Our research group in the Department of Mechanical Engineering at the University of Texas at San Antonio (UTSA) works on statistical learning for systems modeling, control, and optimization. Our work is strongly data-driven, where engineering knowledge and management science are paired with mathematical models and data-driven methods to drive meaningful change in complex systems. Our developed methodologies have been considerably funded and widely utilized in a variety of applications ranging from healthcare to defense to manufacturing.





  • 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 2022, 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, 119759

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

  • 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)

  • 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



  • January 2022, Dr. Alaeddini served on NSF Panel Review: AI/ML Core Small Panel

  • January 2022, The Collaborative Project "Toward Optimal Transportation Electrification: Collaborative Smart Grid Urban Planning using AI-Driven City-Scale Digital Twin"  has been selected as a finalist to compete for $200k award from CPSE, PI: Dr. Alaeddini, Co-PIs: Dr. Paul Rad, Dr. Krystel Castillo.

  • January 2022, Patent Disclosure, 2022.017.UTSA, "Integrated Mobile Platform for Maritime Target Detection and Tracking in Real-Time", Inventor: K. Bhaganagar, A. Alaeddini, Prasanna Kolar

  • December 2021, Publication, 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.

  • November 2021, Dr. Alaeddni became the Chair of INFORMS Quality, Statistics & Reliability Section (https://connect.informs.org/qsr/home)

  • November 2021, Dr. Alaeddni became the Director of the Center for Advanced Manufacturing and Lean Systems (CAMLS)

  • November 2021,  $352k  award from AFOSR for the 3-year project  "A Novel Semi-Supervised Kernel Formulation for Extrapolation from Small Datasets: Rapid Predictive Modeling of the Effect of a Leeway Object Geometry on its Drift and Divergence in Deep Waters", PI: Dr. Alaeddini (UTSA), Co-PI: Dr. Bhaganagar (UTSA).

  • October 2021,  $183,976 award from SAMF for the 1-year project  "Biometric Collaborative Radiology Artificial Intelligence", PI: Golob (PI), Co-PI: Alaeddini (UTSA).


  • A Graduate Research Assistant (GRA) position is available for students with a solid math (statistical) background and good programming (MATLAB/Python) skills