Hau-Hung Yang

• Ph.D. in PsychologySep. 2022 – Jul. 2026

  National Taiwan University, Taipei, Taiwan (R.O.C.)

  • GPA: 4.19 / 4.3
  • Advisor: Prof. Yung-Fong Hsu
• M.S. in PsychologySep. 2020 – Jun. 2022

  National Taiwan University, Taipei, Taiwan (R.O.C.)

  • GPA: 4.13 / 4.3
• B.S. in PsychologySep. 2016 – Jun. 2020

  National Taiwan University, Taipei, Taiwan (R.O.C.)

  • GPA: 4.12 / 4.3
  • Ranked 3rd in the sixth semester

Precision and Robustness in Adaptive Testing: An Item Response Theory Analysis within an Online Convex Optimization Framework

Advisor: Prof. Yung-Fong Hsu · Completed: July 2026

Computerized adaptive testing (CAT) assigns items adaptively to estimate ability with as few items as possible. Despite a rich asymptotic literature, a framework for understanding finite-sample behavior has been missing. This dissertation brings the Online Convex Optimization (OCO) framework to CAT, organized around two complementary themes.

Precision

Shows that the classical information-maximization method is a no-regret algorithm under the OCO framework, and constructs anytime-valid confidence intervals via martingale concentration inequalities and confidence sequences.

Robustness

Designs stability-oriented item-selection algorithms — adapting Upper Confidence Bound (UCB) methods from the multi-armed bandit literature — that account for early-stage estimation error, premature commitment bias, and item-parameter uncertainty during online calibration.

• Professor Chao-ming Cheng Memorial Scholarship2026

  Department of Psychology, National Taiwan University

  The top prize for graduate psychology students for outstanding research in the academic year 2025–2026.

• Dean's Award2026

  College of Science, National Taiwan University

  The top graduating-class distinction for outstanding research achievement in the academic year 2025–2026.

• Postdoctoral Fellowfrom August 2026

  Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (R.O.C.)

• Full-time Research Assistant (R&D Substitute Military Service)July 2023 – February 2025

  Department of Economics, National Taiwan University

• On the Estimation of Standard Errors for the Ability Estimate in Item Response ModelsAug. 2024 – Present

  PI: Prof. Yung-Fong Hsu

  Concerns the estimation of standard errors for the ability estimate in IRT models, advancing estimation methods for computerized adaptive testing. My work covers algorithm development, simulation experiments, literature review, and manuscript preparation.

• Family, Health, and the MarketJul. 2022 – Present

  PI: Prof. Kuan-Ming Chen

  Investigates interactions among individuals, families, and the market under health shocks and long-term care demands. I analyze government administrative data to study wage inequality in Taiwan with the Abowd–Kramarz–Margolis (AKM) framework, and intra-household decision-making and tax-filing strategies using comprehensive income-tax records, complemented by surveys and field experiments.

• Evaluation of an Education Program Using Item Response TheoryJun. 2022 – Present

  PI: Prof. Yu-Chang Chen

  Evaluates the treatment effect of PaGamO, an online learning platform, using a 2-PL IRT model. I review the IRT literature, conduct algorithmic research, and implement the algorithms; we are developing a Bayesian state-space framework to estimate user ability and account for non-linear improvement over time.

• Issue-Oriented Big Data Analyses on Social Inclusion and Smart GovernanceJul. 2023 – Jun. 2025

  PI: Prof. Kuan-Ming Chen

  Examines the substitutability/complementarity between infants and pets, using fertility decisions as a behavioral lens. The study links administrative data from Taiwan's Ministry of Finance (tax records) and Ministry of Agriculture (pet registration data).

• Neural Correlates of Emotion as an Arbitrator to Reconcile the Conflicts within Dual Processing in the Context of Decision Making Under RiskMar. 2021 – Jan. 2023

  PI: Prof. Yung-Fong Hsu

  Behavioral and fMRI experiments probing the role of emotion when people face dual-process induced cognitive conflict under risk. I analyzed fMRI data and contributed to developing an estimation method for utility-function parameters.

• Analysis of Cognitive Structures Underlying Financial BehaviorJun. 2020 – Nov. 2021

  PI: Prof. Tsung-Ren Huang

  Sought common factors explaining financial behavioral biases. I reviewed the bias-related literature and analyzed behavioral data using exploratory factor analysis.

• From Mind Reading to Mind Sharing: Neural Correlates of Cognitive and Affective Theory of Mind and Their Applications to Salesforce EnhancementSep. 2018 – Jun. 2020

  PI: Prof. Heng-Chiang Huang

  Reviewed and reported literature on synchronization, structural equation modeling, and theory of mind, and mentored new team members in preprocessing and statistical analysis of behavioral and neuroimaging data.

• Coalition without Trust: Intra-Brain Connectivity and Inter-Brain Synchronization of Herd Behaviors in an Economic Bubble GameSep. 2017 – Jun. 2020

  PI: Prof. Yu-Ping Chen

  Used fMRI hyperscanning to explore theory-of-mind processes when participants competed in a bubble stock-market game. I reviewed literature spanning the diffusion model, reinforcement learning, prospect theory, and behavioral economics, and analyzed the fMRI and behavioral data.

Journal Articles

1. Chen, K.-M., Chen, Y.-C., Hung, C.-C., & Yang, H.-H. (2026). Institution or major? Understanding student preferences in college admissions. Economic Inquiry (conditionally accepted).
2. Chen, K.-M., Tsai, L.-T., & Yang, H.-H. (2026). Labor market sorting in Taiwan. Taiwan Economic Review (in press).
3. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2025). Identifiability of polychoric models with latent elliptical distributions. Psychometrika, 90(2), 757–778. [doi]
4. Yang, H.-H., & Hsu, Y.-F. (2024). The generalized Robbins–Monro process and its application to psychophysical experiments for threshold estimation. Journal of Mathematical Psychology, 120–121, 102855. [doi]
5. Yang, H.-H., & Hsu, Y.-F. (2024). A note on the application of stochastic approximation to computerized adaptive testing. Behaviormetrika, 51(1), 259–276. [doi]

Submitted Papers

1. Yang, H.-H., Wei, C.-M., & Chen, Y.-C. (2025). On the consistency of Bayesian adaptive testing under the Rasch model. Under revision. [link]
2. Yang, H.-H., Cheng, C., & Hsu, Y.-F. (2025). Parametric bootstrapping of standard errors for ability parameters in dichotomous IRT models: Asymptotic and small-sample analyses. PsyArXiv preprint. [doi]
3. Yang, H.-H., Ho, T.-Y., & Hsu, Y.-F. (2025). Enhancing Random Forest performance on imbalanced data using the General Condorcet Model. Under revision.
4. Chang, W.-C., Yang, H.-H., Lin, T.-Y., Tong, J. C. H., & Hsu, Y.-F. (2025). Comparison of bisection-based and adaptive psychophysical methods for eliciting indifference points in loss aversion research. Submitted.

Manuscripts

1. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2024). On the existence and uniqueness of MLE of the latent trait under log-concave distributional assumptions in IRT. PsyArXiv preprint. [doi]
2. Yang, H.-H., & Hsu, Y.-F. (2024). An alternative modeling proposal to conjoint survey experiments: Re-evaluating data from Duch et al. (2021). PsyArXiv preprint. [doi]
3. Tong, J. C. H., Yang, H.-H., & Chen, Y.-P. (In preparation). Decision-making process of retail investors during a financial bubble: An fMRI study.

2025

1. Yang, H.-H., Wei, C.-M., & Chen, Y.-C. (2025). On the consistency of Bayesian adaptive testing under the Rasch model. Oral presentation, 8th International Conference on Econometrics and Statistics (EcoSta 2025), Tokyo, Japan.
2. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2025). When the test information curve misleads: Exact bias, SE, and RMSE curves in Item Response Theory. Oral presentation, 53rd Annual Meeting of the Behaviormetric Society, Kanagawa, Japan.
3. Cheng, C., Yang, H.-H., Hsu, Y.-F., & Lay, K.-L. (2025). A methodology for addressing the biases caused by ipsative placement of Q-sort items. Poster, SRCD 2025 Biennial Meeting, Minneapolis, MN, USA.
4. Cheng, C., Yang, H.-H., Hsu, Y.-F., & Lay, K.-L. (2025). Paradigmatic decisions for measuring choices and preferences: Likert scales, comparative judgments, or combined models?. Poster, 89th Annual Convention of the Japanese Psychological Association, Sendai, Japan.

2024

1. Cheng, C., Yang, H.-H., Hsu, Y.-F., & Lay, K.-L. (2024). Two are better than one: Incorporating Likert scale and comparative judgment data in joint Thurstonian IRT model. Oral presentation, 63rd Annual Meeting of the Taiwanese Psychological Association, Taipei, Taiwan.
2. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2024). On the existence and uniqueness of polychoric correlations. Poster, 88th Annual Convention of the Japanese Psychological Association, Kumamoto, Japan.
3. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2024). Existence and uniqueness of MLE of the ability in IRT. Poster, IMPS 2024, Prague, Czech Republic.
4. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2024). Predetermined R squared: An index of later development determined by the past. Poster, 27th Biennial Meeting of the ISSBD, Lisbon, Portugal.
5. Chen, K.-M., Chen, Y.-C., Hung, C.-C., & Yang, H.-H. (2024). Estimating preferences for college programs using Taiwanese college admission data. Oral presentation, Annual Conference of the Population Association of Taiwan, Taipei, Taiwan.
6. Chen, K.-M., Chen, Y.-C., Hung, C.-C., & Yang, H.-H. (2024). Estimating preferences for college programs using Taiwanese college admission data. Oral presentation, 18th International Symposium on Econometric Theory and Applications (SETA 2024), Taipei, Taiwan.

2023

1. Chen, K.-M., Chen, Y.-C., Hung, C.-C., & Yang, H.-H. (2023). College and major preference estimation using Taiwanese college admission data. Oral presentation, Asian and Australasian Society of Labour Economics 2023 Conference, Taipei, Taiwan.
2. Yang, H.-H., & Hsu, Y.-F. (2023). On the consistency and relative efficiency of a generalized Robbins-Monro process for threshold estimation. Poster, MathPsych 2023, Amsterdam, Netherlands.
3. Yang, H.-H., Cheng, C., & Hsu, Y.-F. (2023). Evaluating SEs of parameter estimates in the 2PL model with exact parametric bootstrap. Poster, IMPS 2023, College Park, MD, USA.
4. Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2023). Identifiability of polychoric models with latent elliptical distributions. Oral presentation, IMPS 2023, College Park, MD, USA.

2021

1. Yang, H.-H., & Hsu, Y.-F. (2021). Modification of the estimation method of threshold: A new adaptive method taking response time and response confidence into account. Oral presentation, 60th Annual Meeting of the Taiwanese Psychological Association, Taipei, Taiwan.

• National Taiwan University Doctoral ScholarshipAugust 2025 – July 2026

  (NSTC Selection/Allocation)

• College Student Research ScholarshipJuly 2019 – February 2020

  Ministry of Science and Technology, Taiwan (MOST 108-2813-C-002-115-H)

• PSY7001 Experimental Design — Fall 2024
• PSY5033 Applied Linear Regression — Spring 2023
• PSY7001 Experimental Design — Fall 2022
• PSY3010 Intermediate Statistics — Fall 2021
• PSY1004 Statistics in Psychology and Education II — Spring 2021
• PSY1003 Statistics in Psychology and Education I — Fall 2020
• PSY1004 Statistics in Psychology and Education II — Spring 2020
• PSY1003 Statistics in Psychology and Education I — Fall 2019

Analytical

• Statistical modeling — PCA, factor analysis, generalized linear models
• Psychometrics — structural equation modeling, item response theory
• Mathematical psychology — adaptive methods (stochastic approximation), drift diffusion models
• Neuroimaging analysis (fMRI)

Programming

• R
• Python
• MATLAB
• SAS
• LaTeX
• Stata