Research

• Lauría, E.J.M. Drivers of Attrition in the First Year of College: A Bayesian Modeling Approach. SN COMPUT. SCI. 7, 634 (2026). https://doi.org/10.1007/s42979-026-05195-y.
• Damiano A., Lauría E., Sarmiento C., Zhao N., "Early Perceptions of Teaching and Learning Using Generative AI in Higher Education", Journal of Educational Technology Systems, Special Issue: Artificial Intelligence in Education, March 2024. https://doi.org/10.1177/00472395241233290.
• Balnis J., Lauría E., Yucel R., Singer H., Alisch R., Jaitovich A., "Peripheral Blood Omics and other multiplex-based systems in Pulmonary and Critical Care Medicine", American Journal of Respiratory Cell and Molecular Biology. Accepted: June 28, 2023. https://doi.org/10.1165/rcmb.2023-0153PS.
  A collaboration with Albany Medical College (Division of Pulmonary and Critical Care Medicine and Department of Molecular and Cellular Physiology); Temple University (Dept of Epidemiology and Biostatistics); University of Wisconsin School of Medicine and Public Health (Dept of Neurological Surgery).
• Bainbridge J., Melitski J., Zahradnik A., Lauría E., Jayaprakash S., Baron J., "Using learning analytics to predict at-risk students in graduate online public affairs and administration education", Journal of Public Affairs Education, 21(2), Spring 2015, 247-262. https://doi.org/10.1080/15236803.2015.12001831.
• Jayaprakash S., Moody E., Lauría E., Regan J., Baron J., "Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative", Journal of Learning Analytics, 1(1), 2014, 6-47. https://doi.org/10.18608/jla.2014.11.3.
• Duchessi P., Lauría E., "Decision tree models for profiling ski resorts' promotional and advertising strategies and the impact on sales", Expert Systems with Applications, 40(15), 1 November 2013, 5822-5829. https://doi.org/10.1016/j.eswa.2013.05.017.
• Lauría E., March E. "Combining Bayesian Text Classification and Shrinkage to Automate Healthcare Coding: A Data Quality Analysis", ACM Journal of Data and Information Quality 2(3), Article 13, December 2011. https://dl.acm.org/doi/10.1145/2063504.2063506.
• Goel S., Lauría E., "Quantification, Optimization and Uncertainty Modeling in Information Security Risks: A Matrix Based Approach", Information Resources Management Journal, 23(2), 2010, 33-52. http://dx.doi.org/10.4018/irmj.2010040103.
• Fisher C., Lauría E., Matheus C. , "An Accuracy Metric: Percentages, Randomness and Probabilities", ACM Journal of Data and Information Quality, 1(3), Article 16:1-21, December 2009. https://dl.acm.org/doi/10.1145/1659225.1659229.
• Lauría E., Duchessi P., "A methodology for developing Bayesian networks: An application to information technology (IT) implementation", European Journal of Operational Research, 179(1), 16 May 2007, 234-252. https://doi.org/10.1016/j.ejor.2006.01.016.
• Lauría, E., Duchessi, P. "A Bayesian Belief Network for IT implementation decision support", Decision Support Systems, 42(3), December 2006, 1573-1588. https://doi.org/10.1016/j.dss.2006.01.003.
• Lauria E., "Exploring the Behavioral Dimension of Client Server Technology Implementation: An Empirical Investigation", International Journal of Technology and Human Interaction, July-September 2006, 2(3), 63-81 (selected for inclusion in "End User Computing: Concepts, Methodologies, Tools and Applications", Steve Clarke (Ed.), Information Science Reference, Hershey, 2008, 1579-1594. DOI: 10.4018/jthi.2006070104.

• Gonzalez-Bonorino, A., Lauría, E. (2023). Adaptive Kevin: A Multipurpose AI Assistant for Higher Education. In: Uhomoibhi, J. (eds) Computer Supported Education. CSEDU 2022. Revised Selected Papers. Communications in Computer and Information Science, vol 1817. Springer, Cham. https://doi.org/10.1007/978-3-031-40501-3_7.
• Lauría E., Belardo S. "Information or Informing: Does it matter?", in Ralph Berndt (Ed.) Weltwirtschaft 2010: Trends und Strategien (Herausforderungen an das Management), Springer-Verlag GmbH, 2009.(click here).
• Lauria E., "An information-geometric approach to learning Bayesian network topologies from data.", D. Holmes and L.C. Jain (Eds.): Innovations in Bayesian Networks: Theory and Applications, Springer-Verlag 2008, 187-217 http://dx.doi.org/10.1007/978-3-540-85066-3_8.
• Fisher, C., Lauría, E., Chengalur-Smith, S., Wang, R. Introduction to Information Quality (textbook), MIT-IQ Press, Cambridge, MA, 2006.(click here).
• Lauria E., Tayi, G., The Quest for Business Intelligence, in Erfolgsfaktor Innovation, Zurich Graduate School of Management, Ralph Berndt (Ed.), Springer, 2005.(click here).
• Lauria E, "Bayesian Machine Learning", in Encyclopedia of Information Science and Technology, Volume I-III, Mehdi Khosrow-Pour, (Ed.) IGI Global, 2005.DOI: 10.4018/978-1-59140-553-5.ch043.
• Lauria E, Tayi G. (2003) "Bayesian Data Mining and Knowledge Discovery", in Data Mining: Opportunities and Challenges, John Wang (Ed.) Idea Group Publishing, Hershey PA. https://dl.acm.org/doi/10.5555/903826.903838.

• Lauría E., "Causal Inference for Learning Analytics: The Effect of Part-Time Instruction on First-Year Students' Final Grades", Proceedings of the 18th International Conference of Computer Supported Education (CSEDU 2026), May 18-20, 2026, Benidorm, Spain. Volume 1, pages 233-240. DOI: 10.5220/0014666400004021.
• Lauría, E. (2025). Predictors of Freshmen Attrition: A Case Study of Bayesian Methods and Probabilistic Programming. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0; ISSN 2184-285X, SciTePress, pages 120-131. DOI: 10.5220/0013555800003967. Best Paper Award 📄
• Sarmiento, C. and Lauría, E. (2025). Investigating Flavors of RAG for Applications in College Chatbots. In Proceedings of the 17th International Conference on Computer Supported Education (CSEDU), April 1-3, 2025, Porto, Portugal, Volume 2, pages 421-428. DOI: 10.5220/0013468200003932.
• Gonzalez Bonorino A., Lauría E, Presutti E., "Implementing Open-Domain Question-Answering in a College Setting: An End-to-End Methodology and a Preliminary Exploration", Proceedings of the 14th International Conference of Computer Supported Education (CSEDU 2022), April 22-24, 2022, online streaming, Vol 2, pages 66-75. DOI: 10.5220/0011059000003182.
• Lauria, E. "Framing Early Alert of Struggling Students as an Anomaly Detection Problem: An Exploration", Proceedings of the 13th International Conference of Computer Supported Education (CSEDU 2021), online streaming, April 23-25, vol 1, 26-35. Shortlisted for Best Paper Award. DOI: 10.5220/0010471900260035.
• Lauría E., Stenton E., Presutti E., "Boosting Early Detection of Spring Semester Freshmen Attrition: A Preliminary Exploration", Proceedings of the 12th International Conference of Computer Supported Education (CSEDU 2020), Online Streaming, May 2-4, 2020, vol 2, 130-138. Best Paper Award. DOI: 10.5220/0009449001300138.
• Lauría E., Presutti E., Kapogiannis M., "Of Stacks and Muses: Adventures in Learning Analytics", LatinX in AI Workshop, @ICML 2019, Long Beach, CA, June 10, 2019. https://hal.science/hal-02265832/.
• Lauría E., Presutti E., Kapogiannis M., Kamath A., "Stacking Classifiers for Early Detection of Students at Risk", Proceedings of the 10th International Conference of Computer Supported Education (CSEDU 2018), Funchal Madeira, Portugal, March 15-17, 2018, vol 1, 390-397. DOI: 10.5220/0006781203900397.
• Lauria E., Presutti E., Sokoloff M., Guarino, M., "Crossing the Chasm to Big Data: Early Detection of at-Risk Students in a Cluster Computing Environment", Practitioner Track Proceedings of the 7th International Learning Analytics & Knowledge Conference (LAK'17). Simon Fraser University, Vancouver, Canada 13–17 March. (Link).
• Jayaprakash S., Lauría E., Gandhi P, Mendhe D., "Benchmarking Student Performance and Engagement in an Early Alert Predictive System using Interactive Radar Charts", Proceedings of LAK16, Edinburgh, UK, April 25-29, 2016. https://doi.org/10.1145/2883851.2883940.
• Jayaprakash S., Baron J., Gilbert G., Lauría E., Moody E., Reagan J. "Open-source Academic Early Alert and Risk Assessment API", LAK 2015, Practitioner's Track
• Jayaprakash S., Lauría E., (2014), "Open Academic Early Alert System: Technical Demonstration", Proceedings of LAK 14 (Learning Analytics and Knowledge Conference), Indianapolis, IN, March 24-28, 2014.https://dl.acm.org/doi/10.1145/2567574.2567578.
• Regan, J., Moody, E., Lauría, E., Jayaprakash, S., Jonnalagadda, N., Baron, J. "Learning Analytics: Coming to a Classroom Near You". Poster presented at the Annual Meeting of the Association for Psychological Science, Washington, D.C., May 2013.
• Lauría E., Moody E., Jayaprakash S., Jonnalagadda N., Baron J. (2013), "Open Academic Analytics Initiative: Initial Research Findings", Proceedings of LAK 2013 (Learning Analytics and Knowledge Conference), Leuven, Belgium, April 8-12, 2013. https://doi.org/10.1145/2460296.2460325.
• Lauría E., Baron J., Devireddy M., Sundararaju V., Jayaprakash S. (2012), "Mining academic data to improve college student retention: An open-source perspective", Proceedings of LAK 2012 (Learning Analytics and Knowledge Conference), Vancouver, BC, Canada, April 29-May 2, 2012. https://dl.acm.org/doi/10.1145/2330601.2330637.
• Lauría E., Baron E. (2011), “Mining Sakai to Measure Student Performance: Opportunities and Challenges in Academic Analytics”, Proceedings of ECC2011 (Enterprise Computing Community Conference 2011) , Marist College, Poughkeepsie, NY, June 2010.
• Lauría E., Greco C. (2010), “OLAP for financial analysis and planning: a proof of concept”, Proceedings of ICSOFT 2010 (5th International Conference on Software and Data Technologies) / DMIA2010 (International Workshop on Data Management and Information Analytics), Athens, Greece, July 2010. DOI:10.5220/0003042603470355.
• Belardo S. Crnkovic J., Lauría E., "Developing an Instrument to Measure Trust in Organizations", Proceedings of Conf-IRM 2008 (International Conference on Information Resources Management), Niagara Falls, Canada, May 18-20, 2008. (AISeL link).
• Fisher C., Lauría E., Matheus C., “In search of an accuracy metric", Proceedings of the 12th international Conference on Information Quality (ICIQ-2007), Massachusetts Institute of Technology, November 2007. (MIT IQ link).
• Klingenberg, B., Lauría, E.,"Teaching the Global Dimensions of Technology Management: A Framework for Course development", Proceedings of PICMET ' 07, Portland, OR, August 2007. DOI: 10.1109/PICMET.2007.4349469.
• Lauría E., March A., "Misplacing the code: An examination of data quality issues in Bayesian text classification for automated coding of medical diagnoses", Proceedings of IRMA 2007 (Information Resource Management Association) International Conference, Vancouver, May 2007. (IRMA link).
• Lauría, E., March, A., "Effect of Dirty Data on Free Text Discharge Diagnoses used for Automated ICD-9-CM Coding", Proceedings of AMCIS 2006, the 12th Americas Conference on Information Systems, Acapulco, Mexico, August 2006. (AISeL link).
• Lauría, E., (2005), "Learning the Structure of a Bayesian Network: An Application of Information Geometry and the Minimum Description Length Principle", in Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Proceedings of the 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, San José State University, USA, Kevin H. Knuth, Ali E. Abbas, Robin D. Morris, J. Patrick Castle (Ed.), 293-301. https://doi.org/10.1063/1.2149807.
• Lauría E, Iacub P., Rozenfarb D., "Overcoming the Limitations of the ERP paradigm: a Latin American Exploration", Proceedings of IRMA 2005 (Information Resource Management Association) International Conference, San Diego, May 2005. (Paper).
• March A, Lauría E., Lantos J., "Automated ICD9-CM coding employing Bayesian machine learning: a preliminary exploration", Proceedings of SIS2004 (Simposio de Informática y Salud - SADIO),  33rd Conference on Computer Science & Operational Research, Buenos Aires, Argentina, Sept 20-24, 2004. (Paper).
• Lauría E, Duchessi P, "A Bayesian Belief Network-driven Decision Support System for Client-server Implementation", Proceedings of 2004 IFIP International Conference on Decision Support Systems, Prato, Italy, July 2004 https://doi.org/10.1016/j.dss.2006.01.003.
• Lauría E, Tayi G. (2003),  “A Comparative Study of Data Mining Algorithms for Network Intrusion Detection in the Presence of Poor Quality Data”, Proceedings of the 8th international Conference on Information Quality (ICIQ-2003), Massachusetts Institute of Technology, November 2003 MIT ICIQ 2003.
• March A, Leguiza J, Lauría E., Gomez A, G. Bernaldo de Quirós F, Luna D., "Tecnologías OLAP en la gestión de servicios de salud: su aplicación en el estudio del gasto en medicamentos.", Proceedings of SIS2001 (Simposio de Informática y Salud – SADIO), Sept 12-14, 2001. (Research funded by IBM Argentina S.A.), in Spanish. (Paper).
• March A, Lauría E., Meli F., "Computer Assisted Diagnosis Using Neural Networks. An Application for brain tumor diagnosis using computer axial tomography", Proceedings of the 1st International Conference of Medical Informatics, Buenos Aires, 1992.

• Lauría, E., Taylor, C., Fleishman, C., Presutti, E., Bardney, E., "A Monitoring Dashboard for First-Semester, First-Year Students", MCC 2026 (Marist Computing Conference), October 30, 2026.
• Lauría E., "From Early Programs to Autonomous Agents: AI's 70-Year Journey and the Future It Is Creating", D&H Canal Historical Society - AI Symposium: "Evaluating Artificial Intelligence from 10,000 feet", October 16, 2026.
• Conyiers A., Damiano A., Lauría E., "Moral Panic and Social Media: A Large Language Model Approach to Theory-Driven Discourse Analysis​" (poster), Marist Academic Research & Creativity Conference (ARC), September 23, 2026.
• Taylor, C., Fleishman, C., Lauría, E., Presutti, E., Bardney, E., "A Monitoring Dashboard for First-Semester, First-Year Students​" (poster), Marist Academic Research & Creativity Conference (ARC), September 23, 2026.
• "Agentic AI: Putting AI to Work for You" (Panel). The 2026 Hudson Valley Artificial Intelligence (AI) Summit.
  The 2026 Hudson Valley Artificial Intelligence (AI) Summit, co-hosted by Dutchess County Government and Marist University was held on the campus of Marist University in Poughkeepsie, NY. April 9th, 2026.
• Lauría E., "Causal Inference and Machine Learning in Education: Part-Time Instruction and First-Semester Freshmen", MCC 2025 (Marist Computing Conference), November 7, 2025. Second Place People's Choice Award 📄
• Gormanly B., Lauría E., "Harnessing the Power of AI: Effective Prompting and Chain of Thought", Assessment Day: Academic Conversations, Marist College, April 9, 2025.
• Lauría E., "Más Allá de la Máquina: Inteligencia Artificial en la Encrucijada de la Historia", ECIFACET 2024 - Encuentro Científico de Investigadores de la FACET, Universidad Nacional de Tucumán - Facultad de Ciencias Exactas y Tecnología, June 4 2024. (click here).
• Lauría E., "The Promise and Perils of Artificial Intelligence", Makers of History Lecture Series. D&H Canal Historical Society. March 22, 2024. (click here).
• Lauría E., "The Rise of Generative AI", 2023 Transformative Technologies Workshop: GenAI and its Implications for Accounting. American Association of Accounting. October 27, 2023 (click here).
• Lauría E., "The Generative AI Conundrum", Educational Technology Insights, August 2023. Opinion piece (click here).
• Lauría E., "GPT-like models", Educational Technology Insights, 2023. Opinion piece (an extended version of The Generative AI Conundrum article) (click here).
• Gonzalez Bonorino A., Lauría E., "AutoKevin: A Semi-Autonomous AI Knowledge Discovery System for Higher Education", 2023 Enterprise Computing Conference, Marist College, June 11-13, 2023. First Place Presentation Award in the Academic Track. (click here).
• Lauría E., "Machine Learning and the rise of data-driven AI: what's all the fuzz about?", Poughkeepsie Chapter of the Association For Computing Machinery (ACM), March 20, 2023 (click here).
• Lauría E., "The Future of Student Performance Prediction is Data-driven Analytics", Educational Technology Insights, May 2022. Interview (click here).
• Lauría, E. "Machine Learning for Early Detection of Academically At-Risk Students: Challenges, Technologies and Opportunities for Research", GTnum #IA_EO Workshop, Digital Thematic Working Groups on Artificial Intelligence and Open Education, IMT Atlantique/Lab-STICC in partnership with University of Nantes/LS2N, MEN and DANE, June 17, 2021. https://edunumrech.hypotheses.org/3265.
• Lauría E., "An Exploratory Study for Applying Anomaly Detection to Identify Academically at-risk Students", 2021 Enterprise Computing Conference, Marist College (online streaming), June 13-14, 2021. First Place Presentation Award in the Artificial Intelligence / Deep Learning / Automation category. (video: click here).
• Lauría E., "Pilas y Musas: Detección Temprana de Estudiantes en Riesgo Académico," Proyecto Vectores, Facultad de Ingeniería, Universidad de Buenos Aires, August, 2020. (video, in Spanish).
• Lauría E., Presutti E., Stenton E., "A two-stage boosted classification framework for improving early detection of freshmen attrition", 2020 Enterprise Computing Conference, Marist College (online streaming), June 7-9, 2020.
• Lauría E., "Artificial Intelligence: Wonders & Perils of XXI Century Plastics", Educational Technology Insights, March 2020. Opinion piece (click here).
• Lauría E., Presutti E., Kapogiannis M., "MUSE: Marist Universal Student Experience", 2019 Enterprise Computing Conference, Marist College, June 9-11, 2019.
• Lauría, E., Presutti, E., "MUSE: Marist Universal Student Experience", Apereo Lightning Talks: Analytics Theme, March 28, 2018. (video).
• Lauría, E., Presutti, E., "MUSE: Marist Universal Student Experience", 10th International Conference of Computer Supported Education (CSEDU 2018), Funchal Madeira, Portugal, March 15-17, 2018.
• Speaker at 24th CEEMAN Conference, "Management Education for a Digital World", Tallinn, Estonia, Sept 28-30, 2016.(Link).
• Lauria E., Kuck P., Presutti E., Jayaprakash S., Sokoloff M., "Learning Analytics at Marist College: From a Single Node Prototype to a Cluster Computing Platform", 2016 Enterprise Computing Conference, Marist College, June 12-14, 2016.
• Panel at Apache Spark Maker Community Event, Galvanize, San Francisco, (IBM-sponsored event). June 6, 2016.
• Lauría E., “Mining Sakai to Measure Student Performance: Opportunities and Challenges in Academic Analytics” (presentation of the Open Academic Analytics Initiative and discussion of preliminary results), IBM Academy of Technology Affiliates, October 4, 2011.
• Lauría, E., Gold E., Curriculum Work Session and Panel on Business Intelligence and Business Analytics, ECC2010 (2nd Enterprise Computing Community National Conference), Marist College, Poughkeepsie, NY, June 13-15, 2010.
• Lauría, E., Norton, R., Tanner, N., Baron, J., Prajugo, M., “Deconstructing Sakai: A Case Study”, Sakai Conference, Boston, MA, July 8 – 10, 2009.

• IBM Smarter Planet Innovation Faculty Award (2013 - 2014)

  Topic: curriculum development in Big Data and NoSQL (Hadoop/ MapReduce) technologies

  Funding amount: $10,000

• Member of the team that created and launched the NYS Cloud Computing and Analytics Center at Marist College, funded through New York State. The grant is part of a 92.8 million dollar package of funding for 84 projects in the Mid-Hudson Valley that will come to the region through its designation as one of three Best Plan Awardees in the ten-region competition.

  Overall funding: $3 million

  Funding period: 2013-2016

• Major Research Instrumentation grant from the National Science Foundation to acquire a new zEnterprise processor to be located in the enterprise computing research data center. The new processor will include an attached blade center (zBX) that allows research to be performed on the hardware and operating system platform of the researcher’s choice. The new equipment will be used for faculty and student research, research training, and applied research projects with New York businesses. Research areas identified in the grant proposal include large-scale business analytics, converged networking for storage and internet devices, classical thermodynamics and mathematical epidemiology, computational projects in underwater acoustics and wave propagation, and enterprise level virtualization of system resources Applied research projects include guest systems performance optimization, rapid provisioning of Linux servers and other virtual machine environments, automated workload balancing, and other green technologies.

  Principal Investigator: Dr. Roger Norton (Dean of the School of Computer Science and Mathematics)

  Co-PIs: Prof. Ron Coleman, Prof. Eitel Lauría and CIO Bill Thirsk, Vice President of Information Technology.

  Overall funding: $678,880

  Funding period: 2011- 2014

• Data Science Lead of the Open Academic Analytics Initiative (OAAI). The OAAI is funded through the Next Generation Learning Challenges (NGLC), a collaborative, multi-year grant program aimed at increasing college readiness and completion through applied technology. NGLC partners include EDUCAUSE, the League for Innovation in the Community College, the International Association for K-12 Online Learning (INACOL), and the Council of Chief State School Officers (CCSSO). Funding is being provided by the Bill & Melinda Gates Foundation and The William and Flora Hewlett Foundation.

  Overall funding: $250,000

  Funding period: 2010-2011

• IBM Smarter Planet Faculty Award for Health Care Analytics (2010-2011)

  Topic: Introduction to Healthcare Analytics

  Funding amount: $10,000

• IBM Faculty Award (2009 - 2010)

  Topic: curriculum development in Business Analytics

  Funding amount: $25,000

• Founding member of the Enterprise Computing Community, and initiative funded by the National Science Foundation to "Revitalize Undergraduate Education in Enterprise Computing." Founding members include 8 additional universities and 9 industry partners.

  Overall Funding:  $400,000

  Funding period: 2008-2010

  URL: http://ecc.marist.edu

• Project Manager at CCODC (Center for Collaborative and On-Demand Computing),  College Applied Research & Technology Center Program (CART) funded through NYSTAR (New York State Office of Science, Technology & Academic Research).

  CART Program Director, Dr. Roger Norton

  Overall funding: $2.500.000

• Title: "Learning Structure and Parameters of Bayesian Belief Networks: An Application and a Methodology in Information Technology Implementation"

  - Preview at Proquest