Minh Nguyen

I am 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 am very fortunate to work with Anjana Susarla (MSU), Rema Padman (CMU), and Xiao Liu (ASU) on several causal machine learning projects using social media data. I received PhD in Economics and Master in Mathematics from University of Hawaii in 2023 under the supervision of Ruben Juarez and Farzana Nasrin, respectively. 

I am also a  Research Affiliate at the Applied AI in Business and Economics Lab at Vietnam National University HCMC. 

I study causal AI/ML and transformative AI/ML in the contexts of information systems, business analytics, and computational social sciences using a wide range of causal and predictive methods. My research employs causal inference and machine learning in observational and empirical settings where traditional causal methods (e.g., quasi-experimental methods) are hard to apply. My work has been published in leading academic journals including Journal of Forecasting and Early Childhood Research Quarterly. 

My research has been supported by National Institutes of Health (NIH), State of Hawaii Department of Health (DOH), National Institute of Food and Agriculture (NIFA), and Institute of Management Accountants (IMA) in the United States. 

I am open to any collaborations related to my research interests. You can reach me at minhn@msu.edu. I am also on LinkedIn and X. 

• Mar: I was accepted to join the Summer Institute the Summer Institutes in Computational Social Science (SICSS) at Carnegie Mellon University on May 12-23, 2025.
• Jan: We received the Best Award Papers 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, and then will be published as a chapter in the Springer book titled Data Science for Econometrics and Related Topics. 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. Hooray!

• 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 titled Artificial Intelligence and Machine Learning for Econometrics: Applications and Regulation. 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, and then will be published as a chapter in the Springer book titled Data Science for Econometrics and Related Topics. 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

• Sep: One of our manuscripts got 1st round revision at Information Systems Research. 

• Sep: My colleagues and I have submitted a grant proposal on health communication in Vietnam to the National Foundation for Science and Technology Development or NAFOSTED (Vietnam's NSF).

• 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).

• Jun: I was reappointed as a Postdoc Researcher at Broad College of Business, Michigan State University. 

• 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 "Does Dr. YouTube affect medical decision making?" was invited to present at INFORMS 2024 in the session of Advances in Machine Learning and Decision Analytics this October in Seattle, USA. 

• 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.