About Me

Welcome to my homepage! My name is Bojian Hou (also Bo-Jian Hou), a postdoctoral researcher of Department of Biostatistics, Epidemiology and Informatics at the University of Pennsylvania advised by Prof. Li Shen.

I received my B.Sc. and Ph.D. degree in the Department of Computer Science at Nanjing University in 2014 and 2020 separately. I was a member of LAMDA Group led by Prof. Zhi-Hua Zhou during my doctoral study. My Ph.D. supervisor is Prof. Zhi-Hua Zhou.

My research interests mainly focus on trustworthy AI, optimization for AI and AI for science. Specifically, they include:

  • Fairness Learning: developing fair and unbiased machine learning algorithms.
  • Interpretability: studying the interpretability of the black-box machine learning models.
  • Feature Evolvable Learning: studying learning scenarios where data features evolve.
  • Semi-Supervised Learning: learning models from both labeled and unlabeled data.
  • Online Learning: learning models continuously from online streaming data.
  • Natural Language Processing: developing and applying large language models.
  • Biomedical Data Mining: developing machine learning methods to analyze biomedical data (especially for Alzheimer’s disease and related dementia (ADRD)).

I am seeking faculty positions for the 2024-2025 academic year, with a focus on computer science, data science, biomedical informatics, and related fields. I welcome inquiries from interested institutions.

Recent Highlights

  • 11-27-2024: Our paper “Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models” with Joseph Lee, Shu Yang, Jae Young Baik, Xiaoxi Liu, Zhen Tan, Dawei Li, Zixuan Wen, Duy Duong-Tran, Tianlong Chen, and Li Shen was accepted by AMIA 2025 Informatics Summit.
  • 11-27-2024: Our paper “Leveraging Social Determinants of Health in Alzheimer’s Research Using LLM-Augmented Literature Mining and Knowledge Graphs” with Tianqi Shang, Shu Yang, Weiqing He, Tianhua Zhai, Dawei Li, Tianlong Chen, Jason H. Moore, Marylyn D. Ritchie, and Li Shen was accepted by AMIA 2025 Informatics Summit.
  • 11-27-2024: Our paper “Understanding the Clinical Modalities Important in NeuroDegenerative Disorders, Alzheimer’s Disease, and Risk of Patient Injury Using Machine Learning and Survival Analysis” with Kazi Noshin, Mary Regina Boland, Weiqing He, Victoria Lu, Carol Manning, Li Shen, and Aidong Zhang was accepted by AMIA 2025 Informatics Summit.
  • 10-26-2024: Our paper “SEFD: Semantic-Enhanced Framework for Detecting LLM-Generated Text” with Weiqing He, Tianqi Shang, Davoud Ataee Tarzanagh, Qi Long, and Li Shen was accepted by 2024 IEEE International Conference on Big Data (IEEE BigData 2024).
  • 10-13-2024: Our paper “Manifoldron: Direct Space Partition via Manifold Discovery” with Dayang Wang, Feng-Lei Fan, Hao Zhang, Rongjie Lai, Hengyong Yu and Fei Wang was accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
  • 09-25-2024: Our paper “Fairness-Aware Estimation of Graphical Models” with Zhuoping Zhou, Davoud Ataee Tarzanagh, Qi Long, Li Shen was accepted by NeurIPS 2024.
  • 09-21-2024: Our paper “MG-TCCA: Tensor Canonical Correlation Analysis across Multiple Groups” with Zhuoping Zhou, Boning Tong, Davoud Ataee Tarzanagh, Andrew J. Saykin, Qi Long, Li Shen was accepted by IEEE/ACM Transactions on Computational Biology and Bioinformatics.
  • 09-20-2024: Our paper “DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer’s Disease Questions with Scientific Literature” with Dawei Li, Shu Yang, Zhen Tan, Jae Young Baik, Sukwon Yun, Joseph Lee, Aaron Chacko, Duy Duong-Tran, Ying Ding, huan liu, Li Shen, Tianlong Chen was accepted by EMNLP 2024.
  • 09-10-2024: Our paper “Uncovering Important Diagnostic Features for Alzheimer’s, Parkinson’s and Other Dementias Using Interpretable Association Mining Methods” with Kazi Noshin, Mary Regina Boland, Victoria Lu, Carol Manning, Li Shen and Aidong Zhang was accepted by Pacific Symposium on Biocomputing (PSB).
  • 06-29-2024: Our paper “Analyzing Dementia Caregivers’ Experiences on Twitter: A Term-Weighted Topic Modeling Approach” with Yanbo Feng, Ari Klein, Karen O’Connor, Jiong Chen, Andrés Mondragón, Shu Yang, Graciela Gonzalez-Hernandez, Li Shen was accepted by AMIA 2024 Annual Symposium.
  • 06-29-2024: Our paper “Ensuring Fairness in Detecting Mild Cognitive Impairment with MRI” with Boning Tong, Travyse Edwards, Shu Yang, Davoud Ataee Tarzanagh, Ryan J. Urbanowicz, Jason H. Moore, Marylyn D. Ritchie, Christos Davatzikos, Li Shen was accepted by AMIA 2024 Annual Symposium. (This paper won the Distinguished Paper Award!)
  • 06-29-2024: Our paper “MentalGPT: Harnessing AD for compassionate mental health support” with Jia Xu, Tianyi Wei, Patryk Orzechowski, Shu Yang, George Demiris, Li Shen was accepted by AMIA 2024 Annual Symposium.
  • 06-03-2024: Our paper “Interpretable Deep Clustering Survival Machines for Alzheimer’s Disease Subtype Discovery” with Zixuan Wen, Jingxuan Bao, Richard Zhang, Boning Tong, Shu Yang, Junhao Wen, Yuhan Cui, Jason H Moore, Andrew J. Saykin, Heng Huang, Paul M. Thompson, Marylyn D. Ritchie, Christos Davatzikos, Li Shen was accepted by Medical Image Analysis.
  • 04-24-2024: Our paper “Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection” with Jing-Xiao Liao, Hang-Cheng Dong, Hao Zhang, Jinwei Sun, Shiping Zhang, Feng-Lei Fan was accepted by IEEE Transactions on Artificial Intelligence (TAI).
  • 01-19-2024: Our paper “Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods” with Davoud Ataee Tarzanagh, Parvin Nazari, Li Shen and Laura Balzano was accepted by AISTATS’24.
  • 12-21-2023: Our paper “PFERM: A Fair Empirical Risk Minimization Approach with Prior Knowledge” with Andrés Mondragón, Davoud Ataee Tarzanagh, Zhuoping Zhou, Andrew J Saykin, Jason H Moore, Marylyn D Ritchie, Qi Long, and Li Shen was accepted by AMIA 2024 Informatics Summit.
  • 12-21-2023: Our paper “Interpretability Study for Long Interview Transcripts from Behavior Intervention Sessions for Family Caregivers of Dementia Patients” with Weiqing He, Bojian Hou, George Demiris, and Li Shen was accepted by AMIA 2024 Informatics Summit.
  • 12-21-2023: Our paper “Cluster Analysis of Cortical Amyloid Burden for Identifying Imaging-driven Subtypes in Mild Cognitive Impairment” with Ruiming Wu, Bing He, Bojian Hou, Andrew J Saykin, Jingwen Yan, and Li Shen was accepted by AMIA 2024 Informatics Summit.
  • 10-10-2023: Our paper “Online Learning from Evolving Feature Spaces with Deep Variational Models” with Heng Lian, Di Wu, Jian Wu, and Yi He was accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • 09-21-2023: Our paper “Fair Canonical Correlation Analysis” with Zhuoping Zhou, Davoud Ataee Tarzanagh, Boning Tong, Jia Xu, Yanbo Feng, Qi Long and Li Shen was accepted by NeurIPS’23.
  • 07-24-2023: Our paper “Multi-Group Tensor Canonical Correlation Analysis” with Zhuoping Zhou, Boning Tong, Davoud Ataee Tarzanagh, Andrew J. Saykin, Qi Long and Li Shen was accepted by ACM BCB’23. (This paper won the Best Paper Award!)
  • 05-08-2023: Our paper “Fairness-Aware Class Imbalanced Learning on Multiple Subgroups” with Davoud Ataee Tarzanagh, Boning Tong, Qi Long and Li Shen was accepted by UAI’23.
  • 04-18-2023: Our paper “Enhancing thoracic disease detection using chest X-rays from PubMed Central Open Access” with Mingquan Lin, Swati Mishra, Tianyuan Yao, Yuankai Huo, Qian Yang, Fei Wang, George Shih, and Yifan Peng was accepted by Computers in Biology and Medicine.
  • 01-22-2023: Our paper “Deep Clustering Survival Machines with Interpretable Expert Distributions” with Hongming Li, Zhicheng Jiao, Zhen Zhou, Hao Zheng and Yong Fan was accepted by ISBI’23.
  • 12-16-2022: Our paper “Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served populations” with Mingquan Lin, Yunyu Xiao, Tingyi Wanyan, Mohit Manoj Sharma, Zhangyang Wang, Fei Wang, Sarah Van Tassel and Yifan Peng was accepted by AMIA 2023 Informatics Summit.
  • 06-29-2022: Our paper “Online Deep Learning from Doubly-Streaming Data” with Heng Lian, John Scovil Atwood, Jian Wu and Yi He was accepted by ACMMM’22.
  • 06-16-2022: Our paper “Automated diagnosing primary open-angle glaucoma from fundus image by simulating human’s grading with deep learning.” with Mingquan Lin, Lei Liu, Mae Gordon, Michael Kass, Fei Wang, Sarah H. Van Tassel and Yifan Peng was accepted by Scientific Report.
  • 11-22-2021: Winning the Excellent Doctoral Dissertation Award of Jiangsu Province.
  • 09-13-2021: Winning the Excellent Doctoral Dissertation Award of Nanjing University.
  • 08-31-2021: Our paper “Online Learning in Variable Feature Spaces with Mixed Data” with Yi He, Jiaxian Dong, Yu Wang, and Fei Wang was accepted by ICDM’21.
  • 04-01-2021: Our paper “Prediction with Unpredictable Feature Evolution” with Prof. Lijun Zhang and Prof. Zhi-Hua Zhou was accepted by IEEE Transactions on Neural Networks and Learning Systems.
  • 12-24-2020: Winning the JSAI Excellent Doctoral Dissertation Award.
  • 12-02-2020: Our paper “Storage Fit Learning with Feature Evolvable Streams” with Yu-Hu Yan, Peng Zhao and Zhi-Hua Zhou was accepted by AAAI’21.
  • 06-18-2020: Winning the CS Excellent Doctoral Dissertation Award of Nanjing University.
  • 05-27-2020: I have successfully defended my PhD dissertation and became a Ph.D.
  • 04-21-2020: Winning the Outstanding Graduate Student Award of Nanjing University.