Binarization of Inhomogeneously Illuminated Images. - Volodymyr V. Kindratenko; Boris A. Treiger; Piet J. M. Van Espen (ICIAP, 1995)

Classification of irregularly shaped micro-objects using complex Fourier descriptors. - Volodymyr V. Kindratenko; Piet J. M. Van Espen (ICPR, 1996)

Sharing virtual environments over a transatlantic ATM network in support of distant collaboration in vehicle design. - Volodymyr V. Kindratenko; Berthold Kirsch (EGVE, 1998)

Calibration of electromagnetic tracking devices. - Volodymyr V. Kindratenko (Virtual Real., 1999)

Evaluation of Rotation Correction Techniques for Electromagnetic Position Tracking Systems. - Volodymyr V. Kindratenko; Angela Bennett (EGVE, 2000)

A survey of electromagnetic position tracker calibration techniques. - Volodymyr V. Kindratenko (Virtual Real., 2000)

A Comparison of the Accuracy of an Electromagnetic and a Hybrid Ultrasound-Inertia Position Tracking System. - Volodymyr V. Kindratenko (Presence Teleoperators Virtual Environ., 2001)

IntelliBadgeTM: Towards Providing Location-Aware Value-Added Services at Academic Conferences. - Donna J. Cox; Volodymyr V. Kindratenko; David Pointer (UbiComp, 2003)

On Using Functions to Describe the Shape. - Volodymyr V. Kindratenko (J. Math. Imaging Vis., 2003)

The Visible Radio: Process Visualization of a Software-Defined Radio. - Matthew Hall; Alex Betts; Donna J. Cox; David Pointer; Volodymyr V. Kindratenko (IEEE Visualization, 2005)

Neural network-based calibration of electromagnetic tracking systems. - Volodymyr V. Kindratenko; William R. Sherman (Virtual Real., 2005)

Code Partitioning for Reconfigurable High-Performance Computing: A Case Study. - Volodymyr V. Kindratenko (ERSA, 2006)

A case study in porting a production scientific supercomputing application to a reconfigurable computer. - Volodymyr V. Kindratenko; David Pointer (FCCM, 2006)

M03 - Reconfigurable supercomputing. - Tarek A. El-Ghazawi; Duncan A. Buell; Volodymyr V. Kindratenko; Kris Gaj (SC, 2006)

Reconfigurable supercomputing - Is high-performance reconfigurable computing the next supercomputing paradigm? - Tarek A. El-Ghazawi; Dave Bennett; Daniel S. Poznanovic; Allan Cantle; Keith D. Underwood; Rob Pennington; Duncan A. Buell; Alan D. George; Volodymyr V. Kindratenko (SC, 2006)

Mitrion-C Application Development on SGI Altix 350/RC100. - Volodymyr V. Kindratenko; Robert J. Brunner; Adam D. Myers (FCCM, 2007)

Guest Editors' Introduction: High-Performance Reconfigurable Computing. - Duncan A. Buell; Tarek A. El-Ghazawi; Kris Gaj; Volodymyr V. Kindratenko (Computer, 2007)

Accelerating Scientific Applications with Reconfigurable Computing: Getting Started. - Volodymyr V. Kindratenko; Craig P. Steffen; Robert J. Brunner (Comput. Sci. Eng., 2007)

Implementation of NAMD molecular dynamics non-bonded force-field on the cell broadband engine processor. - Guochun Shi; Volodymyr V. Kindratenko (IPDPS, 2008)

The Promise of High-Performance Reconfigurable Computing. - Tarek A. El-Ghazawi; Esam El-Araby; Miaoqing Huang; Kris Gaj; Volodymyr V. Kindratenko; Duncan A. Buell (Computer, 2008)

High-Performance Computing Applications on Novel Architectures. - Volodymyr V. Kindratenko; George K. Thiruvathukal; Steven A. Gottlieb (Comput. Sci. Eng., 2008)

Reconfigurable Systems Summer Institute 2007. - Volodymyr V. Kindratenko; Duncan A. Buell (Parallel Comput., 2008)

Accelerating cosmological data analysis with graphics processors. - Dylan W. Roeh; Volodymyr V. Kindratenko; Robert J. Brunner (GPGPU, 2009)

GPU clusters for high-performance computing. - Volodymyr V. Kindratenko; Jeremy Enos; Guochun Shi; Michael T. Showerman; Galen Wesley Arnold; John E. Stone; James C. Phillips; Wen-mei W. Hwu (CLUSTER, 2009)

Accelerating Cosmological Data Analysis with FPGAs. - Volodymyr V. Kindratenko; Robert J. Brunner (FCCM, 2009)

SoundMaker: a Web-Based Teaching Tool for Sound Design. - Ryan Cavis; Sever Tipei; Volodymyr V. Kindratenko (ICMC, 2009)

Phoenix: A Runtime Environment for High Performance Computing on Chip Multiprocessors. - Avneesh Pant; Hassan Jafri; Volodymyr V. Kindratenko (PDP, 2009)

Novel Computing Architectures. - Volodymyr V. Kindratenko (Comput. Sci. Eng., 2009)

The Bottom-Up Implementation of One MILC Lattice QCD Application on the Cell Blade. - Guochun Shi; Volodymyr V. Kindratenko; Steven A. Gottlieb (Int. J. Parallel Program., 2009)

Implementation of the two-point angular correlation function on a high-performance reconfigurable computer. - Volodymyr V. Kindratenko; Adam D. Myers; Robert J. Brunner (Sci. Program., 2009)

Implementation of scientific computing applications on the Cell Broadband Engine. - Guochun Shi; Volodymyr V. Kindratenko; Ivan S. Ufimtsev; Todd J. Martínez; James C. Phillips; Steven A. Gottlieb (Sci. Program., 2009)

Quantifying the impact of GPUs on performance and energy efficiency in HPC clusters. - Jeremy Enos; Craig P. Steffen; Joshi Fullop; Michael T. Showerman; Guochun Shi; Kenneth Esler; Volodymyr V. Kindratenko; John E. Stone; James C. Phillips (Green Computing Conference, 2010)

Direct self-consistent field computations on GPU clusters. - Guochun Shi; Volodymyr V. Kindratenko; Ivan S. Ufimtsev; Todd J. Martínez (IPDPS, 2010)

High-Performance Computing with Accelerators. - Volodymyr V. Kindratenko; Robert B. Wilhelmson; Robert J. Brunner; Todd J. Martínez; Wen-mei W. Hwu (Comput. Sci. Eng., 2010)

Application Acceleration with the Cell Broadband Engine. - Guochun Shi; Volodymyr V. Kindratenko; Frederico Pratas; Pedro Trancoso; Michael Gschwind (Comput. Sci. Eng., 2010)

GPU acceleration of an image characterization algorithm for document similarity analysis. - Guochun Shi; Volodymyr V. Kindratenko; Rob Kooper; Peter Bajcsy (AICCSA, 2011)

Design of MILC Lattice QCD Application for GPU Clusters. - Guochun Shi; Steven A. Gottlieb; Aaron Torok; Volodymyr V. Kindratenko (IPDPS, 2011)

Trends in High-Performance Computing. - Volodymyr V. Kindratenko; Pedro Trancoso (Comput. Sci. Eng., 2011)

Guest Editor's Introduction: Special Issue on High-Performance Computing with Accelerators. - David A. Bader; David R. Kaeli; Volodymyr V. Kindratenko (IEEE Trans. Parallel Distributed Syst., 2011)

Scientific Computing with GPUs. - Volodymyr V. Kindratenko (Comput. Sci. Eng., 2012)

Application accelerators in HPC - Editorial introduction. - Volodymyr V. Kindratenko; Gregory D. Peterson (Parallel Comput., 2012)

Fine-grain parallelism using multi-core, Cell/BE, and GPU Systems. - Frederico Pratas; Pedro Trancoso; Leonel Sousa; Alexandros Stamatakis; Guochun Shi; Volodymyr V. Kindratenko (Parallel Comput., 2012)

tensorflow-tracing: A Performance Tuning Framework for Production. - Sayed Hadi Hashemi; Paul Rausch; Benjamin Rabe; Kuan-Yen Chou; Simeng Liu; Volodymyr V. Kindratenko; Roy H. Campbell (OpML, 2019)

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era. - Gabrielle Allen; Igor Andreoni; Etienne Bachelet; G. Bruce Berriman; Federica B. Bianco; Rahul Biswas; Matias Carrasco Kind; Kyle Chard; Minsik Cho; Philip S. Cowperthwaite; Zachariah B. Etienne; Daniel George; et al. (CoRR, 2019)

Enabling real-time multi-messenger astrophysics discoveries with deep learning. - Eliu A. Huerta; Gabrielle Allen; Igor Andreoni; Javier Mauricio Antelis; Etienne Bachelet; G. Bruce Berriman; Federica B. Bianco; Rahul Biswas; Matias Carrasco Kind; Kyle Chard; Minsik Cho; Philip S. Cowperthwaite; et al. (CoRR, 2019)

HLS-Based Acceleration Framework for Deep Convolutional Neural Networks. - Ashish Misra; Volodymyr V. Kindratenko (ARC, 2020)

Parameter Identification of RANS Turbulence Model Using Physics-Embedded Neural Network. - Shirui Luo; Madhu Vellakal; Seid Koric; Volodymyr V. Kindratenko; Jiahuan Cui (ISC Workshops, 2020)

HAL: Computer System for Scalable Deep Learning. - Volodymyr V. Kindratenko; Dawei Mu; Yan Zhan; John Maloney; Sayed Hadi Hashemi; Benjamin Rabe; Ke Xu; Roy H. Campbell; Jian Peng 001; William Gropp (PEARC, 2020)

NCSA Internship Program for Cyberinfrastructure Professionals. - Daniel Lapine; Volodymyr V. Kindratenko; Luisa-Maria Rosu (PEARC, 2020)

Confluence of Artificial Intelligence and High Performance Computing for Accelerated, Scalable and Reproducible Gravitational Wave Detection. - Eliu A. Huerta; Asad Khan; Xiaobo Huang; Minyang Tian; Maksim Levental; Ryan Chard; Wei Wei 021; Maeve Heflin; Daniel S. Katz; Volodymyr V. Kindratenko; Dawei Mu; Ben Blaiszik; et al. (CoRR, 2020)

Hands-on with IBM Visual Insights. - Shirui Luo; Volodymyr V. Kindratenko (Comput. Sci. Eng., 2020)

High-Level Synthesis-Based Approach for Accelerating Scientific Codes on FPGAs. - Ramshankar Venkatakrishnan; Ashish Misra; Volodymyr V. Kindratenko; Anne C. Elster (Comput. Sci. Eng., 2020)

Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure. - Eliu A. Huerta; Asad Khan; Edward Davis; Colleen Bushell; William D. Gropp; Daniel S. Katz; Volodymyr V. Kindratenko; Seid Koric; William T. C. Kramer; Brendan McGinty; Kenton McHenry; Aaron Saxton (J. Big Data, 2020)

Efficient HW and SW Interface Design for Convolutional Neural Networks Using High-Level Synthesis and TensorFlow. - Ashish Misra; Churan He; Volodymyr V. Kindratenko (H2RC@SC, 2021)

Turbomachinery Blade Surrogate Modeling Using Deep Learning. - Shirui Luo; Jiahuan Cui; Vignesh Sella; Jian Liu; Seid Koric; Volodymyr V. Kindratenko (ISC Workshops, 2021)

A FAIR and AI-ready Higgs Boson Decay Dataset. - Yifan Chen; Eliu A. Huerta; Javier M. Duarte; Philip C. Harris; Daniel S. Katz; Mark S. Neubauer; Daniel Diaz 003; Farouk Mokhtar; Raghav Kansal; Sang Eon Park; Volodymyr V. Kindratenko; Zhizhen Zhao 001; et al. (CoRR, 2021)

AGNet: Weighing Black Holes with Deep Learning. - Joshua Yao-Yu Lin; Sneh Pandya; Devanshi Pratap; Xin Liu; Matias Carrasco Kind; Volodymyr V. Kindratenko (CoRR, 2021)

The European Factor: From ARM to Atos. - Anne C. Elster; Volodymyr V. Kindratenko (Comput. Sci. Eng., 2021)

Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture. - Murali Emani; Venkatram Vishwanath; Corey Adams; Michael E. Papka; Rick Stevens; Laura Florescu; Sumti Jairath; William Liu; Tejas Nama; Arvind Sujeeth; Volodymyr V. Kindratenko; Anne C. Elster (Comput. Sci. Eng., 2021)

FPGAs in the Cloud. - Miriam Leeser; Suranga Handagala; Michael Zink; Volodymyr V. Kindratenko; Anne C. Elster (Comput. Sci. Eng., 2021)

Sparse Spatio-Temporal Neural Network for Large-Scale Forecasting. - Eamon Bracht; Volodymyr V. Kindratenko; Robert J. Brunner (IEEE Big Data, 2022)

Weakly Supervised Two-Stage Training Scheme for Deep Video Fight Detection Model. - Zhenting Qi; Ruike Zhu; Zheyu Fu; Wenhao Chai; Volodymyr V. Kindratenko (ICTAI, 2022)

FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. - Eliu A. Huerta; Ben Blaiszik; L. Catherine Brinson; Kristofer E. Bouchard; Daniel Diaz 003; Caterina Doglioni; Javier M. Duarte; Murali Emani; Ian T. Foster; Geoffrey C. Fox; Philip C. Harris; Lukas Heinrich; et al. (CoRR, 2022)

Weakly Supervised Segmentation of Buildings in Digital Elevation Models. - Aiman Soliman; Yifan Chen; Shirui Luo; Rauf Makharov; Volodymyr V. Kindratenko (IEEE Geosci. Remote. Sens. Lett., 2022)

Exploring HW/SW Co-Design for Video Analysis on CPU-FPGA Heterogeneous Systems. - Xiaofan Zhang 001; Yuan Ma; Jinjun Xiong; Wen-Mei W. Hwu; Volodymyr V. Kindratenko; Deming Chen (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

DEM_building_Illinois. - Yifan Chen; Aiman Soliman; Volodymyr V. Kindratenko; Shirui Luo; Rauf Makharov (IEEE DataPort, 2022)

APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service. - Zilinghan Li; Shilan He; Pranshu Chaturvedi; Trung-Hieu Hoang; Minseok Ryu; Eliu A. Huerta; Volodymyr V. Kindratenko; Jordan D. Fuhrman; Maryellen L. Giger; Ryan Chard; Kibaek Kim; Ravi K. Madduri (e-Science, 2023)

YouTubePD: A Multimodal Benchmark for Parkinson's Disease Analysis. - Andy Zhou; Samuel Li; Pranav Sriram; Xiang Li; Jiahua Dong 002; Ansh Sharma; Yuanyi Zhong; Shirui Luo; Volodymyr V. Kindratenko; George Heintz; Christopher M. Zallek; Yu-Xiong Wang (NeurIPS, 2023)

Novel Approaches Toward Scalable Composable Workflows in Hyper-Heterogeneous Computing Environments. - Jonathan Bader; Jim Belak; Matthew T. Bement; Matthew Berry; Robert Carson; Daniela Cassol; Stephen Chan; John Coleman; Kastan Day; Alejandro Duque; Kjiersten Fagnan; Jeff Froula; et al. (SC Workshops, 2023)

Cloud-Bursting and Autoscaling for Python-Native Scientific Workflows Using Ray. - Tingkai Liu; Marquita Ellis; Carlos H. A. Costa; Claudia Misale; Sara Kokkila Schumacher; Jinwook Jung; Gi-Joon Nam; Volodymyr V. Kindratenko (ISC Workshops, 2023)

Sequence Generation via Subsequence Similarity: Theory and Application to UAV Identification. - Amir Kazemi; Salar Basiri; Volodymyr V. Kindratenko; Srinivasa M. Salapaka (CoRR, 2023)

Self-Supervised Masked Digital Elevation Models Encoding for Low-Resource Downstream Tasks. - Priyam Mazumdar; Aiman Soliman; Volodymyr V. Kindratenko; Luigi Marini; Kenton McHenry (CoRR, 2023)

Leveraging Large Language Models to Build and Execute Computational Workflows. - Alejandro Duque; Abdullah Syed; Kastan V. Day; Matthew J. Berry; Daniel S. Katz; Volodymyr V. Kindratenko (CoRR, 2023)

Training Next-Generation Artificial Intelligence Users and Developers at NCSA. - Daniel S. Katz; Volodymyr V. Kindratenko; Olena Kindratenko; Priyam Mazumdar (Comput. Sci. Eng., 2023)

Critical Minerals Map Feature Extraction Using Deep Learning. - Shirui Luo; Aaron Saxton; Albert Bode; Priyam Mazumdar; Volodymyr V. Kindratenko (IEEE Geosci. Remote. Sens. Lett., 2023)

Character Face in Video. - Zilinghan Li; Xiwei Wang; Zhenning Zhang; Volodymyr V. Kindratenko (IEEE DataPort, 2023)

FAIR AI models in high energy physics. - Javier M. Duarte; Haoyang Li; Avik Roy; Ruike Zhu; Eliu A. Huerta; Daniel Diaz 003; Philip C. Harris; Raghav Kansal; Daniel S. Katz; Ishaan H. Kavoori; Volodymyr V. Kindratenko; Farouk Mokhtar; et al. (Mach. Learn. Sci. Technol., 2023)

UniNet: Accelerating the Container Network Data Plane in IaaS Clouds. - Yuan Ma; Scott Smith; Bill Gropp; Hubertus Franke; Bharat Sukhwani; Sameh W. Asaad; Jinjun Xiong; Volodymyr V. Kindratenko; Deming Chen (CLOUD, 2024)

OS4C: An Open-Source SR-IOV System for SmartNIC-Based Cloud Platforms. - Scott Smith; Yuan Ma; Marissa Lanz; Bill Dai; Martin Ohmacht; Bharat Sukhwani; Hubertus Franke; Volodymyr V. Kindratenko; Deming Chen (CLOUD, 2024)

Automated Data Management and Learning-Based Scheduling for Ray-Based Hybrid HPC-Cloud Systems. - Tingkai Liu; Huili Tao; Yicheng Lu; Zhongbo Zhu; Marquita Ellis; Sara Kokkila Schumacher; Volodymyr V. Kindratenko (Euro-Par (1), 2024)

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler. - Zilinghan Li; Pranshu Chaturvedi; Shilan He; Han Chen; Gagandeep Singh; Volodymyr V. Kindratenko; Eliu A. Huerta; Kibaek Kim; Ravi K. Madduri (ICLR, 2024)

Training Next Generation AI Users and Developers at NCSA. - Daniel S. Katz; Volodymyr V. Kindratenko; Olena Kindratenko; Priyam Mazumdar (CoRR, 2024)

AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization. - Amir Kazemi; Qurat ul ain Fatima; Volodymyr V. Kindratenko; Christopher Tessum (CoRR, 2024)

RL-Pruner: Structured Pruning Using Reinforcement Learning for CNN Compression and Acceleration. - Boyao Wang; Volodymyr V. Kindratenko (CoRR, 2024)

Transforming the Hybrid Cloud for Emerging AI Workloads. - Deming Chen; Alaa Youssef; Ruchi Pendse; André Schleife; Bryan K. Clark; Hendrik F. Hamann; Jingrui He; Teodoro Laino; Lav R. Varshney; Yuxiong Wang; Avirup Sil; Reyhaneh Jabbarvand; et al. (CoRR, 2024)

ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study. - Eric Modesitt; Ke Yang; Spencer Hulsey; Chengxiang Zhai; Volodymyr V. Kindratenko (CoRR, 2024)

Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2. - Zilinghan Li; Shilan He; Pranshu Chaturvedi; Volodymyr V. Kindratenko; Eliu A. Huerta; Kibaek Kim; Ravi K. Madduri (Comput. Sci. Eng., 2024)

ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study. - Eric Modesitt; Ke Yang; Spencer Hulsey; Xin Liu; ChengXiang Zhai; Volodymyr V. Kindratenko (ACL (Findings), 2025)

TinyHelen's First Curriculum: Training and Evaluating Tiny Language Models in a Simpler Language Environment. - Ke Yang; Volodymyr V. Kindratenko; ChengXiang Zhai (CoRR, 2025)

Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks. - Ayush Khot; Xiwei Wang; Avik Roy; Volodymyr V. Kindratenko; Mark S. Neubauer (CoRR, 2025)

Diff-Ensembler: Learning to Ensemble 2D Diffusion Models for Volume-to-Volume Medical Image Translation. - Xiyue Zhu; Dou Hoon Kwark; Ruike Zhu; Kaiwen Hong; Yiqi Tao; Shirui Luo; Yudu Li; Zhi-Pei Liang; Volodymyr V. Kindratenko (CoRR, 2025)

Neural reservoir control of a soft bio-hybrid arm. - Noel M. Naughton; Arman Tekinalp; Keshav Shivam; Seung Hung Kim; Volodymyr V. Kindratenko; Mattia Gazzola (CoRR, 2025)

FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud. - Aditya Sinha; Zilinghan Li; Tingkai Liu; Volodymyr V. Kindratenko; Kibaek Kim; Ravi K. Madduri (CoRR, 2025)

Hierarchical Diffusion Framework for Pseudo-Healthy Brain MRI Inpainting with Enhanced 3D Consistency. - Dou Hoon Kwark; Shirui Luo; Xiyue Zhu; Yudu Li; Zhi-Pei Liang; Volodymyr V. Kindratenko (CoRR, 2025)