop/s},
  author={Kannan, Ramakrishnan and Sao, Piyush and Lu, Hao and Herrmannova, Drahomira and Thakkar, Vijay and Patton, Robert and Vuduc, Richard and Potok, Thomas},
  booktitle={SC20: International Conference for High Performance Computing, Networking, Storage and Analysis},
  pages={1--13},
  year={2020},
  organization={IEEE}
}

@article{blum2021machine,
  title={Machine Learning Method Reveals Hidden Strong Metal-Support Interaction in Microscopy Datasets},
  author={Blum, Thomas and Graves, Jeffery and Zachman, Michael J and Polo-Garzon, Felipe and Wu, Zili and Kannan, Ramakrishnan and Pan, Xiaoqing and Chi, Miaofang},
  journal={Small Methods},
  volume={5},
  number={5},
  pages={2100035},
  year={2021}
}

@inproceedings{garcia2020structure,
  title={Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach},
  author={Garcia-Cardona, Cristina and Kannan, Ramakrishnan and Johnston, Travis and Proffen, Thomas and Seal, Sudip K},
  booktitle={2020 IEEE International Conference on Big Data (Big Data)},
  pages={1147--1155},
  year={2020},
  organization={IEEE}
}

@inproceedings{manning2020parallel,
  title={Parallel Hierarchical Clustering using Rank-Two Nonnegative Matrix Factorization},
  author={Manning, Lawton and Ballard, Grey and Kannan, Ramakrishnan and Park, Haesun},
  booktitle={2020 IEEE 27th International Conference on High Performance Computing, Data, and Analytics (HiPC)},
  pages={141--150},
  year={2020},
  organization={IEEE}
}

@article{eswar2021orca,
  title={ORCA: Outlier detection and Robust Clustering for Attributed graphs},
  author={Eswar, Srinivas and Kannan, Ramakrishnan and Vuduc, Richard and Park, Haesun},
  journal={Journal of Global Optimization},
  pages={1--23},
  year={2021},
  publisher={Springer US}
}

@article{blum2021machine,
  title={Machine Learning: Machine Learning Method Reveals Hidden Strong Metal-Support Interaction in Microscopy Datasets (Small Methods 5/2021)},
  author={Blum, Thomas and Graves, Jeffery and Zachman, Michael J and Polo-Garzon, Felipe and Wu, Zili and Kannan, Ramakrishnan and Pan, Xiaoqing and Chi, Miaofang},
  journal={Small Methods},
  volume={5},
  number={5},
  pages={2170020},
  year={2021}
}

@inproceedings{sao2020scalable,
  title={Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters},
  author={Sao, Piyush and Lu, Hao and Kannan, Ramakrishnan and Thakkar, Vijay and Vuduc, Richard and Potok, Thomas},
  booktitle={Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing},
  pages={121--131},
  year={2020}
}

@inproceedings{schuman2021sparse,
  title={Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers},
  author={Schuman, Catherine D and Kay, Bill and Date, Prasanna and Kannan, Ramakrishnan and Sao, Piyush and Potok, Thomas E},
  booktitle={2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  pages={308--311},
  year={2021},
  organization={IEEE}
}

@article{eswar2021planc,
  title={PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints},
  author={Eswar, Srinivas and Hayashi, Koby and Ballard, Grey and Kannan, Ramakrishnan and Matheson, Michael A and Park, Haesun},
  journal={ACM Transactions on Mathematical Software (TOMS)},
  volume={47},
  number={3},
  pages={1--37},
  year={2021},
  publisher={ACM New York, NY, USA}
}

@inproceedings{shivakumar2021efficient,
  title={Efficient Parallel Sparse Symmetric Tucker Decomposition for High-Order Tensors},
  author={Shivakumar, Shruti and Li, Jiajia and Kannan, Ramakrishnan and Aluru, Srinivas},
  booktitle={SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21)},
  pages={193--204},
  year={2021},
  organization={Society for Industrial and Applied Mathematics}
}

@inproceedings{kannan2020scalable,
  title={Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters},
  author={Kannan, Ramakrishnan and Thakkar, Vijay and Vuduc, Richard and Potok, Thomas and others},
  booktitle={HPDC'20: Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing},
  year={2020}
}

@article{alexander2020co,
  title={Co-design center for exascale machine learning technologies (ExaLearn)},
  author={Alexander, Francis J and Ang, James and Bilbrey, Jenna A and Balewski, Jan and Casey, Tiernan and Chard, Ryan and Choi, Jong and Choudhury, Sutanay and Debusschere, Bert and DeGennaro, Anthony M and others},
  journal={The International Journal of High Performance Computing Applications},
  pages={10943420211029302},
  year={2020},
  publisher={SAGE Publications Sage UK: London, England}
}

@article{thakkar2021dense,
  title={Dense semiring linear algebra on modern cuda hardware},
  author={Thakkar, Vijay and Kannan, R and Sao, P and Lu, H and Herrmannova, D and Patton, R and Vuduc, R and Potok, T},
  journal={SIAM Computational Sciences and Engineering. SIAM},
  year={2021}
}

@article{buluc2021randomized,
  title={Randomized algorithms for scientific computing (RASC)},
  author={Buluc, Aydin and Kolda, Tamara G and Wild, Stefan M and Anitescu, Mihai and DeGennaro, Anthony and Jakeman, John and Kamath, Chandrika and Kannan, Ramakrishnan and Lopes, Miles E and Martinsson, Per-Gunnar and others},
  journal={arXiv preprint arXiv:2104.11079},
  year={2021}
}

@article{thakkar2021dense,
  title={Dense semiring linear algebra on modern cuda hardware},
  author={Thakkar, Vijay and Kannan, R and Sao, P and Lu, H and Herrmannova, D and Patton, R and Vuduc, R and Potok, T},
  journal={SIAM Computational Sciences and Engineering. SIAM},
  year={2021}
}

@incollection{kurte2021phoenix,
  title={Phoenix: A Scalable Streaming Hypergraph Analysis Framework},
  author={Kurte, Kuldeep and Imam, Neena and Hasan, SM and Kannan, Ramakrishnan},
  booktitle={Advances in Data Science and Information Engineering},
  pages={3--25},
  year={2021},
  publisher={Springer, Cham}
}

@inproceedings{sao2021scalable,
  title={Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters},
  author={Sao, Piyush and Lu, Hao and Kannan, Ramakrishnan and Thakkar, Vijay and Vuduc, Richard and Potok, Thomas},
  booktitle={Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing},
  pages={121--131},
  year={2021}
}

@inproceedings{abe2021fragile,
  title={Fragile Earth: Accelerating Progress towards Equitable Sustainability},
  author={Abe, Naoki and Buckingham, Kathleen and Dilkina, Bistra and Eftelioglu, Emre and Ganguly, Auroop and Hodson, James and Kannan, Ramakrishnan},
  booktitle={Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
  pages={4102--4103},
  year={2021}
}

@inproceedings{bhaskaran2021science,
  title={Science-Guided Machine Learning for Wall-Modeled Large Eddy Simulation},
  author={Bhaskaran, Rathakrishnan and Kannan, Ramakrishnan and Barr, Brian and Priebe, Stephan},
  booktitle={2021 IEEE International Conference on Big Data (Big Data)},
  pages={1809--1816},
  year={2021},
  organization={IEEE}
}

@inproceedings{lim2021visual,
  title={Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis},
  author={Lim, Seung-Hwan and Chae, Junghoon and Cong, Guojing and Herrmannova, Drahomira and Patton, Robert M and Kannan, Ramakrishnan and Potok, Thomas E},
  booktitle={2021 IEEE International Conference on Big Data (Big Data)},
  pages={4381--4386},
  year={2021},
  organization={IEEE}
}

@inproceedings{abe2022fragile,
  title={Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice},
  author={Abe, Naoki and Buckingham, Kathleen and Dilkina, Bistra and Eftelioglu, Emre and Ganguly, Auroop R and Hodson, James and Kannan, Ramakrishnan and Yu, Rose},
  booktitle={Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages={4866--4867},
  year={2022}
}

@inproceedings{kannan2022exaflops,
  title={Exaflops biomedical knowledge graph analytics},
  author={Kannan, Ramakrishnan and Sao, Piyush and Lu, Hao and Kurzak, Jakub and Schenk, Gundolf and Shi, Yongmei and Lim, Seung--Hwan and Israni, Sharat and Thakkar, Vijay and Cong, Guojing and others},
  booktitle={SC22: International Conference for High Performance Computing, Networking, Storage and Analysis},
  pages={1--11},
  year={2022},
  organization={IEEE}
}

@inproceedings{tabassum2022li,
  title={Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning},
  author={Tabassum, Anika and Muralidhar, Nikhil and Kannan, Ramakrishnan and Allu, Srikanth},
  booktitle={NeurIPS 2022 AI for Science: Progress and Promises},
  year={2022}
}

@inproceedings{tabassum2022matphase,
  title={MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning},
  author={Tabassum, Anika and Muralidhar, Nikhil and Kannan, Ramakrishnan and Allu, Srikanth},
  booktitle={2022 IEEE International Conference on Big Data (Big Data)},
  pages={1936--1941},
  year={2022},
  organization={IEEE}
}

@inproceedings{eswar2023distributed,
  title={Distributed-Memory Parallel JointNMF},
  author={Eswar, Srinivas and Cobb, Benjamin and Hayashi, Koby and Kannan, Ramakrishnan and Ballard, Grey and Vuduc, Richard and Park, Haesun},
  booktitle={Proceedings of the 37th International Conference on Supercomputing},
  pages={301--312},
  year={2023}
}

@inproceedings{wang2023parallel,
  title={A parallel machine learning workflow for neutron scattering data analysis},
  author={Wang, Tianle and Seal, Sudip K and Kannan, Ramakrishnan and Garcia-Cardona, Cristina and Proffen, Thomas and Jha, Shantenu},
  booktitle={2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  pages={795--798},
  year={2023},
  organization={IEEE}
}

@inproceedings{abe2023fragile,
  title={Fragile Earth: AI for Climate Sustainability-From Wildfire Disaster Management to Public Health and Beyond},
  author={Abe, Naoki and Buckingham, Kathleen and Chen, Yuzhou and Dilkina, Bistra and Eftelioglu, Emre and Ganguly, Auroop R and Gel, Yulia R and Hodson, James and Kannan, Ramakrishnan and Lee, Huikyo and others},
  booktitle={Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages={5845--5846},
  year={2023}
}

@inproceedings{lu2023optimizing,
  title={Optimizing Communication in 2D Grid-Based MPI Applications at Exascale},
  author={Lu, Hao and Sao, Piyush and Matheson, Michael and Kannan, Ramakrishnan and Wang, Feiyi and Potok, Thomas},
  booktitle={Proceedings of the 30th European MPI Users' Group Meeting},
  pages={1--11},
  year={2023}
}

@article{alexander2020co,
  title={Co-design center for exascale machine learning technologies (ExaLearn)},
  author={Alexander, Francis J and Ang, James and Bilbrey, Jenna A and Balewski, Jan and Casey, Tiernan and Chard, Ryan and Choi, Jong and Choudhury, Sutanay and Debusschere, Bert and DeGennaro, Anthony M and others},
  journal={The International Journal of High Performance Computing Applications},
  pages={10943420211029302},
  year={2020},
  publisher={SAGE Publications Sage UK: London, England}
}

@incollection{garcia2022structure,
  title={Structure Prediction from Scattering Profiles: A Neutron-Scattering Use-Case},
  author={Garcia-Cardona, Cristina and Kannan, Ramakrishnan and Johnston, Travis and Proffen, Thomas and Seal, Sudip K},
  booktitle={Knowledge Guided Machine Learning},
  pages={287--304},
  year={2022},
  publisher={Chapman and Hall/CRC}
}

@incollection{graves2022funnl,
  title={FUNNL: Fast Nonlinear Nonnegative Unmixing for Alternate Energy Systems},
  author={Graves, Jeffrey A and Blum, Thomas F and Sao, Piyush and Chi, Miaofang and Kannan, Ramakrishnan},
  booktitle={Knowledge Guided Machine Learning},
  pages={261--286},
  year={2022},
  publisher={Chapman and Hall/CRC}
}

@article{shivakumar2023sparse,
  title={Sparse Symmetric Format for Tucker Decomposition},
  author={Shivakumar, Shruti and Li, Jiajia and Kannan, Ramakrishnan and Aluru, Srinivas},
  journal={IEEE Transactions on Parallel and Distributed Systems},
  year={2023},
  publisher={IEEE}
}

@inproceedings{kannan2023deep,
  title={A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations},
  author={Kannan, Ramakrishnan and Garcia-Cardona, Cristina and Radhakrishnan, Balasubramaniam and Seal, Sudip K},
  booktitle={2023 IEEE International Conference on Big Data (BigData)},
  pages={1744--1753},
  year={2023},
  organization={IEEE}
}

@inproceedings{srikishan2024reinforcement,
  title={Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation},
  author={Srikishan, Bharat and Tabassum, Anika and Allu, Srikanth and Kannan, Ramakrishnan and Muralidhar, Nikhil},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={13},
  pages={15066--15074},
  year={2024}
}

@techreport{tabassum2024knowledge,
  title={Knowledge Graph Embedding using Large Language Models for COVID-19},
  author={Tabassum, Anika and Kannan, Ramakrishnan and Yin, Junqi and Lim, Seung-Hwan and Cong, Guojing and Hasan, SM and Patton, Robert and Potok, Thomas E},
  year={2024},
  institution={Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak~…}
}

@article{wei2024robustness,
  title={Robustness of graph embedding methods for community detection},
  author={Wei, Zhi-Feng and Moriano, Pablo and Kannan, Ramakrishnan},
  journal={arXiv preprint arXiv:2405.00636},
  year={2024}
}

@inproceedings{soh2024accelerated,
  title={Accelerated Constrained Sparse Tensor Factorization on Massively Parallel Architectures},
  author={Soh, Yongseok and Kannan, Ramakrishnan and Sao, Piyush and Choi, Jee},
  booktitle={Proceedings of the 53rd International Conference on Parallel Processing},
  pages={107--116},
  year={2024}
}

@inproceedings{eftelioglu2024fragile,
  title={Fragile Earth: Generative and Foundational Models for Sustainable Development},
  author={Eftelioglu, Emre and Dilkina, Bistra and Abe, Naoki and Kannan, Ramakrishnan and Chen, Yuzhou and Gel, Yulia R and Buckingham, Kathleen and Ganguly, Auroop and Hodson, James and Mao, Jiafu},
  booktitle={Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages={6710--6711},
  year={2024}
}