About

Amin Ghadami is a Research Assistant Professor in the departments of Civil and Environmental Engineering and Aerospace and Mechanical Engineering at the University of Southern California. He serves as the Principal Investigator of the Data-Driven Dynamics Lab, where his research focuses on data-driven reduced-order modeling in dynamical systems. His work involves developing mechanistic data-driven prediction methods and exploring multi-agent systems, aiming to advance the understanding and modeling of complex dynamical phenomena through data-centric approaches. Professor Ghadami mentors several graduate students, including Ph.D. and M.Sc. candidates, guiding research projects that apply machine learning and data-driven techniques to areas such as health monitoring of Li-ion batteries, fluid-structural system modeling, and epidemiological system dynamics. His academic background and leadership in the lab contribute to the interdisciplinary integration of mechanical, aerospace, electrical, and computer engineering disciplines at USC.

Research topics

• Computer Science
• Engineering
• Mathematics
• Physics
• Artificial Intelligence
• Microeconomics
• Economics
• Virology
• Marketing
• Structural engineering
• Algorithm
• Operations research
• Risk analysis (engineering)
• Business
• Data science
• Aerospace engineering
• Management science
• Medicine

Selected publications

• BOSA: Bayesian Online Strategy Adaptation for Unexpected Events in Multi-Agent Teams

  IEEE Systems Man and Cybernetics Letters · 2026-01-01

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  PublisherDOI

• Explaining complex dynamical systems using conditional SHAP analysis with application to multi-variant epidemic dynamics

  Scientific Reports · 2026-04-18

  articleOpen access
  PublisherDOI

• Reduced Order Modeling and Analysis of Airfoil Flutter Using Dynamics-Based Autoencoders

  AIAA Journal · 2025-05-26 · 1 citations

  articleSenior author

  Nonlinear flutter analysis is essential for ensuring the safety and performance of modern aeroelastic systems. Performing nonlinear stability analysis, however, is a challenging task for aeroelastic systems when relying on traditional approaches. This paper introduces a data-driven approach for nonintrusive nonlinear reduced order modeling and flutter analysis in aeroelastic systems. The proposed approach integrates nonlinear stability analysis for dynamical systems theory with machine learning techniques, enabling nonlinear flutter analysis with a limited number of simulated time-domain trajectories. This data-driven method determines reduced order models of systems exhibiting flutter instabilities and the transformation to and from the state space and the reduced order coordinates. Numerical results are provided to demonstrate the performance of the proposed method for a typical nonlinear airfoil section exhibiting supercritical and subcritical flutter.

  PublisherDOI

• Leveraging Systems-of-Systems Analysis to Strengthen Epidemic Intelligence for Preparedness and Response

  Health Security · 2025-12-01

  article

  The COVID-19 pandemic exposed significant gaps in the coordination and integration of efforts required to effectively manage large-scale infectious disease outbreaks. A successful response to such crises demands the swift and ongoing synthesis of information and activities across multiple sectors, including government, healthcare, and private industry. However, these systems are often managed in isolation, leading to misaligned policies, fragmented communications, and inefficiencies that hinder pandemic response efforts. To address these challenges, we propose adopting a systems-of-systems (SOS) paradigm to enhance epidemic intelligence and improve preparedness and response during infectious disease emergencies. The SOS approach, widely used in engineering, offers a framework for integrating diverse fields such as virology, ecology, psychology, and policy. We illustrate the potential of this approach using highly pathogenic avian influenza (HPAI) as a case study and discuss key considerations for implementing SOS thinking in the context of global epidemic intelligence systems.

  PublisherDOI

• Experimental parametric study of a flap-NES passive absorber for post-flutter control

  Journal of Fluids and Structures · 2025-08-24

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• Development of Active Chitosan Film Based on Bacterial Cellulose Nanofiber Incorporated With ZnO Nanoparticles for Monitoring Hamburger Spoilage

  Journal of Food Processing and Preservation · 2025-01-01 · 2 citations

  articleOpen access1st author

  Food safety is a global concern due to the dangers posed by microbial pathogens, toxins, and food spoilage. Hence, antibacterial and antioxidant compounds have been widely studied for food packaging. This research was aimed at the effect of chitosan (C) film containing bacterial cellulose (BC) nanofibers and zinc oxide (ZnO) nanoparticles (NPs) on the hamburger shelf life. Four types of films including C, chitosan + bacterial cellulose (C‐BC) nanofibers, and chitosan + bacterial cellulose nanofiber + zinc oxide nanoparticle at two concentrations of 1% (C‐BC‐ZnO NP‐1) and 2% (C‐BC‐ZnO NP‐2) were prepared. The results showed that adding of ZnO NPs decreased the thickness and water vapor permeability, increased the opacity, and improved the mechanical properties and thermal stability of films ( p < 0.05). C‐BC‐ZnO NP‐1 had higher tensile strength, elongation at break, modulus of elasticity (ME), and melting temperature ( T m ) than other nanocomposites. A scanning electron microscope (SEM) showed a good distribution of ZnO NPs in the film matrix. The nanocomposites had a significant effect on the chemical and microbial characteristics of hamburger. The lowest pH; total volatile nitrogen (TVN) compounds; peroxide value; thiobarbituric acid; and the total count of mesophilic and psychrophilic bacteria, mold, and yeast population were observed in C‐BC‐ZnO NP‐1 and C‐BC‐ZnO NP‐2 groups ( p < 0.05). In the sensory evaluation, the nanocomposite containing 1% ZnO NPs showed higher overall acceptance than 2%. In general, adding ZnO NPs improves the physical properties of C film and can be used as active packaging in meat products.

  PublisherOA PDFDOI

• Experimental Bifurcation Forecasting Using the Transient Response of an Airfoil in a Wind Tunnel

  Conference proceedings of the Society for Experimental Mechanics · 2024-01-01

  book-chapter
  PublisherDOI

• Dynamic task planning for autonomous reconfigurable manufacturing systems by knowledge-based multi-agent reinforcement learning

  CIRP Annals · 2024-01-01 · 12 citations

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• Data-driven bifurcation analysis using parameter-dependent trajectories

  International Journal of Non-Linear Mechanics · 2024-11-01 · 1 citations

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  PublisherDOI

• Continuous training based on the needs of operating room nurses using web application: a new approach to improve their knowledge

  BMC Medical Education · 2024-03-26 · 10 citations

  articleOpen accessSenior authorCorresponding

  INTRODUCTION: Since university education and intensive and limited pre-service training do not provide an acceptable level of performing the duties of operating room nurses, and considering the limitations of traditional training methods in the field of operating room; This study was conducted with the aim of determining the effect of using the electronic education approach based on web application, leveled, personalized and based on the needs of nurses on their level of knowledge and satisfaction. MATERIALS AND METHODS: This research is a quasi-experimental type of single-group multi-center pre-test-post-test, which during that, four stages of educational needs assessment, educational content design, web application design for training and evaluation of operating room nurses and determining the effectiveness of this method are included. Based on their knowledge and satisfaction, during this period, 36 nurses from the operating rooms that met the study criteria were included in the study by stratified random sampling based on the determined sample size. The data collection includes a four-choice test to measure the knowledge of operating room nurses in heart anatomy (score range 0-20), the principles of movement, transferring and positioning of the patient in the operating room (score range 0-15), the principles of ergonomics in the operating room (score range score 0-10) and satisfaction questionnaire (score range 0-28). Data collected using descriptive statistical tests (percentage of frequency and frequency, mean and standard deviation) and analytical tests (paired sample t-test, independent samples t-test, ANOVA, Pearson correlation, chi-square) with the software SPSS version 16 was analyzed. RESULTS: Generally, the average knowledge scores of operating room nurses before and after the intervention were 5.96 ± 3.96 vs. 13.6 ± 3.77, in the course of principles of moving, transferring and positioning the patient in the operating room were 6.3 ± 3.42 vs. 13.3 ± 1.32, respectively 8.7 ± 3.97 vs. 18.1 ± 1.07 (in heart anatomy), 1.57 ± 2.6 vs. 0.73 ± 9.1 (in the principles of ergonomics in the operating room) and the average Knowledge scores after the intervention were significantly higher than before the intervention (P<0.001). Also, the average satisfaction score of nurses was 21.3 ± 5.83 and 22 nurses (64.7%) were satisfied with the e-learning course. CONCLUSION: The use of the electronic education approach based on the web application, leveled, personalized and based on the needs of the nurses, led to the improvement of the level of knowledge and satisfaction of the operating room nurses. E-learning can be used as a complementary educational tool and method for continuous training of operating room nurses in other specialized fields of operating room and surgery. HIGHLIGHTS: • Educational content in the form of educational videos taught by professors of medical sciences universities on each of the topics of heart anatomy (28 episodes of 5-10 minutes), principles of ergonomics in the operating room (7 episodes of 5-25 minutes) and movement principles. The transfer and positioning of the patient in the operating room (16 episodes of 10-20 minutes) were designed in three primary, intermediate and advanced levels. • The results of this study showed that the use of an electronic education approach based on the web application, levelled, personalized and based on the needs of nurses, led to the improvement of the knowledge of operating room nurses. Also, operating room nurses were delighted with electronic training courses. E-learning can be used as a complementary educational tool and method for continuous training of operating room nurses in other specialized fields of operating room and surgery. • Based on the results of this study, the use of an electronic education approach based on the needs of operating room nurses can be used as a complementary tool to conventional continuous education. Since this method allows interactive, personalized education is levelled, and asynchronous. It can be used at any time and place on a laptop, tablet or mobile phone; a wide range of operating room nurses in the hospitals of the Islamic Republic of Iran can use it for educational justice to Many borders should be established in the country. However, there are studies to evaluate the generalizability and the effect of using the e-learning approach on the clinical skills of operating room nurses and to compare the effect of e-learning with other methods and educational tools on the knowledge and skills of the learners and the extent of consolidating the learned material in their memory.

  PublisherOA PDFDOI

Frequent coauthors

• Bogdan I. Epureanu

  University of Michigan–Ann Arbor

  34 shared

• Guilhem Michon

  12 shared

• Leonardo Sanches

  Université de Toulouse

  12 shared

• Jesús García Pérez

  University of Michigan–Ann Arbor

  8 shared

• Haochen Wu

  6 shared

• Pejman Rohani

  Children's Medical Center

  4 shared

• Hamid Reza Mirdamadi

  4 shared

• John M. Drake

  University of Georgia

  4 shared

Labs

• Data-Driven Dynamics LabPI

Education

• Ph.D., Mechanical Engineering

  University of Southern California

  2006

• M.S., Mechanical Engineering

  University of Southern California

  2003

• B.S., Mechanical Engineering

  University of Tehran

  1999

Awards & honors

• The Engineers Council Future Technology Leader Award (2026)
• AFOSR Young Investigator Award (2025)
• ASME Rising Star of Mechanical Engineering (2025)
• Finalist, U&AI competition, United Nations Development Progr…
• Rising Star in Mechanical Engineering, UC-Berkeley (2020)