Cloud federation in a layered service model. - David Villegas; Norman Bobroff; Ivan Rodero; Javier Delgado; Yanbin Liu; Aditya Devarakonda; Liana Fong; Seyed Masoud Sadjadi; Manish Parashar (J. Comput. Syst. Sci., 2012)

Cloud Paradigms and Practices for Computational and Data-Enabled Science and Engineering. - Manish Parashar; Moustafa AbdelBaky; Ivan Rodero; Aditya Devarakonda (Comput. Sci. Eng., 2013)

Architecting an autograder for parallel code. - Razvan Carbunescu; Aditya Devarakonda; James Demmel; Steven I. Gordon; Jay Alameda; Susan Mehringer (XSEDE, 2014)

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. - Alex Gittens; Aditya Devarakonda; Evan Racah; Michael F. Ringenburg; Lisa Gerhardt; Jey Kottalam; Jialin Liu 002; Kristyn J. Maschhoff; Shane Canon; Jatin Chhugani; Pramod Sharma; Jiyan Yang; et al. (IEEE BigData, 2016)

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. - Alex Gittens; Aditya Devarakonda; Evan Racah; Michael F. Ringenburg; Lisa Gerhardt; Jey Kottalam; Jialin Liu 002; Kristyn J. Maschhoff; Shane Canon; Jatin Chhugani; Pramod Sharma; Jiyan Yang; et al. (CoRR, 2016)

Avoiding Communication in Proximal Methods for Convex Optimization Problems. - Saeed Soori; Aditya Devarakonda; James Demmel; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (CoRR, 2017)

AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks. - Aditya Devarakonda; Maxim Naumov; Michael Garland (CoRR, 2017)

Reducing Communication in Proximal Newton Methods for Sparse Least Squares Problems. - Saeed Soori; Aditya Devarakonda; Zachary Blanco; James Demmel; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (ICPP, 2018)

Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization. - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (IPDPS, 2018)

Avoiding Communication in First Order Methods for Optimization. - Aditya Devarakonda (2018)

Avoiding Communication in Primal and Dual Block Coordinate Descent Methods. - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (SIAM J. Sci. Comput., 2019)

Avoiding Communication in Logistic Regression. - Aditya Devarakonda; James Demmel (HiPC, 2020)

Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths. - Aditya Devarakonda; Grey Ballard (PP, 2024)

Scalable Dual Coordinate Descent for Kernel Methods. - Zishan Shao; Aditya Devarakonda (HPC Asia, 2025)

Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization. - Aditya Devarakonda; Ramakrishnan Kannan (CoRR, 2025)

DistShap: Scalable GNN Explanations with Distributed Shapley Values. - Selahattin Akkas; Aditya Devarakonda; Ariful Azad (CoRR, 2025)