Minh Nguyen

I am an Assistant Professor at the Department of IT and Operations Management, Florida Atlantic University. I am the founder of Viet AI & Business Academic Network, a network to connect Vietnamese scholars worldwide who are interested in doing research in the intersection of AI and business. I also founded Causal Inference and AI Lab (CIAI Lab). I will organize AI & Causal Inference Seminar (online) for any topics related to AI and/or causal inference in Fall 2026. Please let me know if you want to present at this seminar series. 

I was a Postdoctoral Researcher in information systems and causal machine learning at the Department of Accounting and Information Systems, Broad College of Business, Michigan State University. I was very fortunate to work with Anjana Susarla (MSU), Rema Padman (CMU), and Xiao Liu (ASU) on several causal machine learning and LLMs projects using social media data. I received double degrees, PhD in Economics and Master in Mathematics, from University of Hawaii at Manoa in 2023 under the supervision of Ruben Juarez and Farzana Nasrin, respectively. 

I develop methods/theories and do empirical work in causal inference, science of science, information systems, and AI/ML. 

My work has been published in leading journals such as Information Systems Research and Journal of Forecasting, and presented at good conferences/workshops such as AMCIS, PACIS, HICSS, WeB, SCECR, INFORMS, ACIC, APPAM, COMPSTAT, SIAM, and IEEE CogMi. You can check more complete list of my work at Google Scholar. 

My research has been supported by National Science Foundation (NSF), National Institutes of Health (NIH), State of Hawaii Department of Health (DOH), National Institute of Food and Agriculture (NIFA), Institute of Management Accountants (IMA), Robert Wood Johnson Foundation, and Samuel N. and Mary Castle Foundation in the United States. 

I am open to any collaborations related to my research interests. I am also seeking curious students and mentees to work with. You can reach me at minhnguyen@fau.edu. I am also on LinkedIn and X. 

• Jul: Our paper on "p-hacking and publication bias" was accepted to publish at Information Systems Research. Link
• Jun: Our paper on "Economic Value of AI Innovation" was accepted to present at PACIS 2026. Link
• Jun: I founded the Causal Inference and AI Lab (CIAI Lab) with members come from various institutions.
• Jun: I gave a talk on causal inference with DAGs at SICSS-FAU on June 3. 
• Jun: I attended 2026 Penn Causal Inference Summer Institute in on June 1-5, 2026.
• May: New working paper "Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference". arXiv
• May: I attended three 2026 ACIC short courses on (1) Causal ML for Discovering Heterogeneous Treatment Effects (Instructors: Falco J. Bargagli-Stoffi - UCLA, Melody Huang - Yale, Tiffany Tang - Notre Dame, and Ana Maria Kenney - UCI); (2) "Robust Methods for Non-Regular Causal Inference" (Instructors: Matteo Bonvini - Rutgers, Zijian Guo - Zhejiang, and Siyu Heng - NYU); and (3) "Causal Inference in Networks: Applications to Public Health" [Github] (Instructors: Ashley Buchanan and Natallia Katenka - University of Rhode Island)
• May: I organized the 1st AI & Business Conference (online) on May 9. Looking forwad to 2nd conference in Fall 2026.
• Apr: Our work on cyber readiness was featured on SecureTalk Podcast (also YouTube, Spotify and Apple Podcasts)
• Apr: Our paper on data scraping policies was accepted to present at AMCIS 2026.
• Apr: Two posters accepted to present at the 2026 American Causal Inference Conference (ACIC): "Causal Discovery in Game Telemetry", and "When Do Observational Causal Conclusions Survive? Evidence from Patient Access to Medical Records".
• Mar: We presented two posters on "Flying to the cruise in Miami: Predicting passenger satisfaction in cruise-linked air travel using machine learning" [SSRN] and "Data-driven framework for household energy segmentation and prediction" at  the 2026 ASA Florida Chapter Meeting on March 6-7 at FIU. 
• Feb: Our work on cybersecurity readiness was featured on BingUNews, theFreesheet, and SecureWorld.
• Feb: New working paper: "Just Do It vs. Why Do It: Predicting How Consumers Respond to Nike's Reflective Campaign Slogan".
• Feb: New working paper: "Tracing the Evolution of Word Embedding Techniques in NLP". arXiv
• Feb: New working paper: "Effect-Level Validation for Causal Discovery in Game Telemetry". arXiv
• Jan: Our book proposal titled "Information Systems Research in Vietnam" was approved by Springer. We are now calling for book chapters. Link
• Jan: I presented a talk on cybersecurity readiness at HICSS 2026 in Hawaii. Link

• Dec: I served as the Session Chair in the AI & Reviews session at the Workshop in e-Business (WeB) on Dec 13.
• Nov: My co-authors presented two papers at the 2025 ICCCI conference in Ho Chi Minh City, Vietnam: "Topological Framework for Exploring Imbalanced Time Series" (Link) and "Measuring Causal Effects of Online Medical Records on Medical Decision Making Using Causal Machine Learning" (Link).
• Oct: Our paper on "When alignment speaks louder: The subtle power of consistency in online reviews" has been accepted to present at the Workshop on e-Business (WeB) 2025 on Dec 13 in Nashville. 
• Oct: Our paper on "Cross-Country Analysis of Discourse on Misinformation in the Digital Platform Using Topic Modeling" has been accepted at the IEEE CogMI 2025 conference. Link
• Aug: Our manuscript on cybersecurity readiness was conditionally accepted to present at HICSS 2026 in Hawaii.
• Aug: I have officially started my new position as an Assistant Professor of Information Technology and Operations Management at Florida Atlantic University.
• Jul: I officially ended my postdoc at Broad College of Business, Michigan State University. 
• Jun: Our two papers on "Topological Framework for Exploring Imbalanced Time Series" and "Measuring Causal Effects of Online Medical Records on Medical Decision Making Using Causal Machine Learning" (Link) have been accepted for presentation at the 17th International Conference on Computational Collective Intelligence (ICCCI 2025) in Ho Chi Minh City, Vietnam.
• May: Our paper on "An Empirical Analysis of External and Internal Factors Affecting Manufacturing Firm Failure and Resilience" has been published online on Journal of Corporate Accounting & Finance. Link
• May: I founded a group (Viet AI & Business Academic Network) for Vietnamese scholars and students worldwide who do research in the intersection of AI and business. 
• May: I will join Florida Atlantic University (Department of ITOM, College of Business) as Assistant Professor of Information Technology and Operations Management in August 2025. 
• Mar: I was accepted to join the Summer Institutes in Computational Social Science (SICSS) at Carnegie Mellon University on May 12-23, 2025.
• Jan: We received the Best Award Paper prize (awarded to the top three papers) for our paper titled "Hybrid Machine Learning Models Using a Soft Voting Classifier for Financial Distress Prediction" at the 8th International Econometric Conference of Vietnam, held at the Banking University, Vietnam, on January 13-15, 2025. Slides
• Jan: New preprint "Text as treatment from financial reports: Effects of natural hazard risk on firm profitability using causal machine learning" is available at SSRN. Any feedback is highly appreciated! Link

• Dec: Our paper titled "Effects of social media on religious belief: Causal machine learning approach" was officially accepted to present at the 18th International Conference of Thailand Econometrics Society in Chiang Mai, Thailand, in 1/2025. Link

• Nov: I presented an invited talk on "Financial distress prediction using machine learning: Some recent results" at the Conference on Applications of AI in Business and Management at Vietnam National University on Nov 15, 2024. 

• Nov: I was accepted to attend the 2024 Africa Training Workshop in Econometrics on "Causal Machine Learning and Modeling with Big Data in Economics" in 12/2024.

• Nov: Our paper titled "Hybrid machine learning models using soft voting classifier for financial distress prediction" was officially accepted for publication as a chapter in the Springer book. Link

• Nov: Our paper on "Corporate financial distress prediction in a transition economy" was finally assigned Vol and Number in Journal of Forecasting. Link

• Oct: I presented one poster and one invited talk at the 2024 INFORMS Annual Meeting in Seattle.

• Oct: I presented an invited talk on p-hacking and publication bias at the course named "Empirical Methods in Business Research" for PhD students at Broad College of Business, Michigan State University. 

• Oct: Our paper titled "Effects of social media on religious belief: Causal machine learning approach" was conditionally accepted to present at the 18th International Conference of Thailand Econometrics Society in Chiang Mai, Thailand, in 1/2025. Link

• Oct: Our paper titled "Hybrid machine learning models using soft voting classifier for financial distress prediction" was conditionally accepted at the Springer book titled Artificial Intelligence and Machine Learning for Econometrics: Applications and Regulation. Link

• Aug: Our paper on "Hybrid machine learning models using soft voting classifier for financial distress prediction" is now available on SSRN. Link

• Aug: Our paper on "Corporate financial distress prediction in a transition economy" was just published online in Journal of Forecasting. Link

• Aug: I chaired a session on Mechanism, Application at the 2024 AMES in E/SE Asia in Ho Chi Minh City, Vietnam. 

• Jul: Our manuscript on "Corporate financial distress prediction in a transition economy" was accepted for publication in Journal of Forecasting (one of the top journals in forecasting).

• May: Our paper on "Online medical record for medical decision making: Causal machine learning approach" was accepted to present at the 2024 Asia Meeting of the Econometric Society East & Southeast Asia conference (AMES 2024) this August in Ho Chi Minh City, Vietnam. 

• May: Our paper on "Close to home: Family-centered spatial analysis of access to early care and education" was just published on Early Childhood Research Quarterly. Link

• Apr: The 2nd revision of our paper on "Corporate financial distress prediction in a transition economy" was submitted to Journal of Forecasting. 

• Apr: Our paper on "Combining causal machine learning and counterfactual explanations to understand health literacy and engagement in digital platforms" was accepted to present at the 20th Symposium on Statistical Challenges in Electronic Commerce Research (SCECR 2024) this June in Lisbon, Portugal.

• Mar: Our paper on "Text as treatment from Form 10-K: Causal effects of perceived natural hazards on firm profitability" that I presented at Pre-ICIS last December is now available on AIS eLibrary. Link

• Aug: I started Postdoctoral Researcher position at Department of Accounting and Information Systems, Broad College of Business, Michigan State University. Dr. Anjana Susarla is my postdoc supervisor at MSU.
• May: I started Data Analyst position at the Research Corporation of the University of Hawaii (RCUH).
• May: I graduated with double degrees, PhD in Economics [Link] and MSc in Mathematics [Link], from University of Hawaii at Manoa.