Recertification: A Technique to Improve Services in PKI. - Ravi Mukkamala; Satyam Das; Mahantesh Halappanavar (DBSec, 2002)

Security in Distributed Digital Libraries: Issues and Challenges . - Somasekhar Vemulapalli; Mahantesh Halappanavar; Ravi Mukkamala (ICPP Workshops, 2002)

ECPV: Efficient Certificate Path Validation in Public-key Infrastructure. - Mahantesh Halappanavar; Ravi Mukkamala (DBSec, 2003)

Efficient Parallel Implementations of Binomial Tree Option Price Valuation. - Mahantesh Halappanavar; Amit Kumar 024; Ravi Mukkamala; Mohammad Zubair (PDCCS, 2008)

A common application platform for the SURAgrid (CAP). - Mahantesh Halappanavar; John-Paul Robinson; Enis Afgan; Mary Fran Yafchak; Purushotham V. Bangalore (Mardi Gras Conference, 2008)

Algorithms for Vertex-Weighted Matching in Graphs. - Mahantesh Halappanavar (2009)

Tolerating correlated failures for generalized Cartesian distributions via bipartite matching. - Nawab Ali; Sriram Krishnamoorthy; Mahantesh Halappanavar; Jeff Daily (Conf. Computing Frontiers, 2011)

Distributed-Memory Parallel Algorithms for Matching and Coloring. - Ümit V. Çatalyürek; Florin Dobrian; Assefaw Hadish Gebremedhin; Mahantesh Halappanavar; Alex Pothen (IPDPS Workshops, 2011)

Techniques for Improving Filters in Power Grid Contingency Analysis. - Robert Adolf; David Haglin; Mahantesh Halappanavar; Yousu Chen; Zhenyu Huang 001 (MLDM, 2011)

Computing maximum matching in parallel on bipartite graphs: worth the effort? - Ariful Azad; Mahantesh Halappanavar; Florin Dobrian; Alex Pothen (IA3@SC, 2011)

Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems. - Chad Scherrer; Mahantesh Halappanavar; Ambuj Tewari; David Haglin (ICML, 2012)

A Novel Multithreaded Algorithm for Extracting Maximal Chordal Subgraphs. - Mahantesh Halappanavar; John Feo; Kathryn Dempsey; Hesham H. Ali; Sanjukta Bhowmick (ICPP, 2012)

Multithreaded Algorithms for Maxmum Matching in Bipartite Graphs. - Ariful Azad; Mahantesh Halappanavar; Sivasankaran Rajamanickam; Erik G. Boman; Arif M. Khan; Alex Pothen (IPDPS, 2012)

Feature Clustering for Accelerating Parallel Coordinate Descent. - Chad Scherrer; Ambuj Tewari; Mahantesh Halappanavar; David Haglin (NIPS, 2012)

Towards Efficient N-x Contingency Selection Using Group betweenness Centrality. - Mahantesh Halappanavar; Yousu Chen; Robert Adolf; David Haglin; Zhenyu Huang 001; Mark Rice 002 (SC Companion, 2012)

A multithreaded algorithm for network alignment via approximate matching. - Arif M. Khan; David F. Gleich; Alex Pothen; Mahantesh Halappanavar (SC, 2012)

Graph Coloring Algorithms for Muti-core and Massively Multithreaded Architectures - Ümit V. Çatalyürek; John Feo; Assefaw Hadish Gebremedhin; Mahantesh Halappanavar; Alex Pothen (CoRR, 2012)

Approximate weighted matching on emerging manycore and multithreaded architectures. - Mahantesh Halappanavar; John Feo; Oreste Villa; Antonino Tumeo; Alex Pothen (Int. J. High Perform. Comput. Appl., 2012)

Graph coloring algorithms for multi-core and massively multithreaded architectures. - Ümit V. Çatalyürek; John Feo; Assefaw Hadish Gebremedhin; Mahantesh Halappanavar; Alex Pothen (Parallel Comput., 2012)

Graph coarsening for path finding in cybersecurity graphs. - Emilie Hogan; John R. Johnson; Mahantesh Halappanavar (CSIIRW, 2013)

Towards a network-of-networks framework for cyber security. - Mahantesh Halappanavar; Sutanay Choudhury; Emilie Hogan; Peter Hui; John R. Johnson; Indrajit Ray; Lawrence B. Holder (ISI, 2013)

Graph analytics for signature discovery. - Emilie Hogan; John R. Johnson; Mahantesh Halappanavar; Chaomei Lo (ISI, 2013)

Towards effective clustering techniques for the analysis of electric power grids. - Emilie Hogan; Eduardo Cotilla Sanchez; Mahantesh Halappanavar; Shaobu Wang; Patrick Mackey; Paul Hines; Zhenyu Huang 001 (HiPCNA-PG@SC, 2013)

Towards a Networks-of-Networks Framework for Cyber Security - Mahantesh Halappanavar; Sutanay Choudhury; Emilie Hogan; Peter Hui; John R. Johnson; Indrajit Ray; Lawrence B. Holder (CoRR, 2013)

Multi-Fault Tolerance for Cartesian Data Distributions. - Nawab Ali; Sriram Krishnamoorthy; Mahantesh Halappanavar; Jeff Daily (Int. J. Parallel Program., 2013)

Scaling graph community detection on the Tilera many-core architecture. - Daniel G. Chavarría-Miranda; Mahantesh Halappanavar; Ananth Kalyanaraman (HiPC, 2014)

Parallel Heuristics for Scalable Community Detection. - Hao Lu 001; Mahantesh Halappanavar; Ananth Kalyanaraman; Sutanay Choudhury (IPDPS Workshops, 2014)

New Effective Multithreaded Matching Algorithms. - Fredrik Manne; Mahantesh Halappanavar (IPDPS, 2014)

On parallel push-relabel based algorithms for bipartite maximum matching. - Johannes Langguth; Ariful Azad; Mahantesh Halappanavar; Fredrik Manne (Parallel Comput., 2014)

Optimizing irregular applications for energy and performance on the Tilera many-core architecture. - Daniel G. Chavarría-Miranda; Ajay Panyala; Mahantesh Halappanavar; Joseph B. Manzano; Antonino Tumeo (Conf. Computing Frontiers, 2015)

Optimizing Approximate Weighted Matching on Nvidia Kepler K40. - Md. Naim; Fredrik Manne; Mahantesh Halappanavar; Antonino Tumeo; Johannes Langguth (HiPC, 2015)

On the Impact of Execution Models: A Case Study in Computational Chemistry. - Daniel G. Chavarría-Miranda; Mahantesh Halappanavar; Sriram Krishnamoorthy; Joseph B. Manzano; Abhinav Vishnu; Adolfy Hoisie (IPDPS Workshops, 2015)

Balanced Coloring for Parallel Computing Applications. - Hao Lu 001; Mahantesh Halappanavar; Daniel G. Chavarría-Miranda; Assefaw Hadish Gebremedhin; Ananth Kalyanaraman (IPDPS, 2015)

Towards efficient scheduling of data intensive high energy physics workflows. - Mahantesh Halappanavar; Malachi Schram; Luis de la Torre 001; Kevin J. Barker; Nathan R. Tallent; Darren J. Kerbyson (WORKS@SC, 2015)

Codesign Lessons Learned from Implementing Graph Matching on Multithreaded Architectures. - Mahantesh Halappanavar; Alex Pothen; Ariful Azad; Fredrik Manne; Johannes Langguth; Arif M. Khan (Computer, 2015)

A Network-of-Networks Model for Electrical Infrastructure Networks. - Mahantesh Halappanavar; Eduardo Cotilla Sanchez; Emilie Hogan; Daniel Duncan; Zhenyu (Henry) Huang; Paul D. H. Hines (CoRR, 2015)

Comparative Studies of Clustering Techniques for Real-Time Dynamic Model Reduction. - Emilie Hogan; Eduardo Cotilla Sanchez; Mahantesh Halappanavar; Zhenyu Huang 001; Guang Lin 001; Shuai Lu; Shaobu Wang (CoRR, 2015)

A new augmentation based algorithm for extracting maximal chordal subgraphs. - Sanjukta Bhowmick; Tzu-Yi Chen; Mahantesh Halappanavar (J. Parallel Distributed Comput., 2015)

Parallel heuristics for scalable community detection. - Hao Lu 001; Mahantesh Halappanavar; Ananth Kalyanaraman (Parallel Comput., 2015)

Formal Approach for Resilient Reachability based on End-System Route Agility. - Usman Rauf; Fida Gillani; Ehab Al-Shaer; Mahantesh Halappanavar; Samrat Chatterjee; Christopher S. Oehmen (MTD@CCS, 2016)

Accelerating the mining of influential nodes in complex networks through community detection. - Mahantesh Halappanavar; Arun V. Sathanur; Apurba K. Nandi (Conf. Computing Frontiers, 2016)

Modeling the Impact of Silicon Photonics on Graph Analytics. - Nathan R. Tallent; Kevin J. Barker; Daniel G. Chavarría-Miranda; Antonino Tumeo; Mahantesh Halappanavar; Andrés Márquez 001; Darren J. Kerbyson; Adolfy Hoisie (NAS, 2016)

Designing scalable b-Matching algorithms on distributed memory multiprocessors by approximation. - Arif M. Khan; Alex Pothen; Md. Mostofa Ali Patwary; Mahantesh Halappanavar; Nadathur Rajagopalan Satish; Narayanan Sundaram; Pradeep Dubey (SC, 2016)

On Stable Marriages and Greedy Matchings. - Fredrik Manne; Md. Naim; Håkon Lerring; Mahantesh Halappanavar (CSC, 2016)

Influence Maximization on Complex Networks with Intrinsic Nodal Activation. - Arun V. Sathanur; Mahantesh Halappanavar (SocInfo (2), 2016)

Fast Uncovering of Graph Communities on a Chip: Toward Scalable Community Detection on Multicore and Manycore Platforms. - Ananth Kalyanaraman; Mahantesh Halappanavar; Daniel G. Chavarría-Miranda; Hao Lu 001; Karthi Duraisamy; Partha Pratim Pande (Found. Trends Electron. Des. Autom., 2016)

Efficient Approximation Algorithms for Weighted b-Matching. - Arif M. Khan; Alex Pothen; Md. Mostofa Ali Patwary; Nadathur Rajagopalan Satish; Narayanan Sundaram; Fredrik Manne; Mahantesh Halappanavar; Pradeep Dubey (SIAM J. Sci. Comput., 2016)

Approximate Computing Techniques for Iterative Graph Algorithms. - Ajay Panyala; Omer Subasi; Mahantesh Halappanavar; Ananth Kalyanaraman; Daniel G. Chavarría-Miranda; Sriram Krishnamoorthy (HiPC, 2017)

Scalable static and dynamic community detection using Grappolo. - Mahantesh Halappanavar; Hao Lu 001; Ananth Kalyanaraman; Antonino Tumeo (HPEC, 2017)

FlipNet: Modeling Covert and Persistent Attacks on Networked Resources. - Sudip Saha; Anil Vullikanti; Mahantesh Halappanavar (ICDCS, 2017)

Community Detection on the GPU. - Md. Naim; Fredrik Manne; Mahantesh Halappanavar; Antonino Tumeo (IPDPS, 2017)

Introduction to GraML Workshop. - Antonino Tumeo; Mahantesh Halappanavar; John Feo (IPDPS Workshops, 2017)

Towards Efficient Resource Allocation for Distributed Workflows Under Demand Uncertainties. - Ryan D. Friese; Mahantesh Halappanavar; Arun V. Sathanur; Malachi Schram; Darren J. Kerbyson; Luis de la Torre 001 (JSSPP, 2017)

Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks. - Arun V. Sathanur; Mahantesh Halappanavar; Yi Shi 001; Yalin E. Sagduyu (CoRR, 2017)

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture. - Ajay Panyala; Daniel G. Chavarría-Miranda; Joseph B. Manzano; Antonino Tumeo; Mahantesh Halappanavar (J. Parallel Distributed Comput., 2017)

Comparative study of clustering techniques for real-time dynamic model reduction. - Emilie Purvine; Eduardo Cotilla Sanchez; Mahantesh Halappanavar; Zhenyu Huang 001; Guang Lin 001; Shuai Lu; Shaobu Wang (Stat. Anal. Data Min., 2017)

AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids. - Yu Hong Yeung; Alex Pothen; Mahantesh Halappanavar; Zhenyu Huang 001 (SIAM J. Sci. Comput., 2017)

Algorithms for Balanced Graph Colorings with Applications in Parallel Computing. - Hao Lu 001; Mahantesh Halappanavar; Daniel G. Chavarría-Miranda; Assefaw Hadish Gebremedhin; Ajay Panyala; Ananth Kalyanaraman (IEEE Trans. Parallel Distributed Syst., 2017)

Optimizing Distributed Data-Intensive Workflows. - Ryan D. Friese; Nathan R. Tallent; Malachi Schram; Mahantesh Halappanavar; Kevin J. Barker (CLUSTER, 2018)

Scalable Distributed Memory Community Detection Using Vite. - Sayan Ghosh; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman; Assefaw H. Gebremedhin (HPEC, 2018)

Distributed Louvain Algorithm for Graph Community Detection. - Sayan Ghosh; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman; Hao Lu 001; Daniel G. Chavarría-Miranda; Arif Khan 005; Assefaw Hadish Gebremedhin (IPDPS, 2018)

Introduction to GraML 2018. - Antonino Tumeo; Mahantesh Halappanavar; John Feo; Assefaw Hadish Gebremedhin; Abhinav Vishnu (IPDPS Workshops, 2018)

Stochastic Programming Approach for Resource Selection Under Demand Uncertainty. - Tanveer Hossain Bhuiyan; Mahantesh Halappanavar; Ryan D. Friese; Hugh R. Medal; Luis de la Torre 001; Arun V. Sathanur; Nathan R. Tallent (JSSPP, 2018)

MiniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems. - Sayan Ghosh; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman; Assefaw H. Gebremedhin (PMBS@SC, 2018)

Adaptive anonymization of data using b-edge cover. - Arif Khan 005; Krzysztof Choromanski; Alex Pothen; S. M. Ferdous; Mahantesh Halappanavar; Antonino Tumeo (SC, 2018)

Dynamic graphs, community detection, and Riemannian geometry. - Craig Bakker; Mahantesh Halappanavar; Arun V. Sathanur (Appl. Netw. Sci., 2018)

Guest Editorial: Advances in Parallel Graph Processing: Algorithms, Architectures, and Application Frameworks. - Ananth Kalyanaraman; Mahantesh Halappanavar (IEEE Trans. Multi Scale Comput. Syst., 2018)

Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks. - Arun V. Sathanur; Mahantesh Halappanavar; Yi Shi 001; Yalin E. Sagduyu (Social Network Based Big Data Analysis and Applications, 2018)

Fast and Scalable Implementations of Influence Maximization Algorithms. - Marco Minutoli; Mahantesh Halappanavar; Ananth Kalyanaraman; Arun V. Sathanur; Ryan S. McClure; Jason E. McDermott (CLUSTER, 2019)

Mapping Arbitrarily Sparse Two-Body Interactions on One-Dimensional Quantum Circuits. - Arif M. Khan; Mahantesh Halappanavar; Tobias Hagge; Karol Kowalski; Alex Pothen; Sriram Krishnamoorthy (HiPC, 2019)

Distributed Direction-Optimizing Label Propagation for Community Detection. - Xu Liu 015; Jesun Sahariar Firoz; Marcin Zalewski; Mahantesh Halappanavar; Kevin J. Barker; Andrew Lumsdaine; Assefaw H. Gebremedhin (HPEC, 2019)

Scaling and Quality of Modularity Optimization Methods for Graph Clustering. - Sayan Ghosh; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman (HPEC, 2019)

Exploring MPI Communication Models for Graph Applications Using Graph Matching as a Case Study. - Sayan Ghosh; Mahantesh Halappanavar; Ananth Kalyanaraman; Arif Khan 005; Assefaw H. Gebremedhin (IPDPS, 2019)

A generative graph model for electrical infrastructure networks. - Sinan G. Aksoy; Emilie Purvine; Eduardo Cotilla Sanchez; Mahantesh Halappanavar (J. Complex Networks, 2019)

A 2/3-Approximation Algorithm for Vertex Weighted Matching in Bipartite Graphs. - Florin Dobrian; Mahantesh Halappanavar; Alex Pothen; Ahmed Al-Herz (SIAM J. Sci. Comput., 2019)

Direction-optimizing label propagation and its application to community detection. - Xu T. Liu; Mahantesh Halappanavar; Kevin J. Barker; Andrew Lumsdaine; Assefaw H. Gebremedhin (CF, 2020)

TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure. - Sayan Ghosh; Mahantesh Halappanavar (HPEC, 2020)

cuRipples: influence maximization on multi-GPU systems. - Marco Minutoli; Maurizio Drocco; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman (ICS, 2020)

Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation. - Reet Barik; Marco Minutoli; Mahantesh Halappanavar; Nathan R. Tallent; Ananth Kalyanaraman (IISWC, 2020)

Message from the workshop chairs. - Scott McMillan; Manoj Kumar 006; Danai Koutra; Mahantesh Halappanavar; Tim Mattson; Antonino Tumeo (IPDPS Workshops, 2020)

Preempt: scalable epidemic interventions using submodular optimization on multi-GPU systems. - Marco Minutoli; Prathyush Sambaturu; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman; Anil Vullikanti (SC, 2020)

Introduction to the TOPC Special Issue on Innovations in Systems for Irregular Applications, Part 1. - Antonino Tumeo; Fabrizio Petrini; John Feo; Mahantesh Halappanavar (ACM Trans. Parallel Comput., 2020)

Introduction to the TOPC Special Issue on Innovations in Systems for Irregular Applications, Part 2. - Antonino Tumeo; Fabrizio Petrini; John Feo; Mahantesh Halappanavar (ACM Trans. Parallel Comput., 2020)

A Parallel Approximation Algorithm for Maximizing Submodular b-Matching. - S. M. Ferdous; Alex Pothen; Arif Khan 005; Ajay Panyala; Mahantesh Halappanavar (ACDA, 2021)

Transfer-Learnt Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data. - Milan Jain; Khushboo Gupta; Arun V. Sathanur; Vikas Chandan; Mahantesh Halappanavar (ACC, 2021)

Graph analytics in the exascale era. - Mahantesh Halappanavar; Marco Minutoli; Sayan Ghosh (CF, 2021)

V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities. - Siddhartha Shankar Das; Edoardo Serra; Mahantesh Halappanavar; Alex Pothen; Ehab Al-Shaer (DSAA, 2021)

On the Stochastic Stability of Deep Markov Models. - Ján Drgona; Sayak Mukherjee; Jiaxin Zhang 005; Frank Liu 001; Mahantesh Halappanavar (NeurIPS, 2021)

Single-node partitioned-memory for huge graph analytics: cost and performance trade-offs. - Sayan Ghosh; Nathan R. Tallent; Marco Minutoli; Mahantesh Halappanavar; Ramesh Peri; Ananth Kalyanaraman (SC, 2021)

cuTS: scaling subgraph isomorphism on distributed multi-GPU systems using trie based data structure. - Lizhi Xiang; Arif Khan 005; Edoardo Serra; Mahantesh Halappanavar; Aravind Sukumaran-Rajam (SC, 2021)

Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification. - Jingbo Sun; Li Yang 009; Jiaxin Zhang 005; Frank Liu 001; Mahantesh Halappanavar; Deliang Fan; Yu Cao 001 (CSSL, 2021)

A Parallel Approximation Algorithm for Maximizing Submodular b-Matching. - S. M. Ferdous; Alex Pothen; Arif Khan 005; Ajay Panyala; Mahantesh Halappanavar (CoRR, 2021)

Risk-averse bi-level stochastic network interdiction model for cyber-security risk management. - Tanveer Hossain Bhuiyan; Hugh R. Medal; Apurba K. Nandi; Mahantesh Halappanavar (Int. J. Crit. Infrastructure Prot., 2021)

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications. - Seher Acer; Ariful Azad; Erik G. Boman; Aydin Buluç; Karen D. Devine; S. M. Ferdous; Nitin Gawande; Sayan Ghosh; Mahantesh Halappanavar; Ananth Kalyanaraman; Arif Khan 005; Marco Minutoli; et al. (Int. J. High Perform. Comput. Appl., 2021)

HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures. - Xinyu Chen; Marco Minutoli; Jiannan Tian; Mahantesh Halappanavar; Ananth Kalyanaraman; Dingwen Tao (PACT, 2022)

Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification. - Jingbo Sun; Li Yang 009; Jiaxin Zhang 005; Frank Liu 001; Mahantesh Halappanavar; Deliang Fan; Yu Cao 001 (AAAI, 2022)

VWC-BERT: Scaling Vulnerability-Weakness-Exploit Mapping on Modern AI Accelerators. - Siddhartha Shankar Das; Mahantesh Halappanavar; Antonino Tumeo; Edoardo Serra; Alex Pothen; Ehab Al-Shaer (IEEE Big Data, 2022)

Neural Lyapunov Differentiable Predictive Control. - Sayak Mukherjee; Ján Drgona; Aaron Tuor; Mahantesh Halappanavar; Draguna L. Vrabie (CDC, 2022)

Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. - Wenceslao Shaw-Cortez; Ján Drgona; Aaron Tuor; Mahantesh Halappanavar; Draguna L. Vrabie (CDC, 2022)

IMpart: A Partitioning-based Parallel Approach to Accelerate Influence Maximization. - Reet Barik; Marco Minutoli; Mahantesh Halappanavar; Ananth Kalyanaraman (HIPC, 2022)

Scalable and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method. - Prathyush Sambaturu; Marco Minutoli; Mahantesh Halappanavar; Ananth Kalyanaraman; Anil Vullikanti (IJCAI, 2022)

Learning Stochastic Parametric Differentiable Predictive Control Policies. - Ján Drgona; Sayak Mukherjee; Aaron Tuor; Mahantesh Halappanavar; Draguna L. Vrabie (CoRR, 2022)

Direction-optimizing Label Propagation Framework for Structure Detection in Graphs: Design, Implementation, and Experimental Analysis. - Xu T. Liu; Andrew Lumsdaine; Mahantesh Halappanavar; Kevin J. Barker; Assefaw Hadish Gebremedhin (ACM J. Exp. Algorithmics, 2022)

Towards scaling community detection on distributed-memory heterogeneous systems. - Nitin Gawande; Sayan Ghosh; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman (Parallel Comput., 2022)

Characterizing Performance of Graph Neighborhood Communication Patterns. - Sayan Ghosh; Nathan R. Tallent; Mahantesh Halappanavar (IEEE Trans. Parallel Distributed Syst., 2022)

FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix. - Gopikrishnan Raveendran Nair; Han-Sok Suh; Mahantesh Halappanavar; Frank Liu 001; Jae-sun Seo; Yu Cao 001 (DATE, 2023)

Structural Validation of Synthetic Power Distribution Networks Using the Multiscale Flat Norm. - Rounak Meyur; Kostiantyn Lyman; Bala Krishnamoorthy; Mahantesh Halappanavar (ICCS (4), 2023)

Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains. - Buddhika Nettasinghe; Samrat Chatterjee; Ramakrishna Tipireddy; Mahantesh M. Halappanavar (ICML, 2023)

Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning. - Katarzyna Borowiec; Dan Lu 001; Vikas Chandan; Samrat Chatterjee; Pradeep Ramuhalli; Ramakrishna Tipireddy; Mahantesh Halappanavar; Frank Liu 001 (ICMLA, 2023)

Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation. - Luis de la Torre 001; Mahantesh Halappanavar (JSSPP, 2023)

Faster approximate subgraph counts with privacy. - Dung Nguyen 002; Mahantesh Halappanavar; Venkatesh Srinivasan 001; Anil Vullikanti (NeurIPS, 2023)

AMG Preconditioners based on Parallel Hybrid Coarsening and Multi-objective Graph Matching. - Pasqua D'Ambra; Fabio Durastante; S. M. Ferdous; Salvatore Filippone; Mahantesh Halappanavar; Alex Pothen (PDP, 2023)

cuAlign: Scalable Network Alignment on GPU Accelerators. - Lizhi Xiang; Arif M. Khan; S. M. Ferdous; Aravind Sukumaran-Rajam; Mahantesh Halappanavar (SC Workshops, 2023)

Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties. - Ashutosh Dutta; Samrat Chatterjee; Arnab Bhattacharya 008; Mahantesh Halappanavar (CoRR, 2023)

Perspectives on AI Architectures and Co-design for Earth System Predictability. - Maruti K. Mudunuru; James A. Ang; Mahantesh Halappanavar; Simon D. Hammond; Maya B. Gokhale; James C. Hoe; Tushar Krishna; Sarat Sreepathi; Matthew R. Norman; Ivy Bo Peng; Philip W. Jones (CoRR, 2023)

There is more to graphs than meets the eye: Learning universal features with self-supervision. - Laya Das; Sai Munikoti; Mahantesh Halappanavar (CoRR, 2023)

Streaming Algorithms for Weighted k-Disjoint Matchings. - S. M. Ferdous; Bhargav Samineni; Alex Pothen; Mahantesh Halappanavar; Bala Krishnamoorthy (CoRR, 2023)

Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach. - Wenceslao Shaw-Cortez; Ján Drgona; Draguna L. Vrabie; Mahantesh Halappanavar (CoRR, 2023)

Fused Breadth-First Probabilistic Traversals on Distributed GPU Systems. - Reece Neff; Mostafa Eghbali Zarch; Marco Minutoli; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman; Michela Becchi (CoRR, 2023)

Semi-supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. - Yu Wang 167; Yuxuan Yin; Karthik Somayaji N. S.; Ján Drgona; Malachi Schram; Mahantesh Halappanavar; Frank Liu 001; Peng Li 001 (AAAI, 2024)

Exploring the Landscape of Distributed Graph Clustering on Leadership Supercomputers. - Naw Safrin Sattar; Abigail Kapocius; Hao Lu 001; Mahantesh Halappanavar; Feiyi Wang (IEEE Big Data, 2024)

Semi-Streaming Algorithms for Weighted k-Disjoint Matchings. - S. M. Ferdous; Bhargav Samineni; Alex Pothen; Mahantesh Halappanavar; Bala Krishnamoorthy (ESA, 2024)

FuseIM: Fusing Probabilistic Traversals for Influence Maximization on Exascale Systems. - Reece Neff; Mostafa Eghbali Zarch; Marco Minutoli; Mahantesh Halappanavar; Antonino Tumeo; Ananth Kalyanaraman; Michela Becchi (ICS, 2024)

Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing. - S. M. Ferdous; Reece Neff; Bo Peng; Salman Shuvo; Marco Minutoli; Sayak Mukherjee; Karol Kowalski; Michela Becchi; Mahantesh Halappanavar (IPDPS, 2024)

Distributed Multi-GPU Community Detection on Exascale Computing Platforms. - Naw Safrin Sattar; Hao Lu 001; Feiyi Wang; Mahantesh Halappanavar (IPDPS (Workshops), 2024)

AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. - Siddhartha Shankar Das; S. M. Ferdous; Mahantesh M. Halappanavar; Edoardo Serra; Alex Pothen (KDD, 2024)

Using Isoefficiency as a Metric to Assess Disaggregated Memory Systems for High Performance Computing. - Anusha Devulapally; Mahantesh Halappanavar; Amit Puri; Vijaykrishnan Narayanan; Andres Marquez 001 (MEMSYS, 2024)

A Performance and Energy Study of GPU-Resident Preconditioners for Conjugate Gradient Solvers: In the Context of Existing and Novel Approaches. - Kasia Swirydowicz; Jesun Firoz; Joseph B. Manzano; Mahantesh Halappanavar; Stephen Thomas; Kevin J. Barker (SBAC-PAD, 2024)

Efficient Weighted Graph Matching on GPUs. - Michael Mandulak; Sayan Ghosh; S. M. Ferdous; Mahantesh Halappanavar; George M. Slota (SC, 2024)

Streaming Matching and Edge Cover in Practice. - S. M. Ferdous; Alex Pothen; Mahantesh Halappanavar (SEA, 2024)

texttt{Picasso}: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing. - S. M. Ferdous; Reece Neff; Bo Peng; Salman Shuvo; Marco Minutoli; Sayak Mukherjee; Karol Kowalski; Michela Becchi; Mahantesh Halappanavar (CoRR, 2024)

Approximate Bipartite b-Matching using Multiplicative Auction. - Bhargav Samineni; S. M. Ferdous; Mahantesh Halappanavar; Bala Krishnamoorthy (CoRR, 2024)

Predictive Analytics of Varieties of Potatoes. - Fabiana Ferracina; Bala Krishnamoorthy; Mahantesh Halappanavar; Shengwei Hu; Vidyasagar Sathuvalli (CoRR, 2024)

RAG vs. Long Context: Examining Frontier Large Language Models for Environmental Review Document Comprehension. - Hung Phan; Anurag Acharya 002; Sarthak Chaturvedi; Shivam Sharma; Mike Parker; Dan Nally; Ali Jannesari; Karl Pazdernik; Mahantesh Halappanavar; Sai Munikoti; Sameera Horawalavithana (CoRR, 2024)

Parallel Algorithms for Median Consensus Clustering in Complex Networks. - Md Taufique Hussain; Mahantesh Halappanavar; Samrat Chatterjee; Filippo Radicchi; Santo Fortunato; Ariful Azad (CoRR, 2024)

PermitQA: A Benchmark for Retrieval Augmented Generation in Wind Siting and Permitting domain. - Rounak Meyur; Hung Phan; Sridevi Wagle; Jan Strube 001; Mahantesh Halappanavar; Sameera Horawalavithana; Anurag Acharya 002; Sai Munikoti (CoRR, 2024)

Learning to Simulate Aerosol Dynamics with Graph Neural Networks. - Fabiana Ferracina; Payton Beeler; Mahantesh Halappanavar; Bala Krishnamoorthy; Marco Minutoli; Laura Fierce (CoRR, 2024)

An Integrated Epidemic Simulation Workflow for Submodular Intervention Strategies. - Reet Barik; Marco Minutoli; Mahantesh Halappanavar; Ananth Kalyanaraman (CoRR, 2024)

DISHONEST: Dissecting misInformation Spread using Homogeneous sOcial NEtworks and Semantic Topic classification. - Caleb Stam; Emily Saldanha; Mahantesh Halappanavar; Anurag Acharya 002 (CoRR, 2024)

GraMeR: Graph Meta Reinforcement learning for multi-objective influence maximization. - Sai Munikoti; Balasubramaniam Natarajan; Mahantesh Halappanavar (J. Parallel Distributed Comput., 2024)

Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. - Karthik Somayaji N. S.; Yu Wang 167; Malachi Schram; Ján Drgona; Mahantesh M. Halappanavar; Frank Liu 001; Peng Li 001 (Trans. Mach. Learn. Res., 2024)

Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications. - Sai Munikoti; Deepesh Agarwal; Laya Das; Mahantesh Halappanavar; Balasubramaniam Natarajan (IEEE Trans. Neural Networks Learn. Syst., 2024)

Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases. - Yongjia Lei; Haoyu Han 001; Ryan A. Rossi; Franck Dernoncourt; Nedim Lipka; Mahantesh M. Halappanavar; Jiliang Tang; Yu Wang 160 (ACL (Findings), 2025)

FlowForecaster: Automatically Inferring Detailed & Interpretable Workflow Scaling Models for Forecasts. - Hyungro Lee; Jesun Firoz; Nathan R. Tallent; Luanzheng Guo; Mahantesh Halappanavar (IPDPS, 2025)

Disharmony: Forensics Using Reverse Lighting Harmonization. - Philip Wootaek Shin; Jack Sampson; Vijaykrishnan Narayanan; Andres Marquez 001; Mahantesh Halappanavar (WACV (Workshops), 2025)

GreediRIS: Scalable influence maximization using distributed streaming maximum cover. - Reet Barik; Wade Cappa; S. M. Ferdous; Marco Minutoli; Mahantesh Halappanavar; Ananth Kalyanaraman (J. Parallel Distributed Comput., 2025)

Retrieval-Augmented Generation with Graphs (GraphRAG). - Haoyu Han 001; Yu Wang 160; Harry Shomer; Kai Guo 003; Jiayuan Ding; Yongjia Lei; Mahantesh Halappanavar; Ryan A. Rossi; Subhabrata Mukherjee; Xianfeng Tang; Qi He 002; Zhigang Hua; et al. (CoRR, 2025)

SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks. - Siddhartha Shankar Das; Naheed Anjum Arafat; Muftiqur Rahman; S. M. Ferdous; Alex Pothen; Mahantesh M. Halappanavar (CoRR, 2025)

GNN-Based Candidate Node Predictor for Influence Maximization in Temporal Graphs. - Priyanka Gautam; Balasubramaniam Natarajan; Sai Munikoti; S. M. Ferdous; Mahantesh Halappanavar (CoRR, 2025)

ScaWL: Scaling k-WL (Weisfeiler-Lehman) Algorithms in Memory and Performance on Shared and Distributed-Memory Systems. - Coby Soss; Aravind Sukumaran-Rajam; Janet Layne; Edoardo Serra; Mahantesh Halappanavar; Assefaw H. Gebremedhin (ACM Trans. Archit. Code Optim., 2025)

Denoising Diffusion Probabilistic Models for Coastal Inundation Forecasting. - Kazi Ashik Islam; Zakaria Mehrab; Mahantesh Halappanavar; Henning S. Mortveit; Sridhar Katragadda; Jon Derek Loftis; Madhav V. Marathe (CoRR, 2025)

A Graph Perspective to Probe Structural Patterns of Knowledge in Large Language Models. - Utkarsh Sahu; Zhisheng Qi; Yongjia Lei; Ryan A. Rossi; Franck Dernoncourt; Nesreen K. Ahmed; Mahantesh M. Halappanavar; Yao Ma 001; Yu Wang 160 (CoRR, 2025)

ELRUHNA: Elimination Rule-basedHypergraph Alignment. - Cameron Ibrahim; S. M. Ferdous; Ilya Safro; Marco Minutoli; Mahantesh Halappanavar (CoRR, 2025)

ApproxJoin: Approximate Matching for Efficient Verification in Fuzzy Set Similarity Join. - Michael Mandulak; S. M. Ferdous; Sayan Ghosh; Mahantesh Halappanavar; George M. Slota (CoRR, 2025)