John Talburt, Ph.D.

Dr. Talburt is a Distinguished Professor of Computer and Information Sciences and the Acxiom Chair for Information Quality. He also holds the Vision for the Future Endowed Chair and is the Graduate Coordinator for the Information Quality Program.

PhD, University of Arkansas, Fayetteville
Major: Mathematics
Dissertation Title: Computational Methods for Problems in Finite Solvable Group Theory

MS, University of Arkansas, Fayetteville
Major: Mathematics

BS, Arkansas State University
Major: Mathematics
Minor: Physics

Dr. Talburt is the Executive Director of the Center for Advanced Research in Entity Resolution and Information Quality (ERIQ) at the University of Arkansas at Little Rock. The ERIQ Center conducts advanced research in entity resolution, master data management, information quality management, and data and AI governance. Current research focuses on how AI language models and vision models can be used to enhance the effectiveness of these systems and processes.

PATENTS AND INVENTIONS

Morgan, C.D., Talley, T., Talburt, J. R., Bussell, C., Kooshesh, A., Anderson, W., Johnston, K., Farmer, R., Hashemi, R., Dobrovich, M., Baxter, R., Ward, M. K., & Ratliff; J. K. (2003) Data linking system and method using tokens, U.S. Patent No. 6,523,041. Washington, DC: U.S. Patent and Trademark Office.

Morgan, C.D., Talburt, J.R., Harvey, S., Talley, T., Anderson, W.E., Welch, S.K., & White, C.S. (2003) Data linking system and method using encoded links, U.S. Patent Number 6,766,327 B2, European Patent Office Application 03254567.5.

Morgan, C.D., McLaughlin, G.L., Fogata, M.G., Baker, J.L., Cook, J.E., Mooney, J.E., Roland, D.B., & Talburt, J.R. (2000) Method and system for the creation, enhancement, and update of remote data using persistent keys, U.S. Patent 6,073,140. Washington, DC: U.S. Patent and Trademark Office.

BOOKS

Talburt, J.R. & Zhou, Y. (2015) Entity Information Life Cycle for Big Data: Master Data Management and Information Integration, Morgan Kaufmann.

Yeoh, W., Talburt, J.R., & Zhou, Y. (Eds.) (2014) Information Quality and Governance for Business Intelligence. IGI Global.

Talburt, J.R. (2011) Entity resolution and information quality. Burlington, MA: Morgan Kaufmann (Elsevier).

Chan, Y., Talburt, J., & Talley, T. (Eds.) (2010). Data engineering: Mining, information and intelligence. Norwell, MA: Springer.

RECENT BOOK CHAPTERS

Kabir, M.R., Altaf, A.M., Morshed, M.S., Milanova, M., & Talburt, J.R. (2025) Entity Resolution Using Transformers for Synthetic Datasets, In: Jain, L.C., Mironov, R.P., Kountcheva, R.A., Draganov, I. (eds) New Approaches for Multidimensional Signal Processing. NAMSP 2024. Smart Innovation, Systems and Technologies, vol 437. Springer, Singapore. https://doi.org/10.1007/978-981-96-2482-9_8

Althaf, A.M., Morshed, M.S., Kabir, M.R., Milanova, M., Talburt, J.R. (2025). Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach. In: Palaiahnakote, S., Schuckers, S., Ogier, JM., Bhattacharya, P., Pal, U., Bhattacharya, S. (eds) Pattern Recognition. ICPR 2024 International Workshops and Challenges. ICPR 2024. Lecture Notes in Computer Science, vol 15618. Springer, Cham. https://doi.org/10.1007/978-3-031-88220-3_7

Mohammed, O.K., Talburt, J.R., Syed, K., Siddiqui, A.S., Mohammed, A., Tarannum, A., & Mohammed, F. (2024). Household discovery with group membership graphs. In: Latifi, S. (eds) ITNG 2024: 21st International Conference on Information Technology-New Generations. ITNG 2024. Advances in Intelligent Systems and Computing, vol 1456. Springer, Cham. https://doi.org/10.1007/978-3-031-56599-1_31

Kobayashi, F., Talburt, J.R. (2025). Using Linkage Context for Automated Correction in Unsupervised Entity Resolution. In: Deligiannidis, L., Ghareh Mohammadi, F., Shenavarmasouleh, F., Amirian, S., Arabnia, H.R. (eds) Image Processing, Computer Vision, and Pattern Recognition and Information and Knowledge Engineering. CSCE 2024. Communications in Computer and Information Science, vol 2262. Springer, Cham. https://doi.org/10.1007/978-3-031-85933-5_19

Xu, X., Foua, B.T., Wang, X., Gunasekaran, V., & Talburt, J.R. (2024) Leveraging large language models for efficient representation learning for entity resolution. In Artificial Intelligence: Machine Learning, Convolutional Neural Networks and Large Language Models, edited by Leonidas Deligiannidis, George Dimitoglou and Hamid Arabnia, Berlin, Boston: De Gruyter, 2024, pp. 373-394. https://doi.org/10.1515/9783111344126-017

Xu, X., Foua, B.T., Wang, X., Gunasekaran, V., & Talburt, J.R. (2024) TOAA: Train once, apply anywhere. In Artificial Intelligence: Machine Learning, Convolutional Neural Networks and Large Language Models, edited by Leonidas Deligiannidis, George Dimitoglou and Hamid Arabnia, Berlin, Boston: De Gruyter, 2024, pp. 395-426. https://doi.org/10.1515/9783111344126-018

Seker, E., Talburt, J.R. and Greer, M.L., (2022). Preprocessing to address bias in healthcare data. In Seroussi, B, Weber, P, & Dhombres, F. (Eds.) Challenges of Trustable AI and Added-Value on Health, p.327.

RECENT JOURNAL ARTICLES

Talburt, J.R., Mohammed, M.A., Cakmak, M.C., Mohammed, O.K., Mohammed, M.K., Syed, K., & Claassens, L. (2026) Case Count Metric for Comparative Analysis of Entity Resolution Results, Frontiers in Big Data, Volume 9 – 2026, https://doi.org/10.3389/fdata.2026.1736939

Aatif, M., Mohammed, M. A., Milanova, M., Talburt, J., & Cakmak, M. C. (2025). Multi-Agent RAG Framework for Entity Resolution: Advancing Beyond Single-LLM Approaches with Specialized Agent Coordination. MDPI Computers, 14(12), 525. https://doi.org/10.3390/computers14120525.

Ma, J, McQuay, C., Talburt. J.R. Tiwari, A.K., & Yang, M.Q. (2025) Single-cell transcriptomic analysis unveils key regulators and signaling pathways in lung adenocarcinoma progression. Biomedicines, 2025, 13, 1606, https://doi.org/10.3390/biomedicines13071606.

Sajid, B., Abu-Halimeh, A, & Talburt, J.R. (2025) SSN filtering method with pre-trained models for entity matching in data washing machine, AI Insights, 2025; 1(1): 1929, https://doi.org/10.62617/aii1929.

Hagan, N.K.A. & Talburt, J.R. (2024) SparkDWM: A scalable design of a Data Washing Machine using Apache Spark. Frontiers in Big Data: Data Mining and Management Section, Volume 7 – 2024 | https://doi.org/10.3389/fdata.2024.1446071.

Hagan, N.K.A, Talburt, J.R., Anderson, K.E., & Hagan, D. (2024) A scalable MapReduce-based design of an unsupervised entity resolution system. Frontiers in Big Data: Data Mining and Management Section, Volume 7 – 2024 | https://doi.org/10.3389/fdata.2024.1296552.

Zhang, W., Huckaby, B., Talburt, J.R., Weissman, S., & Yang, M.Q. (2024) cnnImpute: missing value recovery for single cell RNA sequencing data. Scientific Reports, (2024) 14:3946, http://doi.org/10.1038/s41598-024-53998-x.

Talburt, J.R., Ehrlinger, L, & Magruder, J. (2023) Editorial: Automated data curation and data governance automation. Frontiers in Big Data: Data Mining and Management Section, Vol 6-2023, 10.3389/fdata.2023.1148331.

Ebeid, I., Talburt, J.R., Hagan, N.K., & Siddique, M.A. (2022) ModER: Graph-based Unsupervised Entity Resolution using Composite Modularity Optimization and Locality Sensitive Hashing. International Journal of Advanced Computer Science and Applications (IJACSA), 13(9), August 2022.

Ma, J., Pettit, N., Talburt, J.R., Wang, S., Weissman, S.M., & Yang, M. (2022). Integrating single-cell transcriptome and network analysis to characterize the therapeutic response of chronic myeloid leukemia. International Journal of Molecular Sciences 2022, 23, 14335. https://doi.org/10.3390/ijms232214335

Wang, Z., Talburt, J.R., Wu, N., Dagtas, S. and Zozus, M.N., (2020). A rule-based data quality assessment system for electronic health record data. Applied clinical informatics, 11(04), pp.622-634.

Talburt. J.R., Al Sarkhi, A., Pullen, D, Claassens, L, & Wang, R. (2020). An iterative, self-assessing entity resolution system: First steps toward a data washing machine. International Journal of Advanced Computer Science and Applications, 11(12) pp. 680-689, https://par.nsf.gov/servlets/purl/10219479.

Parmar, P., Morris, M., Talburt, J.R., & Syed, H. (2020) Variations in Outcome for the same Map Reduce Transitive Closure Algorithm Implemented on Different Hadoop Platforms, International Journal of Computer Science & Information Technology, 12(4), pp. 27-34.

Al Sarkhi, A. & Talburt, J.R. (2020) A Scalable, Hybrid Entity Resolution Process for Unstandardized Entity References, The Journal of Computing Sciences in Colleges, 35(9), pp. 19-29.

Gadde, M.A., Wang, Z., Zozus, M., Talburt, J.R. & Greer, M.L. (2020) Rules-Based Data Quality Assessment on Claims Database, Studies in Health Technology and Informatics, Vol. 272, pp. 350-353.

RECENT CONFERENCE ARTICLES

Sasirekha, O., Talburt, J.R., & Cakmak, M.C. (2026) Household Movement Detection in Mixed-Format Occupancy Data Using LLM-Based Entity Resolution, Proceedings of the 6th International Conference on NLP & Data Mining, NLDM 2026, Vancouver, Canada, May 23-24, 2026, pp. 11-30, DOI: 10.5121/csit.2026.1601002

Mohammed, M.A., Talburt, J.R., Mohammed, A., Syed, K. (2025). Entity Resolution with Household Movement Discovery Using Google Generative AI. In: Latifi, S. (eds) The 22nd International Conference on Information Technology-New Generations (ITNG 2025). ITNG 2025. Advances in Intelligent Systems and Computing, vol 1463. Springer, Cham. https://doi.org/10.1007/978-3-031-89063-5_41.

Al Mandalawi, S., Mohammed, M.A., Cakmak, M.C., Tarannum, A., Maclean, H.C., & Talburt. J.R. (2026) A Coordinated Multi-Agent Architecture for Automated Data Governance Using Large Language Models, Proceedings of the 23rd International Conference on Information Technology – New Generations, ITNG 2026,.

Mohammed, M.A., Tarannum, A., Dailey, E.D., Johnson, M., Cakmak, M.C., & Talburt. J.R. (2026) AI-Powered Multi-Stakeholder Ecosystems for Global Development: A Design Research Study on the GSI D-Hub Proof-of-Concept Platform, Proceedings of the 23rd International Conference on Information Technology – New Generations, ITNG 2026, https://doi.org/10.48550/arXiv.2603.06584

Mohammed, A.A.T., Cakmak, M.C., & Talburt. J.R. (2026) A Hybrid Entity Resolution Pipeline Integrating LLM Intelligence, Semantic Clustering, and Household Movement Analysis, Proceedings of the 23rd International Conference on Information Technology – New Generations, ITNG 2026. (Accepted for Publication)

Maclean, H.C., Cakmak, M.C., Mohammed, M.A., Al Mandalawi, S., & Talburt. J.R. (2025) Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems, Proceedings of the 23rd International Conference on Information Technology – New Generations, ITNG 2026, https://doi.org/10.48550/arXiv.2601.18012.

Tarannum, A., Mohammed, M.A., Cakmak, M.C., Al Mandalawi, S., & Talburt. J.R. (2025) A System for Name and Address Parsing with Large Language Models, Proceedings of the 23rd International Conference on Information Technology – New Generations, ITNG 2026, https://doi.org/10.48550/arXiv.2601.18014.

Mohammed, M.A., Talburt, J.R., Muhammad, A., & Milanova, M. (2025) Multi-LLM record linkage: A comparative analysis framework for co-residence pattern discovery. Proceedings: World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE’25), Springer, (accepted for publication)

Mohammed, M.A., Al Mandalawi, S., Maclean, H., & Talburt, J.R., (2025) Multilingual customer record linkage: A novel approach using LLMs for cross-lingual entity resolution. Proceedings: World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE’25), Springer, (accepted for publication)

Mohammed, M.A., Talburt, J.R., Claassens, L., & Marais, A. (2025) Retrieval-Augmented Multi-LLM Ensemble for Industrial Part Specification Extraction. Proceedings: 17th International Conference on Knowledge and System Engineering (KSE 2025), Da Lat, Vietnam, 2025, pp. 1-6, IEEE Press, DOI: 10.1109/KSE68178.2025.11309590.

Muhammad, A., Mohammed, M.A., Milanova, M., Talburt, J.R., & Cakmak, M. (2025) Policy-Aware Generative AI for Safe, Auditable Data Access Governance. Proceedings: 17th International Conference on Knowledge and System Engineering (KSE 2025), Da Lat, Vietnam, 2025, pp. 1-6, IEEE Press, DOI: 10.1109/KSE68178.2025.11309632.

Althaf, A.M., Morshed, M.S., Kabir, M.R., Milanova, M., & Talburt, J.R. (2025) Semantic Entity Resolution on Synthetic Datasets: A Transformer-Centric Approach. Proceedings: International Conference on Pattern Recognition (ICPR 2024), Vol.15618, pp. 107-116. Springer, Cham. pp. 107-116, Springer, DOI: 10.1007/978-3-031-88220-3_7.

Mohammed, M.A., Talburt, J.R., Mohammed, A., & Syed, K. (2025) Entity resolution with household movement discovery using Google generative AI, Proceedings of the 22nd International Conference on Information Technology – New Generations, ITNG 2025. Advances in Intelligent Systems and Computing, vol 1463, pp. 469-481, Springer, https://doi.org/10.1007/978-3-031-89063-5_41.

Syed, K., Mohammed, O.K., Talburt, J.R., Tarannum, A., Mohammed, A., Mir, A.M., Mohammed, M.K. (2025). Improving Quality of Entity Resolution Using a Cascade Approach. Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025), Vol. 3, pp. 60-69, SCITEPRESS, DOI: 10.5220/0013077400003890.

Mohammed, O.K., Syed, K., Mohammed, O.K., Talburt, J.R., Tarannum, A., Kashif, A.K.K., Kahan, S., Syed, N., & Mehdi, S.Y. (2025). A Pattern-Based Approach to Name and Address Parsing with Active Learning. Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025), Vol. 3, pp. 60-69, SCITEPRESS, DOI: 10.5220/0013077500003890.

Anderson, K.E., Talburt, J.R., Hagan, N.K.A., Zimmerman, T.J., & Hagan, D. (2023) Optimal starting parameters for unsupervised data clustering and cleaning in the Data Washing Machine. Proceedings: Future Technologies Conference, K. Arai (Ed.): FTC 2023, LNNS 814, pp. 106–125, 2023. https://doi.org/10.1007/978-3-031-47451-4_8

Sarker, M.I., Milanova, M., & Talburt, J.R. (2023) Explaining multimodal image retrieval using a vision and language task model. Proceedings: ITNG 2023 20th International Conference on Technology-New Generations, Advances in Intelligent Systems and Computing (pp. 351-357). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-28332-1_40

Ma, J., Epperson, N., Talburt, J.R., & Yang, M.Q. (2023) A deep learning-based model for gene regulatory network inference. 2023 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA, 2023, pp. 546-550, doi: 10.1109/CSCI62032.2023.00097.

Foua, B.T., Talburt, J.R., & Xu, X. (2023) Large language model-based representation learning for entity resolution using contrastive learning. 2023 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA, 2023, pp. 15-22, doi: 10.1109/CSCI62032.2023.00010.

Foua, B.T., Wang, X., Talburt, J.R., & Xu, X. (2023) Train once, match everywhere: Harnessing generative language models for entity matching. 2023 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA, 2023, pp. 30-36, doi: 10.1109/CSCI62032.2023.00012.

Senapati, B., Talburt, J.R., Naeem, A.B. and Batthula, V.J.R. (2023) Transfer learning-based models for food detection using ResNet-50. In 2023 IEEE International Conference on Electro Information Technology (eIT), pp. 224-229. IEEE, 2023. 10.1109/eIT57321.2023.10187288

Mohammed, M., Talburt, J.R., Syed, H., & Mehjabeen. (2023) Metadata: An integral component of the modern data strategy. Proceedings: CSCE 2023 The 2023 World Congress in Computer Science, Computer Engineering & Applied Computing, July 24-27, 2023, Las Vegas, IEEE Press, DOI: 10.1109/CSCE60160.2023.00267

Kobayashi, F. & Talburt, J.R. (2023) Context extraction in unsupervised entity resolution. 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE), Las Vegas, NV, USA, 2023, pp. 1842-1848, doi: 10.1109/CSCE60160.2023.00304.

Mohammed, M. & Talburt, J.R. (2021) A Zero Trust Model Based Framework for Data Quality Assessment, Proceedings: The 2021 International Conference on Computational Science and Computational Intelligence, December 15-17, 2021, IEEE Press, DOI: 10.1109/CSCI54926.2021.00123

Zhang, W., Yang, W., Talburt, J.R., Weissman, S., Yang, M. (2021), Missing value recovery for single cell RNA sequencing data”, International Conference on Computational Science and Computational Intelligence CSCI’21. pp. 344-348. 2021 IEEE Computer Society, 10.1109/CSCI54926.2021.00129.

Yang, J.Y., Wu, X, Chen, G, Yang, W., Talburt, J.R., Xie, H, Fang, Q. Wang, S., & Yang, M.Q. (2021) Merging Deep Learning and Data Analytics for Inferring Coronavirus Human Adaptive Transmutability and Transmissibility. In: Arabnia, H.R., Ferens, K., de la Fuente, D., Kozerrnko, E.B., Olivas Varela, J.A., & Tinetti, F.G. (eds) Advances in Artificial Intelligence and Applied Cognitive Computing. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70296-0_21

Kobayashi, F., Talburt, J.R. (2021), & Al Sarkhi, A. (2021) Token Correction for the Data Washing Machine: Types and Comparisons. Proceedings: The 2021 World Congress in Computer Science, Computer Engineering & Applied Computing Conference (CSCE-2021) (in press)

Awarded the Vision for the Future Endowed Chair for Information Quality, April 2025

Faculty Excellence Award for Research and Creative Endeavors, Donaghey College of Science, Technology, Engineering, and Mathematics, March 2024

We Heart Faculty Award for the 2020-2021 School Year, Awarded by the Student Government Association, May 2021

I Heart Graduate Faculty Award for the 2020-2021 School Year for the Donaghey College of Science, Technology, Engineering, and Mathematics, Awarded by the UA Little Rock Graduate Student Association, May 2021

CDO Magazine’s List of Top Academic Data Leaders for 2021, 2022, 2023, 2024

International Association for Information and Data Quality 2014 Distinguished Member Award, October 9, 2014

University of Arkansas at Little Rock, Donaghey College of Engineering and Information Technology, 2014 Faculty Excellence Award for Research, April 10, 2014

University of Arkansas for Medical Sciences Office of Research Compliance Certificate of Appreciation, in Recognition of Outstanding Service and Significant Contributions to the Certified Research Specialist Program, April 18, 2012

MIT Information Quality Industry Symposium, Recognition for Leadership, July 14, 2010

Data Management Association, International, 2008 Academic Award

Principles of Information Quality, INFQ 70303

Entity Resolutions and Information Quality, INFQ 74803

Project and Change Management, INFQ 73703

IQCP, Information Quality Certified Professional, International Association for Information and Data Quality (IAIDQ), 2011

MDQM, Certified Master Data Quality Manager for ISO 8000-110: 2009 Master Data Quality, Electronic Commerce Code Management Organization (ECCMA), 2011.

CDMP, Certified Data Management Professional, Institute for Certification of Computer Professionals (ICCP), 2008

CDP, Certificate in Data Processing, Institute for Certification of Computer Professionals (ICCP), 1981.

International Society of Chief Data Officers (isCDO), since 2016

Association for Computing Machinery (ACM), since 1984

Arkansas Academy of Computing (AAoC), Charter Member since 2006

Data Governance Professionals Organization (DGPO), since 2017

International Association for Data Quality, Governance, and Analytics (IADQGA), since 2020

Member of the U.S. Technical Advisory Group to the International Organization for Standardization (ISO), Technical Committee 184, Sub-Committee 4, Working Group 13 for Data Quality Standards, appointed 2016

Coordinator for the UA Little Rock Information Quality Graduate Program, appointed 2010

Executive Director, UA Little Rock Center for Advanced Research in Entity Resolution and Information Quality (ERIQ), appointed 2006

Univ of Arkansas at Little Rock, Donaghey College of Science, Technology, Engineering, and Mathematics
2025 – present  Distinguished Professor of Computer and Information Sciences, Acxiom Chair of Information Quality, and Vision for the Future Endowed Professorship
2007 – 2025 Professor of Information Science and Acxiom Chair of Information Quality
2005 – 2007 Visiting Professor of Information Science and Acxiom Chair of Information Quality

Noetic Partners, Inc., Great Falls, VA
2018 – Present Partner and Lead Consultant for Data Governance, Data Quality, and Master Data Management

Chief Data Officer Certification Program, Boston, MA
2024 – Present Instructor and Subject Matter Expert, Data Curation and Master Data Management

Black Oak Analytics, Inc., Little Rock, Arkansas
2008 – 2017 Co-Founder and Chief Scientist

Acxiom Corporation, Little Rock, Arkansas
2004 – 2005 Division Leader for New Products and Solutions, Acxiom Marketing Organization
2000 – 2004 Leader for Global Data Development, Product and Infrastructure Technology Organization
1999 – 2000 Leader for Advanced Technology & Research, Enterprise Software Development Group
1998 – 1999 Leader for Data Research and Development, Data Content Group
1995 – 1998 Leader for Research and Development, Advanced Technology Group

University of Arkansas at Little Rock, College of Science and Engineering Technology
1991 – 1995 Professor of Computer and Information Science
[1986 – 1993] Chair, Department of Computer and Information Science
1983 – 1991 Associate Professor of Computer and Information Science

Professional Computer Software, Inc., Batesville, Arkansas
1981 – 1983 President and CEO

Carter, Mitchum, and Company, CPA’s, Batesville, Arkansas
1980 – 1981 Information Systems Manager

Data Management Services, Batesville, Arkansas
1977 – 1980 Owner and Operator

Columbus State University, Columbus, Georgia
1974 – 1977 Associate Professor of Mathematics and Computer Science
[1973 – 1977] Campus Coordinator for Academic Computing
1971 – 1974 Assistant Professor of Mathematics and Computer Science