Publications

2025

  1. Journal SWARM: Reimagining Scientific Workflow Management Systems in a Distributed World Balaprakash, Prasanna and Raghavan, Krishnan and Cappello, Franck and Deelman, Ewa and Mandal, Anirban and Jin, Hongwei and Mahmud, Imtiaz and Thareja, Komal and Wu, Shixun and Zuk, Pawel and others The International Journal of High Performance Computing Applications , 2025
  2. Journal Advancing Anomaly Detection in Computational Workflows with Active Learning Raghavan, Krishnan and Papadimitriou, George and Jin, Hongwei and Mandal, Anirban and Kiran, Mariam and Balaprakash, Prasanna and Deelman, Ewa Future Generation Computer Systems , 2025
  3. Conference A Greedy Consensus-Based Approach to Distributed Job Selection: Toward Fully-Decentralized Workload Management System Thareja, Komal and Raghavan, Krishnan and Mandal, Anirban and Zuk, Pawel and Mahmud, Imtiaz and Kiran, Mariam and Deelman, Ewa 2025 IEEE 25th International Symposium on Cluster, Cloud and Internet Computing (CCGrid) , 2025
  4. Conference Bridging Speed and Optimality in Job Scheduling: A Hybrid Ant Colony Optimization Approach for Distributed Systems Thareja, Komal and Raghavan, Krishnan and Mandal, Anirban and Deelman, Ewa Proceedings of the SC ’25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis , 2025
  5. Preprint Sampling Imbalanced Data with Multi-Objective Bilevel Optimization Medlin, Karen and Leyffer, Sven and Raghavan, Krishnan arXiv preprint arXiv:2506.11315 , 2025
  6. Preprint LifeLong Learning for Large Language Models in Predicting Chemical Reaction Yields Sivaraman, Ganesh and Jackson, Nicholas and Raghavan, Krishnan ChemRxiv , 2025
  7. Preprint Who Gets the Reward, Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents Yang, Chih-Hsuan and Mallick, Tanwi and Chen, Le and Raghavan, Krishnan and Wells, Azton and Gueroudji, Amal and Foster, Ian T. and Thakur, Rajeev arXiv preprint arXiv:2511.10687 , 2025

2024

  1. Journal Automated Defect Identification in Coherent Diffraction Imaging with Smart Continual Learning Yildiz, Orcun and Raghavan, Krishnan and Chan, Henry and Cherukara, Mathew J. and Balaprakash, Prasanna and Sankaranarayanan, Subramanian and Peterka, Tom Neural Computing and Applications , 2024
  2. Journal Classification of Events from α-Induced Reactions in the MUSIC Detector via Statistical and ML Methods Raghavan, Krishnan and Avila, Melina L. and Balaprakash, Prasanna and Jayatissa, Heshani and Santiago-Gonzalez, Daniel Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment , 2024
  3. Journal Uncertainty-Quantification-Enabled Inversion of Nuclear Responses Raghavan, Krishnan and Lovato, Alessandro Physical Review C , 2024
  4. Journal Cooperative Deep Q-Learning Framework for Environments Providing Image Feedback Raghavan, Krishnan and Narayanan, Vignesh and Jagannathan, Sarangapani IEEE Transactions on Neural Networks and Learning Systems , 2024
  5. Conference Large Language Models for Anomaly Detection in Computational Workflows: From Supervised Fine-Tuning to In-Context Learning Jin, Hongwei and Papadimitriou, George and Raghavan, Krishnan and Zuk, Pawel and Balaprakash, Prasanna and Wang, Cong and Mandal, Anirban and Deelman, Ewa SC24: International Conference for High Performance Computing, Networking, Storage and Analysis , 2024
  6. Conference Privacy-Preserving Federated Learning for Science: Challenges and Research Directions Kim, Kibaek and Raghavan, Krishnan and Kotevska, Olivera and Dorier, Matthieu and Madduri, Ravi and Ryu, Minseok and Munson, Todd and Ross, Rob and Flynn, Thomas and Kagawa, Ai and others 2024 IEEE International Conference on Big Data (BigData) , 2024
  7. Conference DISTRI: Development and Integration of Simulation Tools for Resilient Infrastructure Mahmud, Imtiaz and Zuk, Pawel and Wang, Cong and Kiran, Mariam and Wu, Kesheng and Thareja, Komal and Raghavan, Krishnan and Mandal, Anirban and Deelman, Ewa 2024 IEEE International Conference on Big Data (BigData) , 2024
  8. Conference Agent-Based Modeling of Communities for Understanding Equity Effects of Climate Change Macal, Charles and Stevens, Abby and Rimer, Sara and Ozik, Jonathan and Adrian, Melissa and Raghavan, Krishnan AGU Fall Meeting Abstracts , 2024
  9. Conference A Lightweight Decision Support Framework for Community Climate Resilience in Chicago Stevens, Abby and Adrian, Melissa and Raghavan, Krishnan and Ozik, Jonathan and Macal, Charles AGU Fall Meeting Abstracts , 2024
  10. Book Chapter FlowBench Raw Data Archive Papadimitriou, George and Jin, Hongwei and Wang, Cong and Raghavan, Krishnan and Mahmud, Imtiaz and Thareja, Komal and Zuk, Pawel and Mayani, Rajiv and Balaprakash, Prasanna and Kiran, Mariam and others , 2024
  11. Book Chapter RADT Scripts for Network Research Mahmud, Imtiaz and Papadimitriou, George and Wang, Cong and Jin, Hongwei and Thareja, Komal and Zuk, Pawel and Raghavan, Krishnan and Mayani, Rajiv and Balaprakash, Prasanna and Kiran, Mariam and others , 2024
  12. Preprint On Understanding of the Dynamics of Model Capacity in Continual Learning Chakraborty, Supriyo and Raghavan, Krishnan , 2024
  13. Preprint A Bilevel Optimization Framework for Imbalanced Data Classification Medlin, Karen and Leyffer, Sven and Raghavan, Krishnan arXiv preprint arXiv:2410.11171 , 2024
  14. Preprint DGRO: Diameter-Guided Ring Optimization for Integrated Research Infrastructure Membership Wu, Shixun and Raghavan, Krishnan and Di, Sheng and Chen, Zizhong and Cappello, Franck arXiv preprint arXiv:2410.11142 , 2024

2023

  1. Journal Quantifying Uncertainty for Deep Learning Based Forecasting and Flow-Reconstruction Using Neural Architecture Search Ensembles Maulik, Romit and Egele, Romain and Raghavan, Krishnan and Balaprakash, Prasanna Physica D: Nonlinear Phenomena , 2023
  2. Journal Graph Neural Networks for Detecting Anomalies in Scientific Workflows Jin, Hongwei and Raghavan, Krishnan and Papadimitriou, George and Wang, Cong and Mandal, Anirban and Kiran, Mariam and Deelman, Ewa and Balaprakash, Prasanna The International Journal of High Performance Computing Applications , 2023
  3. Conference SF-SFD: Stochastic Optimization of Fourier Coefficients to Generate Space-Filling Designs Garg, Manisha and Chang, Tyler H. and Raghavan, Krishnan 2023 Winter Simulation Conference (WSC) , 2023
  4. Conference Forward Gradients for Data-Driven CFD Wall Modeling Hückelheim, Jan and Kumar, Tadbhagya and Raghavan, Krishnan and Pal, Pinaki NeurIPS Machine Learning and the Physical Sciences Workshop , 2023
  5. Conference CARIBU-matic and the MUSIC ML Project: Examples of Machine-Learning Applications for Beam Tuning and Experimental Data Analysis/Classification Santiago-Gonzalez, Daniel and Avila, Melina and Balaprakash, Prasanna and Jayatissa, Heshani and Raghavan, Krishnan and Callahan, Nathan APS Meeting Abstracts , 2023
  6. Book Chapter Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations Boito, Francieli and Brandt, Jim and Cardellini, Valeria and Carns, Philip and Ciorba, Florina M. and Egan, Hilary and Eleliemy, Ahmed and Gentile, Ann and Gruber, Thomas and Hanson, Jeff and others 2023 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops) , 2023
  7. Book Chapter Introduction to Reinforcement Learning Sun, Yixuan and Raghavan, Krishnan and Balaprakash, Prasanna Methods and Applications of Autonomous Experimentation , 2023
  8. Book Chapter 2023 AI Testbed Expeditions Report Vishwanath, Venkat and Emani, Murali and Sastry, Varuni and Arnold, William and Thakur, Rajeev and Taylor, Valerie and Foster, Ian and Habib, Salman and Papka, Michael E. and Allen, Bryce and others , 2023
  9. Preprint Self-Supervised Learning for Anomaly Detection in Computational Workflows Jin, Hongwei and Raghavan, Krishnan and Papadimitriou, George and Wang, Cong and Mandal, Anirban and Deelman, Ewa and Balaprakash, Prasanna arXiv preprint arXiv:2310.01247 , 2023
  10. Preprint Flow-Bench: A Dataset for Computational Workflow Anomaly Detection Papadimitriou, George and Jin, Hongwei and Wang, Cong and Mayani, Rajiv and Raghavan, Krishnan and Mandal, Anirban and Balaprakash, Prasanna and Deelman, Ewa arXiv preprint arXiv:2306.09930 , 2023
  11. Preprint Learning Continually on a Sequence of Graphs – The Dynamical System Way Raghavan, Krishnan and Balaprakash, Prasanna arXiv preprint arXiv:2305.12030 , 2023

2022

  1. Journal A Game Theoretic Approach for Addressing Domain-Shift in Big-Data Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. IEEE Transactions on Big Data , 2022
  2. Conference AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification Egele, Romain and Maulik, Romit and Raghavan, Krishnan and Lusch, Bethany and Guyon, Isabelle and Balaprakash, Prasanna 2022 26th International Conference on Pattern Recognition (ICPR) , 2022
  3. Conference Workflow Anomaly Detection with Graph Neural Networks Jin, Hongwei and Raghavan, Krishnan and Papadimitriou, George and Wang, Cong and Mandal, Anirban and Krawczuk, Patrycja and Pottier, Loı̈c and Kiran, Mariam and Deelman, Ewa and Balaprakash, Prasanna 2022 IEEE/ACM Workshop on Workflows in Support of Large-Scale Science (WORKS) , 2022
  4. Conference Continual Learning via Dynamic Programming Raghavan, Krishnan and Balaprakash, Prasanna 2022 26th International Conference on Pattern Recognition (ICPR) , 2022
  5. Conference Automated Continual Learning of Defect Identification in Coherent Diffraction Imaging Yildiz, Orcun and Chan, Henry and Raghavan, Krishnan and Judge, William and Cherukara, Mathew J. and Balaprakash, Prasanna and Sankaranarayanan, Subramanian and Peterka, Tom 2022 IEEE/ACM International Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S) , 2022

2021

  1. Journal Machine-Learning-Based Inversion of Nuclear Responses Raghavan, Krishnan and Balaprakash, Prasanna and Lovato, Alessandro and Rocco, Noemi and Wild, Stefan M. Physical Review C , 2021
  2. Journal Distributed Min–Max Learning Scheme for Neural Networks with Applications to High-Dimensional Classification Raghavan, Krishnan and Garg, Shweta and Jagannathan, Sarangapani and Samaranayake, V. A. IEEE Transactions on Neural Networks and Learning Systems , 2021
  3. Conference Formalizing the Generalization-Forgetting Trade-Off in Continual Learning Raghavan, Krishnan and Balaprakash, Prasanna Advances in Neural Information Processing Systems , 2021
  4. Book Chapter Optimal Adaptive Control of Partially Uncertain Linear Continuous-Time Systems with State Delay Moghadam, Rohollah and Jagannathan, Sarangapani and Narayanan, Vignesh and Raghavan, Krishnan Handbook of Reinforcement Learning and Control , 2021
  5. Preprint Learning to Control Using Image Feedback Raghavan, Krishnan and Narayanan, Vignesh and Jagannathan, Sarangapani arXiv preprint arXiv:2110.15290 , 2021

2020

  1. Journal Direct Error-Driven Learning for Deep Neural Networks with Applications to Big Data Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. IEEE Transactions on Neural Networks and Learning Systems , 2020
  2. Conference Online Optimal Adaptive Control of a Class of Uncertain Nonlinear Discrete-Time Systems Moghadam, Rohollah and Natarajan, Pappa and Raghavan, Krishnan and Jagannathan, Sarangapani 2020 International Joint Conference on Neural Networks (IJCNN) , 2020
  3. Book Chapter Direct Error Driven Learning for Classification in Applications Generating Big-Data Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. Development and Analysis of Deep Learning Architectures , 2020

2019

  1. Journal A Hierarchical Dimension Reduction Approach for Big Data with Application to Fault Diagnostics Raghavan, Krishnan and Samaranayake, V. A. and Jagannathan, Sarangapani Big Data Research , 2019
  2. Journal A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Big Data Raghavan, Krishnan and Samaranayake, V. A. and Jagannathan, Sarangapani IEEE Transactions on Knowledge and Data Engineering , 2019
  3. Book Chapter Deep Neural Network Learning-Based Classifier Design for Big-Data Analytics Raghavan, Krishnan , 2019

2018

  1. Conference Distributed Learning of Deep Sparse Neural Networks for High-Dimensional Classification Garg, Shweta and Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. 2018 IEEE International Conference on Big Data (Big Data) , 2018
  2. Conference Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. Procedia Computer Science International Conference on Big Data and Deep Learning (INNS) , 2018
  3. Conference A Minimax Approach for Classification with Big-Data Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. 2018 IEEE International Conference on Big Data (Big Data) , 2018

2017

  1. Conference Deep Learning Inspired Prognostics Scheme for Applications Generating Big Data Raghavan, Krishnan and Jagannathan, Sarangapani and Samaranayake, V. A. 2017 International Joint Conference on Neural Networks (IJCNN) , 2017

2015

  1. Conference Hierarchical Mahalanobis Distance Clustering Based Technique for Prognostics in Applications Generating Big Data Raghavan, Krishnan and Jagannathan, Sarangapani 2015 IEEE Symposium Series on Computational Intelligence , 2015

2014

  1. Book Chapter Computer Vision Libraries for Trailer Truck Testbed Using Open Source Computer Vision Libraries Raghavan, Krishnan , 2014