Chao Huang, PhD
Assistant Professor
Department of Statistics - College of Arts and Sciences - Florida State University
Assistant Professor (courtesy)
Department of Biomedical Sciences - College of Medicine - Florida State University
Address: 407 Statistics Building, 117 N. Woodward Ave., Tallahassee, FL 32306
Email: chuang7 AT fsu DOT edu
[CV] [GitHub] [Google Scholar] [OCRID] [ResearchGate]
Education
PhD in Biostatistics University of North Carolina at Chapel Hill 2019
BS in Applied Mathematics Southeast University (China) 2008
Research Interest
Chao's research interests mainly focus on statistical learning of large-scale biomedical data including clinical, imaging, and genomic data. The goal of his research is to develop novel statistical methods and machine learning (deep learning) algorithms for analyzing data with complex structures, including high dimensional data, functional data, manifold data and data with heterogeneity. These statistical methods and computational tools can help us understand the disease progression and improve clinical trials for the treatment and early prevention. Some projects that he is currently working on are: big data integration, manifold data analysis, functional data analysis, imaging heterogeneity, imaging genetics, and deep learning. Chao is also interested in some public datasets including Alzheimer’s Disease Neuroimaging Initiative [ADNI], The Osteoarthritis Initiative [OAI], UK Biobank [UKB], Adolescent Brain Cognitive Development [ABCD], and Human Connectome Project [HCP].
News
2024-04: Chao gave an invited talk "Exploring Aging through Statistical Shape Analysis in Imaging Studies" at the Department of Epidemiology and Biostatistics, University of Arizona.
2024-03: Chao's PhD student Shengxian Naomi Ding successfully defended her dissertation research entitled "Advanced Functional Regression Models in Biomedical Data Analysis".
2024-03: Chao gave an invited talk "Exploring Aging through Statistical Shape Analysis in Imaging Studies" at the Biostatistics & Bioinformatics Division, Penn State University.
2024-03: Chao’s co-author rejoinder paper "Rejoinder on: Shape-based functional data analysis" was published in Test.
2024-02: Chao gave an invited talk "Exploring Aging through Statistical Shape Analysis in Imaging Studies" at the Department of Biostatistics, Yale University.
2024-01: Chao's PhD student Miyeon Yeon received the Honorable Mention in the 2024 ASA Mental Health Statistics Section Student Paper Award competition.
2024-01: Chao received the FSU Summer Research Support (SRS) Award "Identification and Evaluation of Subgroups in Alzheimer’s Disease and Related Dementias Using Longitudinal Multimodal Image Data from Multiple Studies": Role: PI.
2024-01: Chao’s equal-contributed first-author paper "Merging or Ensembling: Integrative Analysis in Multiple Neuroimaging Studies" was published in Biometrics.
2024-01: Chao offered a new graduate course STA 5327 Statistical Inference.
2023-11: Chao’s editorial paper "Editorial: Modern statistical learning strategies in imaging genetics, volume II" was published in Frontiers in Neuroscience.
2023-10: Chao’s corresponding-author paper "Distribution-on-scalar single-index quantile regression model for handling tumor heterogeneity" was accepted by Technometrics.
2023-09: Chao’s corresponding-author paper "Confounder adjustment in shape-on-scalar regression model: corpus callosum shape alterations in Alzheimer's disease" was published in Stats.
2023-08: Chao’s co-author discussion paper "Shape-based functional data analysis" was published in Test.
2023-07: Chao’s corresponding-author paper "Quantifying the growth of glioblastoma tumors using multimodal MRI brain images" was published in Cancers.
2023-07: Chao gave an invited talk "When mediation analysis faces multi-level imaging heterogeneity" at the 2023 ICSA China Conference.
2023-06: Chao's PhD student Yuanyao Tan gave an invited talk "When Shape Regression Analysis Faces Multi-level Imaging Heterogeneity: Normal Brain Aging Monitoring based on 3D Brain Subcortical Structures" at the 2023 ICSA Applied Statistics Symposium.
2023-05: Chao's PhD student Kaizhou Lei gave an invited talk "When mediation analysis faces subgroup heterogeneity" at the 2023 Statistical Methods in Imaging Conference.
2023-03: Chao’s corresponding-author paper "Deep zero-inflated negative binomial model and its application in scRNA-seq data integration" was published in IEEE SoutheastCon 2023.
2023-01: Chao offered a new graduate course STA 6448 Advanced Probability and Inference II.
More News
2022-12: Chao gave an invited talk "Shape-on-Scalar Regression Models: Going Beyond Prealigned Non-Euclidean Responses" at the Department of Mathematics and Statistics, Binghamton University.
2022-11: Chao’s first-author paper "LMFE: Learning based Multi-scale Feature Engineering in Partial Discharge Detection" was published in IEEE Transactions on Neural Networks and Learning Systems.
2022-08: Chao received the FSU Accelerator Award "DeepCare: Artificial Intelligence & Quality of Life in Older Adults at Risk of Alzheimer’s Disease and Related Dementias": Role: Co-PI.
2022-03: Chao’s coauthored paper "Low-Rank Plus Sparse Decomposition of fMRI Data With Application to Alzheimer's Disease" was published in Frontiers in Neuroscience.
2022-01: Chao’s first-author paper "Functional Hybrid Factor Regression Model for Handling Heterogeneity in Imaging Studies" was accepted by Biometrika.
2022-01: Chao’s first-author paper "DADP: Dynamic abnormality detection and progression for longitudinal knee magnetic resonance images from the Osteoarthritis Initiative" was accepted in Medical Image Analysis (IF 8.545).
2021-12: Chao gave an invited talk "Mixture of Shape-on-Scalar Regression Models: Going Beyond Prealigned Non-Euclidean Responses" at the CMStatistics Conference 2021.
2021-12: Chao gave a one-day short course on ML/AI at US Food and Drug Administration (FDA).
2021-08: Chao offered a new graduate course STA 5934 - 0003 Statistical Data Science with Python.
2021-05: Chao gave an invited talk "Geodesic Factor Regression Model with Misaligned Pre-shape Responses in Statistical Shape Analysis" at the Statistical Methods in Imaging Conference 2021.
2021-05: Chao received the FSU Planning Grant (PG) Award "Statistical Harmonization Methods in Integrating Large-scale Imaging Studies": Role: PI.
2021-05: Chao gave an invited talk "Geodesic Factor Regression Model with Misaligned Pre-shape Responses in Statistical Shape Analysis" at the Statistical Methods in Imaging Conference 2021.
2021-05: Chao was invited as a Guest Associate Editor and launched a topic "Modern Statistical Learning Strategies in Imaging Genetics" in the journal Frontiers in Neuroscience (Brain Image Method Section).
2021-02: Chao gave an invited talk "Image-on-Scalar Single Index Model with Increasing Link for Handling Heterogeneity in Imaging Studies" at the 2021 ENAR Spring Meeting.
2021-02: Chao’s first-authored paper "Geo-FARM: Geodesic Factor Regression Model for Misaligned Pre-shape Responses in Statistical Shape Analysis" was accepted by 2021 CVPR (oral presentation, acceptance rate < 17%).
2020-09: Chao’s coauthored paper "(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients" was published in NeuroImage.
2020-07: Chao received the FSU Collaborative Collision Seed Fund "Embedding-based Knowledge Graphs for Critical Biomedical Applications": Role: Co-PI.
2020-04: Chao was granted the courtesy assistant professor appointment with Department of Biomedical Sciences at FSU College of Medicine.
2020-03: Chao received the FSU First Year Assistant Professor Award "Shape Regression and Its Applications in Heterogeneous Medical Image Data": Role: PI.
2020-02: Chao was funded by a 3-year award from NSF: DMS-1953087 "CDS&E: Geometrical Regression Models Involving Complex Shape Variables": Role: Co-PI (50%).
Openings
Chao is looking for one or two highly motivated graduate students for Research Assistant positions. Please contact him through Email. You can also visit his office by appointment.