​​

2025

• Martinez, Stanford, Alaeddini, Adel, "Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study." Technometrics, (2025) Just-Accepted.

• ​​​J.C. Rico SM, S.H.A. Faruqui, A. Alaeddini*, S. Fisher-Hoch, J. Mccormick, A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network, IEEE Journal of Biomedical and Health Informatics, 2025, Accepted

• S. Martinez SM, A. Alaeddini*, Gradient and Acceleration Enhanced Semi-Supervised Kernel for Sample Efficient Learning of Expensive Functions. Technometrics, (2024): Tentative Acceptance.

• S Martinez SM, C Ramirez-Tamayo SM, SHA Faruqui, K Clark, A Alaeddini *, …, Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study, JMIR Formative Research 9 (1) (2025), e53928, DOI: 10.2196/53928

• DL Andrew SM, R Ribeiro, M Thomsen, J Ocampo, A Alaeddini, CF Popelar, ...

• Utilizing Spatial Statistical Bounds on Residual Stress Fields From Cold Expansion: Effects on Fatigue Crack Growth Behavior, Fatigue & Fracture of Engineering Materials & Structures 48 (1) (2025) , 244-260, DOI: 10.1111/ffe.14481

• M Pullen SM, L Neely, M Kirkpatrick, A Alaeddini, Teaching pool side safety skills to decrease elopement-related incidents for children with ASD, Journal of Developmental and Physical Disabilities 36 (6) (2025) , 1055-1068, DOI: 10.1007/s10882-024-09978-0

 

2024

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• K Keith SM; K. K. Castillo-Villar*, A. Alaeddini, Machine Learning based Problem Space Reduction in Stochastic Programming Models: An Application in Biofuel Supply Chain Network Design, IEEE ACCESS, (2024): 33852 – 33866. DOI:10.1109/ACCESS.2024.3372516

• M. Chang SM, A. Alaeddini*, Few-shot Classification with Prototypical Neural Network for Hospital Flow Recognition under Uncertainty, Network Modeling Analysis in Health Informatics and Bioinformatics, 13.1 (2024): 1-11. DOI: 10.1007/s13721-024-00450-9

• H.K. Koodiani SM, E. Jafari SM, A. Majlesi SM, M. Shahin SM, A. Matamoros, A. Alaeddini, Machine Learning Tools to Improve Nonlinear Modeling Parameters of RC Columns, Journal of Building Engineering. 84 (2024): 108492. DOI: 10.1016/j.jobe.2024.108492

• J.C. Rico SM, A. Alaeddini*, S.H.A. Faruqui, S.P. Fisher-Hoch, J.B. Mccormick, A Laplacian Regularized Graph Neural Network for Predictive Modeling of Multiple Chronic Conditions, Computer Methods and Programs in Biomedicine, (2024): 108058. DOI: 10.1016/j.cmpb.2024.108058

• N. Pallotta*, J. Lane, J.M. Locklear, X. Ren, V. Robila, A. Alaeddini, Discovering data sets in unstructured corpora: Discovering use and identifying new opportunities, Harvard Data Science Review (2024), Just Accepted. DOI: 10.1162/99608f92.77bfa1c9

• C. Ramirez-Tamayo SM, S.H.A. Faruqui, S. Martinez SM, A. Brisco, N. Czarnek, K. Clark, A. Alaeddini*, J.R. Mock, E. J. Golob, Incorporation of Eye-Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-rays: A Randomized Controlled Clinical Trial, Journal of the American College of Radiology, (2024): Just Accepted. DOI: 10.1016/j.jacr,2024.02.001

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2023

​​​

• H.K. Koodiani, E. Jafari, A. Majlesi, M. Shahin, A. Matamoros, A. Alaeddini, Machine Learning Tools to Improve Nonlinear Modeling Parameters of RC Columns, Elsevier, Accepted.

• S.H.A. Faruqui, A. Alaeddini, Y. Du, S. Li, K. Sharma, J. Wang, Nurse-in-the-Loop Artificial Intelligence for Precision Management of Type 2 Diabetes in a Clinical Trial Utilizing Transfer-Learned Predictive Digital Twin, arXiv e-prints.

• P. Bhounsule, D. Torres, E.H Hinojosa, A. Alaeddini, Task-Level Control and Poincaré Map-Based Sim-To-Real Transfer for Effective Command Following of Quadrupedal Trot Gait,  IEEE.

• J. Krause, A. Alaeddini, P. Bhounsule, Gaussian Process Regression for Sim-To-Real Transfer of Hopping Gaits, American Society of Mechanical Engineers, Accepted. 

• M. Chang, S.H.A. Faruqui, A. Alaeddini, H. Wan, Evaluation and Improvement of Student Learning Experience in the Post-COVID World: A Lean Six-Sigma DMAIC Study, SAGE Publications.

• C. Ramirez-Tamayo, S.H.A. Faruqui, S. Martinez, A. Brisco, N. Czarnek, A. Alaeddini, J. Mock, E. Golob, K. Clark, Incorporation of Eye-Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-rays: A Randomized Controlled Clinical Trial,  arXiv preprint.

• S. Martinez, C. Ramirez-Tamayo, S.H.A. Faruqui, K. Clark, A. Alaeddini, N. Czarnek, A. Aggarwal, S. Emamzadeh, J. Mock, E. Golob,  Discrimination of Radiologists Utilizing Eye-Tracking Technology and Machine Learning: A Case Study, arXiv preprint.

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2022

​​

• S. Martinez, A. Alaeddini, A Laplacian‐Regularized Dual‐Phase Gaussian Process Technique for Semi‐Supervised Response Surface Modeling of Black‐Box Functions, Quality and Reliability Engineering International.

• Y. Du, J. Wang, S.  Li, B. Dennis, C. Meireles, N. Siddiqui, D. Patel, J. Gelfond, C. Li, A. Alaeddini, V. Drel, J. Tumova, H. Ye, R. Montellano, G. Armaiz-Pena, K. Sharma, A Technology Assisted Precision Ketogenic Diet Intervention for Cardio-Renal-Metabolic Health in Overweight or Obese Adults: Protocol for a Randomized Controlled Trial, Elsevier, Accepted, 

• K. Bhaganagar, P. Kolar, S.H.A.  Faruqui, D. Bhattacharjee, A. Alaeddini, K. Subbarao, A Novel Machine-Learning Framework With a Moving Platform for Maritime Drift Calculations, Frontiers, Accepted, 

• S.H. Silva, A. Das, A. Alaeddini, P. Najafirad, Adaptive Clustering of Robust Semantic Representations for Adversarial Image Purification on Social Networks, Proceedings of the International AAAI Conference on Web and Social Media, Accepted,

• Y. Zeng, P. Shojaee, S.H.A. Faruqui. Alaeddini, R. Jin, Contextual Bandit Guided Data Farming for Deep Neural Networks in Manufacturing Industrial Internet, IEEE Access, Accepted.

• S.H.A. Faruqui, A. Alaeddini, J. Wang,  S. Fisher-Hoch, J. Mccormick, J. Carvajal, A Model Predictive Control Functional Continuous Time Bayesian Network for Self-Management of Multiple Chronic Conditions, arXiv e-prints, Accepted.

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2021

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• S.H.A. Faruqui, A. Alaeddini, S. Fisher-Hoch, J. Mccormick, Dynamic Functional Continuous Time Bayesian Networks for Prediction and Monitoring of the Impact of Patients Lifestyle Behaviours on the Emergence of Multiple Chronic Conditions, IEEE Access, Accepted.

• S.H.A. Faruqui, A. Alaeddini, J. Wang, C. Jaramillo, M.J. Pugh, Functional Continuous Time Bayesian Networks for Exploring the Evolution of Multiple Chronic Conditions, IEEE Access, Accepted.

• R. Meka, A. Alaeddini, Nonso Ovuegbe1, Pranav Bhounsule, P. Rad, k. Yang, Multi-Armed Bandit Regularized Expected Improvement for Efficient Global Optimization of Expensive Computer Experiments, IEEE Access, 9 (2021): 100125-100140.

• R. Meka, A. Alaeddini, K. Bhaganagar, A Robust Deep Learning Framework for Short-Term Wind Power Forecast of a Full-Scale Wind Farm using Atmospheric Variables, Energy, 221 (2021), 119759

• DL. Andrew, HC. Han, J. Ocampo, A. Alaeddini, M. Thomsen, Characterization of residual stresses from cold expansion using spatial statistics, Fatigue & Fracture of Engineering Materials & Structures, 44 (1) (2021): 101-114

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2020

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• One-Step Deadbeat Control of a 5-Link Biped Using Data-Driven Nonlinear Approximation of the Step-to-Step Dynamics, Publication in Robotics, Accepted

• J. Ocampo De Los Rios, H.C. Han, A. Alaeddini, M. Thomsen, Characterization of residual stresses from cold expansion using spatial statistics, Fatigue & Fracture of Engineering Materials & Structures, Accepted,

• R. Meka, A. Alaeddini, S. Oyama, K. Langer, An Active Learning Methodology for Efficient Estimation of Expensive Noisy Black-Box Functions using Gaussian Process Regression. IEEE Access (2020)

• S. H. Silva, A. Alaeddini, P. Najafirad, Temporal Graph Traversals Using Reinforcement Learning With Proximal Policy Optimization. IEEE Access, 8, 63910-63922 (2020)

• S.H. Faruqui, A. Alaeddini, M. C. Chang, S. Shirinkam, C.A. Jaramillo, P. Najafirad, M.J. Pugh. Summarizing Complex Graphical Models of Multiple Chronic Conditions Using the Second Eigenvalue of Graph Laplacian: Algorithm Development and Validation. JMIR Medical Informatics, 8(6), e16372   (2020)

• M. Huang, Y. Wang, S. Shirinkam, A. Alaeddini, K. Yang, Application of Multivariate Control Chart Techniques to Identifying Nonconforming Pallets in Automotive Assembly Plants (No. 2020-01-0477). SAE Technical Paper (2020)

• J. Nielson, K. Bhaganagar, R. Meka, A. Alaeddini, Using Atmospheric Inputs for Artificial Neural Networks to Improve Wind Turbine Power Prediction, 190 Energy (2020): 116-273.. (5-Year Impact Factor: 5.747)

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2019

​

• J. Sumner, A. Alaeddini, Analysis of Feature Extraction Methods for Prediction of 30-Day Hospital Readmissions. Methods of Information in Medicine, 58(06), 213-221 (2019)

• S.H.A. Faruqui, Y. Du, R. Meka, A. Alaeddini, C. Li, S. Shirinkam, J. Wang, Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial JMIR mHealth and uHealth 7, no. 11 (2019): e14452. (Impact Factor: 4.301)

• S. Shirinkam, A. Alaeddini, E. Gross, Identifying the Number of Components in Gaussian Mixture Models using Numerical Algebraic Geometry, Journal of Algebra and its Applications, (2019), In Press. DOI: 10.1142/S0219498820502047

• S. Martinez, A. Alaeddini, K. Langer, A Sequential Weighted Laplacian Regularized Optimal Design for Response Surface Modeling of Expensive Functions with Outliers: An Application in Linear Elastic Fracture Mechanics, Quality Reliability Engineering International, 35.6 (2019):1911–1928. DOI: 10.1002/qre.2483

• A. Alaeddini, P. Shi, J. E. Helm, S.H. Faruqui, An Integrated Framework for Reducing Hospital Readmissions using Risk Trajectories Characterization and Discharge Timing Optimization, IIE Transactions on Healthcare Systems Engineering, 9.2 (2019): 172-185. DOI: 10.1080/24725579.2019.1584133

• A. Alaeddini, R. Meka, S. Martinez, E. Kraft, Sequential Laplacian Regularized V-Optimal Design of Experiments for Response Surface Modeling of Expensive Tests: An Application in Wind Tunnel Testing, IIE Transactions. 51.5 (2019): 559-576. DOI: 10.1080/24725854.2018.1508928

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2018

 

• S.H. Faruqui, A. Alaeddini, C.A. Jaramillo, J.S. Potter, M.J. Pugh. Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network. PLOS One. 13.7 (2018):1-22. DOI: 10.1371/journal.pone.0199768 J

• A. Alaeddini, A. Motasemi, S.H.A. Faruqui, A Spatiotemporal Outlier Detection Methodology based on Partial Least Square Regression and Area Delaunay Triangulation for Image-based Process Monitoring, IIE Transactions, 50.2 (2018): 74-87. DOI: 10.1080/24725854.2017.1386336

 

2017

 

• A. Alaeddini, C. Jaramillo, M.J. Pugh, S.H.A. Faruqui, Mining Major Transitions of Chronic Conditions in Patients with Multiple Chronic Conditions, Methods of Information in Medicine, 56.5 (2017): 391-400.

• A. Alaeddini, SH. Hong, A Multi-Way Multi-Task Learning Approach for Multinomial Logistic Regression: An Application in Joint Prediction of Appointment Miss-Opportunities across Multiple Clinics, Methods of Information in Medicine, 56.4 (2017): 294-307. DOI: 10.3414/ME16-01-0112.

• M. H. Bakhtiarifar, A. Amiri, A. Alaeddini, Economic-Statistical Design of Shewhart Control Charts with Fuzzy Parameters, Journal of Intelligent & Fuzzy Systems, 32.6 (2017): 3961-3971. DOI: 10.3233/JIFS151097.

 

2016

 

• A. Motasemi, A. Alaeddini, and C. Zou. An Area-based Methodology for the Monitoring of General Linear Profiles. Quality and Reliability Engineering International, (2016): 159-181. DOI: 10.1002/qre.1998.

• S. Shirinkam, A. Alaeddini, H. Millwater, On the Application of Multicomplex Algebras in Numerical Integration, Applied Mathematics & Information Sciences, 10.1 (2016): 1-9. DOI: 10.18576/amis/100101.

 

Earlier

 

• J. E. Helm, A. Alaeddini, J. Stauffer, K. Bretthauer, Reducing Hospital Readmissions by Integrating Empirical Prediction with Resource Optimization, Production and Operations Management, 25.2 (2015): 233–257. DOI: 10.1111/poms.12377.

•  A. Alaeddini, Ch. K. Reddy, K. Yang, Predicting Disturbances in Appointment Scheduling through Hybrid Probabilistic Modelling, IIE Transactions on Healthcare Systems Engineering, 5.1 (2015): 14-32. DOI: 10.1080/19488300.2014.993006.

• A. Alaeddini, K. Yang, H. Mao, A. Murat, B. Ankenman, An Adaptive Sequential Experimentation Methodology for Expensive Response Surface Optimization- Case Study in Traumatic Brain Injury (TBI) Modelling. Quality and Reliability Engineering International, (2014): 767-793. DOI: 10.1002/qre.1523.

•  G. Abdella, K. Yang, A. Alaeddini, Multivariate Adaptive Approach for Monitoring Simple Linear Profiles (VSSI-T2), International Journal of Data Analysis Techniques and Strategies (IJDATS), Special Issue for Micro Array Quality control, 6.1 (2014): 2-14.

• A. Alaeddini, A. Murat, K. Yang, B. Ankenman, An Efficient Adaptive Sequential Methodology for Expensive Response Surface Optimization, Quality and Reliability Engineering International, 29.6 (2013): 799-817. DOI: 10.1002/qre.1432

•  A. Alaeddini, K. Yang, A. Murat, ASRSM: A Sequential Experimental Design for Response Surface Optimization, Quality and Reliability Engineering International, 29.2 (2013): 241-258. DOI: 10.1002/qre.1306.

•  G. Abdella, K, Yang, A. Alaeddini, On the Effect of Location of Explanatory Variable on Monitoring Polynomial Quality Profiles, International Journal of Engineering, 25.2 (2012): 131-140 ISSN 1025-2495.

• A. Alaeddini, I. Dogan, Using Bayesian Networks for Root Cause Analysis in Statistical Process Control, Expert Systems with Applications, 38.9 (2011): 11230-11243

• Y. Guo, K. Yang, A. Alaeddini, A Truncated Logistic Regression Model in Evaluation of Probability of Detection, Quality Engineering, 23.4 (2011): 365-377

• A. Alaeddini, K. Yang, S. Q. Yu, Ch. K. Reddy, A Probabilistic Model for Predicting the Rate of No-Show in Hospital Appointments, Healthcare Management Science, 14.2 (2010): 146-157, DOI: 10.1007/s10729-011- 9148-9.

•  M.H. Fazel Zarandi, A. Alaeddini, A General Fuzzy-Statistical Clustering Approach for Estimating the Time of Changes in Variable Sampling Control Charts, Information Sciences, 180 (2010): 3033–3044

• M.H. Fazel Zarandi, A. Alaeddini, I.B. Turksen, M. Ghazanfari., Using Adaptive Neuro-Fuzzy Systems to Monitor Linear Quality Profiles, Journal of Uncertain Systems, 4.2 (2010): 147-160

• A. Alaeddini, K. Yang, Adaptive Sequential Experiment Methodology for Response Surface Optimization, International Journal Quality Technology and Engineering, 1 (2009): 20-61.

• Alaeddini, M. Ghazanfari, M. Amin Nayeri, A Hybrid Fuzzy-Statistical Clustering Approach for Estimating the Time of Changes in Shewhart Control Charts, Information Sciences, 170.11 (2009): 1769-1784.

• M. Ghazanfari, A. Alaeddini, S.T.A. Niaki, M.B.G. Aryanejad, A Clustering Approach to Identify the Time of a Step Change in Shewhart Control Charts, Quality and Reliability Engineering International, 24.7 (2008): 765-778.

• M.H. Fazel Zarandi, A. Alaeddini, I.B. Turksen, A Hybrid Fuzzy Adaptive Sampling –Run Rules for Shewhart Control Charts, Information Sciences, 17.8 (2008): 1152–1170.

• M. Ghazanfari, A. Alaeddini, K. Noghondarian, A Novel Fuzzy Clustering Approach for Estimating the Time of Step Changes in Shewhart Control Charts, International Journal of Industrial Engineering and Production Research, 19.4 (2008): 39-64.

• R. Noorosana, A. Alaeddini, Using Constraint Area Between Reference and Observed Curves to Monitor Nonlinear Profiles”, Azad University Research Journal, 54 (2004): 117-124.

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