Jiawei Huang 黄嘉炜
My research sits at the intersection of statistics, artificial intelligence, and business.
I am Assistant Professor of Data Science at Católica Lisbon School of Business and Economics. I received my Ph.D. in Business Analytics from the Carl H. Lindner College of Business at the University of Cincinnati, an M.S. in Statistics from the University of Wisconsin–Madison, and a B.S. in Statistics from Renmin University of China.
My research centers on two themes:
- Novel statistical methodology. I contribute to nominal data analysis, configurational methods, and overparameterized models, with applications in socioeconomics, finance, and information systems.
- AI adoption for analytics. I study how AI is adopted for analytics, from large-scale text and organizational data to AI-supported experiments and systems.
I am also actively engaged in industry collaboration. Working with several partners, I have developed methods and systems that were carried through from problem definition to deployment.
Research
Published
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A Deep Manifold-Regularized Learning Model for Improving Phenotype Prediction from Multi-Modal Data
Nature Computational Science, 2(1), 38–46. Article
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Manifold Learning Analysis Suggests Strategies to Align Single-Cell Multimodal Data of Neuronal Electrophysiology and Transcriptomics
Communications Biology, 4, 1308. Article
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scGRNom: A Computational Pipeline of Integrative Multi-Omics Analyses for Predicting Cell-Type Disease Genes and Regulatory Networks
Genome Medicine, 13(1), 95. Article
Under review
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An “i-Mobility” Framework for Studying Social Mobility: Individualized Inference via Generative Analysis of Discrete Data
Under review
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Leveraging Generative AI Models for Textual Analysis in Healthcare Human Resources Operations
Major revision
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(Mis)Understanding Benign Overfitting in Equity Return Prediction
Under review
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I Will Pay You Back in the Future: Employees’ On-Job Perceptions of Organizations and Their Intention of Making Post-Turnover Employment Referrals
Under review
In progress
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Finite-Sample Variable Prescreening Methods for Qualitative Comparative Analysis
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The Configuration–Regression Nexus: A Systematic Review of Methodological Friction and Integration
Industry-partnered research
Applied analytics projects with Ryerson Inc., HSD Metrics, Drees Homes, and ABC Fitness.
Teaching
Católica Lisbon
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Causality and Randomized Experiments
Master's, 2027
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Business Research Methods
Master's, 2026
University of Cincinnati
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Probability Models
Master's, 2025 — evaluation 5.0 / 5.0
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Statistical Computing
Master's, 2025 — evaluation 4.6 / 5.0
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Descriptive Analytics and Data Visualization
Undergraduate, 2024 and 2022 — evaluations 4.7 and 4.4 / 5.0
Mentoring
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Discussant, MS dissertation defenses
University of Cincinnati, multiple cohorts
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Second reader, MSBA capstone projects
University of Cincinnati, multiple cohorts
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Mentor, UC Center for Business Analytics
Supervised two undergraduate students in Business Analytics and two master's students in Computer Science on industry projects with Drees Homes and ABC Fitness
Contact
Students and prospective collaborators are welcome to write to me at jhuang@ucp.pt, or to reach out on LinkedIn.
Católica Lisbon School of Business and Economics
Caminho de Palma de Cima, 1649-023 Lisboa, Portugal