2024

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• J Carvajal-Rico, SHA Faruqui, A Alaeddini, S. Fisher-Hoch, J. Mccormick, A Laplacian Regularized Graph Neural Network for Predictive Modeling of Multiple Chronic Conditions, Computer Methods and Programs in Biomedicine.

• 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, Accepted.

• K Keith; 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, Accepted.

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2023

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• 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

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• 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

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• 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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