Houping Xiao is a tenure-track assistant professor in the J. Mack Robinson College of Business at Georgia State University. He is a primary faculty with Institute for Insight. He got his Ph.D. in Computer Science and Engineering from the State University of New York at Buffalo. He also holds a Bachelor of science degree in Statistics from Beijing Normal University.
His research interests lie primarily in data mining and machine learning, especially for large-scale heterogeneous data. He is generally interested in deep learning, text mining, and optimization and their applications in business and education. His work has been applied in Fintech and computerized adaptive testing (CAT).
Contact
- E-mail: hxiao at gsu dot edu
- Phone: (404) 413-7704
- Office: 55 Park Place, Room 1640
- Address: Room 1640, 55 Park Place, Atlanta GA 30303
News( More)
- September 2024: EMNLP 2024 Main FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models!
- September 2024: ACM BCB 2024 (oral presentation) Asymmetric Mutual Learning for Decentralized Federated Medical Imaging!
- September 2024: ACRM 2024 Drivers of Stroke Independence During Inpatient Rehabilitation Care: Causal Forest Modeling! Poster presentation accepted by ACRM.
- September 2024: ACRM 2024 Spinal Cord Injury Inpatient Recovery: Sequence Modeling with Emphasis on Physical and Occupational Therapy! Poster presentation accepted by ACRM, the world's largest interdisciplinary rehabilitation research event.
- July 2024: Honored to receive the Georgia State-Augusta University Seed Grants!
- June 2024: Decision Support Systems (DSS), Accepted Predicting digital product performance with team composition features derived from a graph network.
- March 2024: BMSP 2024, Forthcoming A Two-Step Item Bank Calibration Strategy based on 1-bit Matrix Completion for Small-Scale Computerized Adaptive Testing.
- December 2023: SAIM SDM 2024 MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation on Healthcare.
- October 2023: Journal of Financial Economics (JFE), Forthcoming Charting By Machines
- February 2023: MSDA Program ranks 12th nationally, 5th among publics from 2023 Best Master’s of Business Analytics Programs, TFE Times
- Janurary 2023: SAIM SDM 2023 Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT!
- December 2022: IEEE BIBM 2022 MedAttacker: Exploring black-box adversarial attacks on risk prediction models in healthcare!
- September 2022: INFORMS Workshop on Data Mining & Decision Analytics Resolving Conflicts in Crowds: An Application In Earnings Forecasts!
- August 2022: MSDA Program ranks #18 from FORTUNE's Best Master's in Data Science Programs in 2022
- July 2022: INFORMS Annual Meeting Presentation Resolving Conflicts in Crowds: An Application In Earnings Forecasts!
- May 2022: Honored to receive the Pre-Tenured Scholarly Support Internal Grant!
- May 2022: IEEE TKDE 2022: A Joint Maximum Likelihood Estimation Framework for Truth Discovery: A Unified Perspective!
- February 2022: ACM TKDD 2022: Toward Quality of Information Aware Distributed Machine Learning!
Selected Publications (More)
"Predicting digital product performance with team composition features derived from a graph network", with Aaron Baird and Yusen Xia, June. 2024.
Decision Support Systems (DSS), Forthcoming .
Decision Support Systems (DSS), Forthcoming .
Digital Product Performance
Team Composition
Graph Network Analysis
Machine Learning
Interpretability
Interpretable Machine Learning
"Charting By Machines", with Scott Murray and Yusen Xia, March. 2024.
Journal of Financial Economics (JFE) .
Journal of Financial Economics (JFE) .
"A Two-Step Item Bank Calibration Strategy based on 1-bit Matrix Completion for Small-Scale Computerized Adaptive Testing", with Yawei Shen and Shiyu Wang. 2024.
British Journal of Mathematical and Statistical Psychology.
British Journal of Mathematical and Statistical Psychology.
Educational Psychology
Machine Learning
Matrix Completion
Small Big Analysis
Computerized Adaptive Testing
"A Joint Maximum Likelihood Estimation Framework for Truth Discovery: A Unified Perspective", with Shiyu Wang, 2022.
IEEE Transactions on Knowledge and Data Engineering.
IEEE Transactions on Knowledge and Data Engineering.
Truth Discovery
Crowdsourcing
Joint Maximum Likelihood Estimation
Profile Likelihood Estimation
Asymptotic Consistency
"Toward Quality of Information Aware Distributed Machine Learning", with Shiyu Wang, 2022.
ACM Transactions on Knowledge Discovery from Data
ACM Transactions on Knowledge Discovery from Data
Truth Discovery
Distributed Learning
Machine Learning
Quality of Information
Artificial Intelligence
"Adaptive Weight Estimation of Latent Ability: Application to Computerized Adaptive Testing With Response Revision", with Shiyu Wang and Allan Cohen, 2021.
Journal of Educational and Behavioral Statistics
Journal of Educational and Behavioral Statistics
Educational Psychology
Machine Learning
Adaptive Weight Estimation
Robust Estimation
Computerized Adaptive Testing
Response Revision
"Towards confidence interval estimation in truth discovery", with Jing Gao, Qi Li, Fenglong Ma, Lu Su, Yunlong Feng and Aidong Zhang. 2018.
IEEE Transactions on Knowledge and Data Engineering.
IEEE Transactions on Knowledge and Data Engineering.
Truth Discovery
Data Mining
Confidence Interval Estimation
Bootstrapping
Working Papers
"Can Machines Understand Human Skills? Insights from Analyst Selection", with Sean Cao, Xuxi Guo and Baozhong Yang, 2024. Revision and Resubmit
Semi-finalist of the FMA 2021 Best Paper in FinTech
Semi-finalist of the FMA 2021 Best Paper in FinTech
Slides
Deep Learning
CNN
Big Data
Artificial Intelligence
Analyst Forecast
Analyst Skill
Crowd Wisdom
"Intellectual Capital and Digital Platforms: An Appraisal-Based Perspective of a Large Language Model vs. an Online Community", with Aaron Baird and Yusen Xia, 2024. Ready to Submit.
"Whitebox inside blackbox: Using interpretable language models to analyze financial narratives", with Sean Cao, Angie Wang and Yongtae Kim, 2024. Under Review.
Slides
Machine Learning
Textual Analysis
Natural Language Processing
Artificial Intelligence
Sentiment Analysis
Conference Calls
"Resolving Conflicts in Crowds: A Earnings Forecasts Application", with Shiyu Wang, 2024. Revision and Resubmit.
"On-the-fly: An Efficient Online Tucker Decomposition for Tensor Streams", with Kai Zhao and Arun Rai, 2024. INFORMS Journal on Computing (JOC), Revision and Resubmit.