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Curriculum Vitae

Dr. Yijun Zhao

Associate Professor
Director of the MS in Data Science (MSDS) Program
Co-director of the Dual MS in Data Science and MA in Economic Program
Co-director of the Joint MS in Data Science and Quantitative Econometrics Program
Computer and Information Sciences Department
Fordham University

Publications (by year)

Authors marked in red are Fordham students/alumni, mostly from the MSDS program. You may also browse by application domain, research area, and type.

2025

  1. S. Do , A. Chu, Y. Zhao , Y. Li", Stock Market Forecasting with Pretrained Deep Learning Models," IEEE BigDataService, 2025
  2. Y. Li , Y. Liu , and Y. Zhao , " A-CLAPS: Automatic Correction of Language and Pronunciation Errors in Slide-based Presentations," IEEE COMPSAC, 2025
  3. D. Cordero , Y. Zhao , P. Diaz , G. Weiss, " Unveiling Bias: Analyzing Race and Gender Disparities in AI Gene," IEEE COMPSAC, 2025
  4. J. Warren , G. Weiss, F. Martinez, A. Guo, Y. Zhao , “Decoding Fatphobia: Examining Anti-Fat and Pro-Thin Bias in AI-Generated Images”, Findings of the Association for Computational Linguistics (NAACL), 2025

2024

  1. Y. Zhao , A. Borell , F. Martinez , H. Xue , and G. Weiss, "Admissions in the Age of AI: Detecting AI-generated Application Materials in Higher Education," Scientific Reports, 2024 [Online]
  2. K. Afane and Y. Zhao , "Selecting Classifiers and Resampling Techniques for Imbalanced Datasets: A New Perspective," 28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), 2024
  3. S. Yun , H. Xue , X. Zhang , J. Zhang, and Y. Zhao , "Enhancing Crime Investigation: Attention-Based GAN for Sketch-to-Portrait Conversion," IEEE COMPSAC, 2024
  4. F. Martinez , G. Weiss, M. Palma , H. Xue , A. Borelli , and Y. Zhao , "GPT vs. Llama2: Which Comes Closer to Human Writing?," International Conference on Educational Data Mining (EDM), 2024
  5. Y. Zhao , Z. Qi , S. Do , J. Grossi , J. Kang , and G. Weiss, "Addressing Disparity in GRE-optional Admissions by Predicting GRE Performance Using Application Materials," International Conference on Educational Data Mining (EDM), 2024

2023

  1. E. Thrall, F. Martinez Lopez , T. Egg , S. Lee, J. Schrier, and Y. Zhao , "Rediscovering the Particle-in-a-Box: Machine Learning Regression Analysis for Hypothesis Generation in Physical Chemistry Lab," Journal of Chemical Education, 2023 [Online]
  2. Y. Zhao , X. Chen , H. Xue , and G. Weiss "A Machine Learning Approach to Graduate Admissions and the Role of Letters of Recommendation," PLOS One, 2023 [Online]
  3. Y. Zhao , Z. Qi , J. Grossi , and G. Weiss "Gender and culture bias in letters of recommendation for computer science and data science masters programs," Scientific Reports, 2023 [Online]
  4. Y. Zhao , Y. Ding, H. Chekerid , Y. Wu , and Q. Wang " Ethnic Differences in Response to COVID-19: A Study of American-Asian and Non-Asian College Students," Behavior Sciences, 2023 [Online]
  5. Y. Zhao , T. Wang , D. Mansah , E. Parnoff , S. He , and G. Weiss, "A Quantitative Machine Learning Approach to Evaluating Letters of Recommendation," Hawaii International Conference on System Sciences (HICSS), 2023. &[Online]
  6. Y. Zhao , Z. Du , S. Xu , Y. Chen , J. Mu , and M. Ning, "Social Media, Market Sentiment and Meme Stocks," , IEEE COMPSAC, 2023 [Online]
  7. F. Martinez , and Y. Zhao , "Integrating Multiple Visual Attention Mechanisms in Deep Neural Networks," IEEE COMPSAC, 2023 [Online]

2022

  1. Y. Zhao , D. Smith , and A. Jorge, " Comparing Two Machine Learning Approaches in Predicting Lupus Hospitalization Using Longitudinal Data," Scientific Reports, 2022 [Online]
  2. Y. Zhao , Y. Ding, H. Chekerid , and Y. Wu , "Student Adaptation to College and Coping in Relation to Adjustment During COVID-19: A Machine Learning Approach," PLOS One, 2022 [Online]
  3. Y. Zhao , S. Xu , and J. Ossowski, "Deep Learning Meets Statistical Arbitrage: An Application of Long Short-Term Memory Networks to Algorithmic Trading," Journal of Fiancial Data Science, 2022. [Online]
  4. Y. Zhao , M. Qin , and A. Jorge, "A Calibrated Ensemble Algorithm to Address Data Heterogeneity in Machine Learning: An Application to Identify Severe SLE Flares in Lupus Patients," IEEE Access, 2022 [Online]
  5. S. Li , and Y. Zhao , "Addressing Motion Blurs in Brain MRI Scans Using Conditional Adversarial Networks and Simulated Curvilinear Motions," Journal of Imaging, 2022 [Online]
  6. Y. Zhao , Y. Ding, Y. Shen , S. Failing , and J. Hwang , "Different coping patterns among U.S. graduate and undergraduate students during COVID-19 pandemic: A machine learning approach," International Journal of Environmental Research and Public Health, 2022 [Online]
  7. Y. Zhao , Y. Ding, Y. Shen , and W. Liu , "Gender Difference in Psychological, Cognitive, and Behavioral Patterns Among University Students During COVID-19: A machine learning approach," Frontiers in Psychology, 2022 [Online]
  8. A. Jorge , D. Smith , Z .Wu , T. Chowdhury , K. Costenbader, Y. Zhang, H.Choi, C. Feldan, and Y. Zhao "Exploration of Machine Learning Methods to Predict Systemic Lupus Erythematosus Hospitalizations," Lupus, 2022 [Online]
  9. Y. Zhao and T. Chitnis, "Dirichlet Mixture of Gaussian Processes with Split-kernel: An Application to Predicting Disease Course in Multiple Sclerosis Patients," The International Joint Conference on Neural Networks (IJCNN), 2022 [PDF]
  10. Q. Xu , M. Sun , B. Fu , and Y. Zhao , "Deep Learning Based Parking Vacancy Detection for Smart Cities," Hawaii International Conference on System Sciences (HICSS), 2022 [Online]
  11. D. Leeds, C. Chen , Y. Zhao , F. Metla , J. Guest , and G. Weiss, "Generalize Sequential Pattern Mining of Undergraduate Courses," International Conference on Educational Data Mining (EDM), 2022 [PDF]
  12. Y. Wang , Y. Wang , C. Zhong , and Y. Zhao, "US County-level Risk Factors Associated with COVID-19 Exacerbation During Vaccination Era," IEEE COMPSAC, 2022 [Online]
  13. W. Liu , J. Zhang , and Y. Zhao, "A Comparison of Deep Learning and Traditional Machine Learning Approaches in Detecting Cognitive Impairment Using MRI Scans," IEEE COMPSAC, 2022 [Online]
  14. Y. Wang , Y. Wang , C. Zhong , and Y. Zhao, "Assessing Deep Learning Approaches in Detecting Masked Facial Expressions," IEEE COMPSAC, 2022 [Online]

2021

  1. M. He , X. Wang , and Y. Zhao , "A calibrated deep learning ensemble for abnormality detection in musculoskeletal radiographs," Scientific Reports, 2021 [Online]
  2. H. Pardoe, S. Martin, Y. Zhao , A. George, H. Yuan , J. Zhou , W. Liu , and O. Devinsky, "Estimation of in-scanner head pose changes during structural MRI using a convolutional neural network trained on eye tracker video," Journal of Magnetic Resonance Imaging, 2021 [Online]
  3. E. Thrall, S. Lee , J. Schrier, and Y. Zhao , "Machine Learning for Functional Group Identification in Vibrational Spectroscopy: A Pedagogical Lab for Undergraduate Chemistry Students," Journal of Chemical Education, 2021 [Online]
  4. S. Bai and Y. Zhao "Startup Investment Decision Support: Application of Venture Capital Scorecards Using Machine Learning Approaches," Systems, 2021 [Online]
  5. Y. Zhao , J. Ossowski, X. Wang , S. Li , O. Devinsky, S. Martin, and H. Pardoe, "Localized Motion Artifact Reduction on Brain MRI Using Deep Learning with Effective Data Augmentation Techniques," The International Joint Conference on Neural Networks (IJCNN), 2021 [Online]
  6. Y. Xiao and Y. Zhao , "Preserving Gender and Identity in Face Age Progression of Infants and Toddlers," International Joint Conference on Biometrics (IJCB), 2021 [Online]
  7. H. Yuan , W. Zheng , S. Yun , and Y. Zhao , "Parallel Deep Neural Networks for Musical Genre Classification: A Case Study," IEEE COMPSAC, 2021 [Online]
  8. Y. Shi , Z. Wu , S. Zhang , H. Xiao, and Y. Zhao , "Assessing Palliative Care Needs Using Machine Learning Approaches," IEEE COMPSAC, 2021 [Online]

2020

  1. Y. Zhao , T. Wang , R. Bove, B. Cree, R. Henry, H. Lokhande, M. Polgar-Turcsanyi, M. Anderson, R. Bakshi, H. Weiner, T. Chitnis, and SUMMIT Investigators. "Ensemble learning predicts multiple sclerosis disease course in the SUMMIT study," npj Digital Medicine, 2020 [Online]
  2. Y. Zhao , M. Berretta , T. Wang , and T. Chitnis, "A Temporal Model with Dynamic Imputation for Missing Target Values in Longitudinal Patient Data," IEEE International Conference on Healthcare Informatics (ICHI), 2020 [Online]
  3. Y. Zhao , B. Lackaye, J. Dy, and C. Brodley, "A Quantitative Machine Learning Approach to Master Students Admission for Professional Institutions," International Conference on Educational Data Mining (EDM), 2020 [PDF]
  4. Y. Zhao , Q. Xu , M. Chen , and G. Weiss "Predicting Student Performance in a Master’s Program in Data Science using Admissions Data," International Conference on Educational Data Mining (EDM), 2020 [PDF]
  5. Y. Zhao , H. Yuan , J. Zhou , S. Martin, H. Pardoe, "Deep Convolutional Neural Networks for Predicting Head Pose During Brain MRI Acquisition," Journal of Vision for VSS Annual Meeting, 2020 [Online]
  6. Y. Zhao , J. Ossowski, X. Wang , S. Li , S. Martin, H. Pardoe, "Deep Convolutional Autoencoder for Reducing Motion Artifactsin Structural Brain MRI Scans," Conference for Organization of Human Brain Mapping (OHBM), 2020
  7. A. Jorge, Z. Wu , T. Chowdhury , Y. Zhao , "Exploration of Machine Learning Methods in Predicting Systemic Lupus Erythematosus Hospitalizations," ACR Convergence, 2020 [Online]

2019

  1. Y. Zhao , W. Wu , Y. Jin , S. Gu , H. Wu , J. Wang , X. Jiang, and H. Xiao, "Predicting 30-Day Hospital Readmissions for Patients with Diabetes," International Conference on Health Informatics (HIMS), 2019 [PDF]
  2. Y. Zhao , T. Chitnis, and T. Doan , "Ensemble Learning for Predicting Multiple Sclerosis Disease Course," The 15th International Conference on Data Science, 2019, [PDF]
  3. Y. Zhao and S. Lebak , "Deep Convolutional Autoencoder for Recovering Defocused License Plates and Smudged Fingerprints," The 15th International Conference on Data Science, 2019 [PDF]

2017

  1. Y. Zhao , B. Healy, D. Rotstein, C. Guttmann, R. Bakshi, H. Weiner, C. Brodley, and T. Chitnis "Exploration of Machine Learning Techniques in Predicting Multiple Sclerosis Disease Course," PLOS ONE , 2017 [PDF]

2016

  1. Y. Zhao , B. Ahmed, T. Thesen, K. E. Blackmon, J. Dy, and C. Brodley "A Non-parametric Approach to Detect Epileptogeic Lesions using Restricted Boltzmann Machines," 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) , 2016 [PDF]

2015

  1. Y. Zhao , T. Chitnis, B. Healy, J. Dy, and C. Brodley "Domain Induced Dirichlet Mixture of Gaussian Processes: An Application to Predicting Disease Progression in Multiple Sclerosis Patients," The IEEE International Conference on Data Mining Series (ICDM) , 2015 [PDF]

2014

  1. Y. Zhao , C. Brodley, T. Chitnis, and B. Healy, "Addressing Human Subjectivity via Transfer Learning: An Application to Predicting Disease Outcome in Multiple Sclerosis Patients," 2014 SIAM International Conference on Data Mining , 2014 [PDF]
  2. B. Ahmed, T. Thesen, K. Blackmon, and Y. Zhao , O. Devinsky, R. Kuzniercky, C. Brodley, "HierarchicalConditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations," The 31st International Conference on Machine Learning (ICML) , 2014 [PDF]

2000

  1. M. Kong and Y. Zhao , "Computing k-independent sets for regular bipartite graphs," Congressus Numerantium Vol. 143(2000), pp. 65-80 [PDF]