Faculty

Institution

Unit

Venue

Xinhua Zhang

Associate Professor

University of Illinois Chicago

Affiliations

College of Engineering

Computer Science

Xinhua Zhang is currently serving as a College Of Engineering Associate Professor at University of Illinois Chicago.

Honors

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Experiences

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Education

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Xinhua Zhang

University of Illinois Chicago

Associate Professor

You can click a keyword to filter the displayed items

machine learning computer science applied mathematics data science machine learning research deep learning computational statistics mathematical optimization statistical methodology computational intelligence artificial intelligence oncology kernel methods convex analysis computer vision supervised learning neuroscience pattern recognition cancer care bayesian analysis deep q-learning cancer treatment unsupervised machine learning convex optimization locoregional therapy cancer research numerical algorithms patient-reported outcomes semi-supervised learning logistic regression stochastic optimization support vector machines oropharyngeal squamous carcinomas outcomes research knowledge discovery biomedical informatics prognosis computational learning theory adversarial machine learning cancer management deep reinforcement learning convex two-layer modeling multinomial logistic regression optimal treatment selection machine vision neuroinformatics risk analysis (business) density estimation association rules pattern mining accelerated training late symptoms empirical risk minimization semi-supervised learning algorithms conditional gradient medical internet research textual practice laboratory medicine medical image computing optimal investment security estimation theory online learning dirichlet form network robustness learning classifier system intelligent classification automatic classification failure prediction pattern discovery disease classification computability theory matrix-norm regularization sparse estimation consistent image analogies convex deep learning normalized kernels reinforcement learning action model learning automated machine learning

Notable Scholarly Works

Notable Federal Grants

Collaborators

Externally Validated Digital Decision Support Tool for Time-To-Osteoradionecrosis Risk-Stratification Using Right-Censored Multi-Institutional Observational Cohorts. Radiotherapy and Oncology (2025)

Laia Humbert-VidanSerageldin KamelAndrew WentzelZaphanlene KaffeyMoamen AbdelaalKyle B SpierNatalie A WestG Elisabeta MaraiGuadalupe CanahuateXinhua ZhangMelissa M ChenKareem A WahidJillian RigertSeyedmohammadhossein HosseinianAndrew J SchaeferKristy K BrockMark ChambersAdegbenga O OtunRuth Aponte-WessonVinod PatelAndrew HopeJack PhanAdam S GardenSteven J FrankWilliam H MorrisonMichael T SpiottoDavid RosenthalAnna LeeRenjie HeMohamed A NaserErin WatsonKatherine A HutchesonAbdallah S R MohamedVlad C SandulacheLisanne V van DijkAmy C MorenoTeresa Guerrero UrbanoClifton D FullerStephen Y Lai

digital healthpublic healthtime-to-osteoradionecrosis risk-stratificationcohort studies

Support Vector Machines. Cambridge University Press eBooks (2025)

Zhen “Leo” Liu

computer sciencecomputational intelligenceautomatic classificationpattern recognitionmachine learningknowledge discoverydavid hilbertdata sciencecomputational learning theorynumerical algorithmssupport vector machinesintelligent classificationartificial intelligencesupport vecdata miningapplied mathematicsmachine learning researchlearning classifier system

Collaborative Filtering for the Imputation of Patient Reported Outcomes. Lecture notes in computer science (2024)

Eric Ababio AnyimaduClifton David FullerXinhua ZhangG Elisabeta MaraiGuadalupe Canahuate

computer scienceoutcomes researchdata sciencepatient safetypublic healthcollaborative filteringpatient-centered outcomespatient-reported outcomes

Data Deposition for"Optimal Policy Determination in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: A Patient-Physician Digital Twin Dyad With Deep Q-Learning". Figshare (2024)

Elisa TardiniXinhua ZhangGuadalupe CanahuateAndrew WentzelAbdallah MohamedLisanne Van DijkClifton (Dave) FullerG. Elisabeta Marai

deep learninghealth policymedicinecancer treatmentdeep q-learningmachine learningoptimal policy determinationoncologyoropharyngeal squamous carcinomasradiation oncologymedicinal researchlocoregional therapydata deposition

Mandibular Dose-Volume Predicts Time-To-Osteoradionecrosis in an Actuarial Normal-Tissue Complication Probability (Ntcp) Model: External Validation of Right-Censored Clinico-Dosimetric and Competing Risk Application Across International Multi-Institutional Observational Cohorts and Online Graphical User Interface Clinical Support Tool Assessment. medRxiv (2024)

Laia Humbert-VidanSerageldin KamelAndrew WentzelZaphanlene KaffeyMoamen AbdelaalKyle B. SpierNatalie A. WestG. Elisabeta MaraiGuadalupe CanahuateXinhua ZhangMelissa M. ChenKareem A. WahidJillian RigertSeyedmohammadhossein HosseinianAndrew J. SchaeferKristy K. BrockMark ChambersAdegbenga O. OtunRuth Aponte-WessonVinod PatelAndrew HopeJack PhanAdam S. GardenSteven J. FrankWilliam H MorrisonMichael T SpiottoDavid RosenthalAnna LeeRenjie HeMohamed A. NaserErin WatsonKatherine A. HutchesonAbdallah S. R. MohamedVlad C. SandulacheLisanne V. van DijkAmy C. MorenoTeresa Guerrero UrbanoStephen Y. LaiClifton D. Fuller

critical caredosimetryrisk applicationactuarial scienceexternal validation

Offline Reward Perturbation Boosts Distributional Shift in Online Rl.. PubMed (2024)

Zishun YuSiteng KangXinhua Zhang

machine learningonline rloffline reward perturbationdistributional shift

Pro-Based Stratification Improves Model Prediction for Toxicity and Survival of Head and Neck Cancer Patients. IEEE Journal of Biomedical and Health Informatics (2024)

Eric A. AnyimaduYaohua WangCarla FloricelSerageldin KamelClifton David FullerXinhua ZhangG. Elisabeta MaraiGuadalupe M. Canahuate

survival analysispatient safetyneck cancer patientspro-based stratificationpatient-reported outcomescancer researchmodel predictionmedical image computingneck oncologymachine learning researchprognosishealth informaticsoncologypredictive toxicologyepidemiologybiostatisticscancer discoverysystems biologythoracic oncologyprognostic evaluationbiomedical informatics

Actor-Critic Alignment for Offline-To-Online Reinforcement Learning.. PubMed (2023)

Zishun YuXinhua Zhang

actor-critic alignmentreinforcement learningcomputer scienceoffline-to-online reinforcement learning

Improving Prediction of Late Symptoms Using LSTM and Patient-Reported Outcomes for Head and Neck Cancer Patients. 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI) (2023)

Yaohua WangLisanne Van DijkAbdallah S. R. MohamedMohamed NaserClifton David FullerXinhua ZhangG. Elisabeta MaraiGuadalupe Canahuate

outcomes researchoncologysurvival analysisradiation oncologylate symptomsforecastingpatient-reported outcomesprognosisfailure predictionepidemiology

Poisoning Generative Replay in Continual Learning to Promote Forgetting. Proceedings of International Conference on Machine Learning (ICML) (2023)

memory studiesmemory losscognitive sciencecontinual learningmemory

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Xinhua Zhang

Associate Professor

University of Illinois Chicago

Affiliations

College of Engineering

Computer Science

Xinhua Zhang is currently serving as a College Of Engineering Associate Professor at University of Illinois Chicago.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Xinhua Zhang

University of Illinois Chicago

Associate Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

digital healthpublic healthtime-to-osteoradionecrosis risk-stratificationcohort studies

Support Vector Machines. Cambridge University Press eBooks (2025)

Zhen “Leo” Liu

Collaborative Filtering for the Imputation of Patient Reported Outcomes. Lecture notes in computer science (2024)

Eric Ababio AnyimaduClifton David FullerXinhua ZhangG Elisabeta MaraiGuadalupe Canahuate

computer scienceoutcomes researchdata sciencepatient safetypublic healthcollaborative filteringpatient-centered outcomespatient-reported outcomes

Elisa TardiniXinhua ZhangGuadalupe CanahuateAndrew WentzelAbdallah MohamedLisanne Van DijkClifton (Dave) FullerG. Elisabeta Marai

critical caredosimetryrisk applicationactuarial scienceexternal validation

Offline Reward Perturbation Boosts Distributional Shift in Online Rl.. PubMed (2024)

Zishun YuSiteng KangXinhua Zhang

machine learningonline rloffline reward perturbationdistributional shift

Pro-Based Stratification Improves Model Prediction for Toxicity and Survival of Head and Neck Cancer Patients. IEEE Journal of Biomedical and Health Informatics (2024)

Eric A. AnyimaduYaohua WangCarla FloricelSerageldin KamelClifton David FullerXinhua ZhangG. Elisabeta MaraiGuadalupe M. Canahuate

Actor-Critic Alignment for Offline-To-Online Reinforcement Learning.. PubMed (2023)

Zishun YuXinhua Zhang

actor-critic alignmentreinforcement learningcomputer scienceoffline-to-online reinforcement learning

Improving Prediction of Late Symptoms Using LSTM and Patient-Reported Outcomes for Head and Neck Cancer Patients. 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI) (2023)

Yaohua WangLisanne Van DijkAbdallah S. R. MohamedMohamed NaserClifton David FullerXinhua ZhangG. Elisabeta MaraiGuadalupe Canahuate

outcomes researchoncologysurvival analysisradiation oncologylate symptomsforecastingpatient-reported outcomesprognosisfailure predictionepidemiology

Poisoning Generative Replay in Continual Learning to Promote Forgetting. Proceedings of International Conference on Machine Learning (ICML) (2023)

memory studiesmemory losscognitive sciencecontinual learningmemory

1
2
3
4
5
13
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