team

Dr. Amir H. Alavi

Assistant Professor

Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.

Dr. Amir H. Alavi is an Assistant Professor in the  Department of Civil and Environmental Engineering at the  University of Pittsburgh. Dr. Alavi’s research interests include structural health monitoring, smart civil infrastructure systems, deployment of advanced sensors, energy harvesting, and civil engineering system informatics. He has worked on research projects supported by Federal Highway Administration (FHWA), National Institutes of Health (NIH), National Science Foundation (NSF), Missouri DOT, and Michigan DOT. Dr. Alavi has authored 5 books and over 170 publications in archival journals, book chapters, and conference proceedings. He has received a number of award certificates for his journal articles. Recently, he has been selected among the Google Scholar 200 Most Cited Authors in Civil Engineering, as well as Web of Science ESI's World Top 1% Scientific Minds. He has served as the editor/guest editor of several journals such as Case Studies in Construction Material, Automation in Construction, Geoscience Frontiers, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, and Advances in Mechanical Engineering. Dr. Alavi received his PhD degree in Civil Engineering from Michigan State University.

 

|Faculty Page|LinkedIn||G-Scholar|ResearchGate|

 

Kaveh Barri

PhD Student

Qianyun Zhang

PhD Student

Join Our Team:
Candidates with a background in smart infrastructure, smart sensing materials, structural health monitoring, energy harvesting, and civil engineering system informatics are highly encouraged to contact Dr. Alavi regarding the availability of graduate research assistantships/fellowship. Undergraduate students at Pitt or from other peer institutions are welcomed to join our team for research internship. Furthermore, there are open positions for visiting professors. Please send your resume to Dr. Alavi at alavi@pitt.edu.

 

RESEARCH

 

 

Overview of Research Projects

 

A Framework for Civil Infrastructure Health Monitoring Based on Integration of Self-Powered Sensing Technology and Advanced Data Analytics (FHWA: DTFH61-13-H-00009) PDF

Recently, significant attention has been devoted to the utilization of new sensing technologies for infrastructure/structural health monitoring (I/SHM). In this context, wireless sensor networks are increasingly utilized as alternatives to traditional I/SHM systems. Finding a cost-effective sustainable energy resource for empowering the wireless sensors still remains a major concern for their wide application. A viable solution to this limitation is developing self-powered wireless sensors that harvest the micro-strain energy of structures. On the other hand, interpretation of the valuable but limited data measured by this type of sensors is a challenging task. The main goal of our interdisciplinary research, which has been funded by FHWA, is to address these issues through the development of an advanced data analysis framework for civil I/SHM based on a pioneering self-powered sensing technology. The current work characterizes the performance of a fairly new class of self-powered sensors for specific application problems with complex behavior. The proposed health monitoring systems are established through the integration of statistical, machine learning and finite element methods. Different infrastructure systems with various damage types are analyzed using sensor networks (e.g. steel bridge girders of I-96/M-52 Bridge, gusset plate of the I-35W Highway Bridge, steel plates, and pavement systems).

 

Figure 1: (a) Different prototypes of the self-powered sensor for infrastructure monitoring, (b) Reading data from a network of self-powered sensors and transmission of the data to the cloud through IoT, and (c) Real-time monitoring using Microsoft certified IoT module connected to the self-powered sensor.

 

The network architecture comprises self-powered sensors that use the electrical energy directly harvested by piezoelectric ceramic Lead Zirconate Titanate (PZT) or polyvinylidene difluoride (PVDF) transducers. The beauty of this so-called self-powered monitoring system is that the operating power for the smart sensors directly comes from the signal being monitored. An advantage of using these sensors is that there is no need to directly measure the absolute value of strain in order to estimate damage. In fact, the proposed self-sustained sensing systems use the sensor output to relate the variation rate of strain distributions to the rate of damage. These smart sensing units possess several novel features including: low cost (<$1 in raw materials in production!), low power requirements (<1 μW), self-powered continuous sensing (battery-free), the ability to deploy in dense networks, small size (order of a coarse aggregate particle), robust on-board computing data storage and wireless communication. The data stored in memory chips of the sensor can be read using RF readers that are operated manually or mounted on a moving vehicle or on an unmanned aerial vehicle (UAV) (see Figure 1). The data received by the reader can be logged with data acquisition units (e.g., a Raspberry Pi platform) which can be directly connected to the cloud or periodically uploaded to a central processing unit and then wirelessly pushed into the cloud based on the Internet of Things (IoT) technology. During the upcoming full-scale pilot projects, (Big) Data Analytics and machine learning will provide powerful data-driven decision-making tools through interpretation of the information from a network of smart sensors.

 

However, we believe this framework can serve as an integral part of the next generation of Smart Civil Infrastructure, which will be capable of self-charging and self-diagnosis of damage well in advance of the occurrence of (catastrophic) failures. In addition, such integrated sensing platform can be modified to become building blocks of future medical, mechanical, civil, transportation, and aerospace long-term sensing technologies in Smart Cities.

 

References:

Chakrabartty S., Lajnef N., Elvin N., Elvin A., Gore A., (2011). Self-powered Sensor. US Patent Number: US 8,056,420 B2.

Lajnef N., Chatti K., Chakrabartty S., Rhimi M., Sarkar P., (2013) Smart Pavement Monitoring System. Report: FHWA-HRT-12-072, Federal Highway Administration (FHWA), Washington, DC.

Alavi A. H., Hasni H., Lajnef  N., Chatti K., Faridazar F., (2016). An Intelligent Structural Damage Detection Approach Based on Self-Powered Wireless Sensor Data. Aut Construct., 62:24–44.

Alavi A. H., Hasni H., Lajnef  N., Chatti K., (2016). Damage Growth Detection in Steel Plates: Numerical and Experimental Studies, Eng. Struct., 128:124-138.

 

 

Biomedical Sensors: Wireless, Self-Powered Sensors for Continuous and Long-term Monitoring of the Spinal Fusion Process (NIH Grant Number: 1R21AR075242-01)

One of the other Pitt’s iSMaRT group main research areas is deploying smart biomedical sensing and monitoring systems. Our recent NIH-funded project is focused on the feasibility of a wireless, self-powered sensors capable of monitoring the spinal fusion. Achieving better surgical outcomes and research studies involving lumbar spinal fusion requires reliable determination and degree of fusion. Current imaging technologies are not suitable to accurately and reliably determine different degrees of spinal fusion. These modalities are costly and expose the patient to significant radiation. In addition, nearly all of the previously developed implantable telemetry systems comprise on-board energy storage devices (batteries and super-capacitors) for sensing, computation, storage, and wireless communication. In collaboration with Washington University in St. Louis, our goal is to design and test a fully integrated spinal fusion implant which is completely self-powered by the micro-motion of the spine. Data collected by the sensor will be wirelessly retrieved using a portable ultrasound-scanner and the resulting output will be time-evolution curves, which will be correlated with the changes of functional spinal unit (FSU) stiffness (see Figure 2). These evolution curves would enable clinicians to differentiate between conditions of osseous union, assess the effective fusion period, and schedule for more accurate implant removal in several types of spinal fusion procedures. Upon successful completion of this study, we will demonstrate in-vitro monitoring of clinically relevant dynamics underlying the process of spinal fusion. Such a powerful tool would enable design of the next-generation, smart fixation-devices with self-monitoring capabilities.

 

Figure 2. Vision of the proposed research for reliable determination of spinal fusion development post-surgery.

 

Smartphone Technology: A Connected Citizen-Engaged Monitoring System (MoDOT Project #TR201709) PDF 1, PDF 2

In a recent report by the American Society of Civil Engineers (ASCE 2017), the country’s aging infrastructure has received a D+ grade. An estimated $206 billion must be invested each year to raise the overall infrastructure grade and to maintain US global competitiveness by 2025 (ASCE 2017). The losses associated with aging and deterioration in the US infrastructure are significant. An example is the $67 billion cost imposed annually on drivers due to the poor condition of 32% of America’s major roads. However, the challenges of aging infrastructure networks imply the need for developing innovative civil infrastructure monitoring solutions. These issues have been exacerbated by increased urbanization and have created a market for ‘Smart City’ technologies and software platforms. It is estimated that the development of truly Smart Cities will create a global technology market of over $1.5 trillion by as early as 2020, and will remain on the center stage as one of the most important challenges for city planners and managers and for researchers and technology providers over the next few decades (Frost & Sullivan 2013). The next generation Smart Cities will be heavily dependent on the integration of smart infrastructure with information and communication technologies (ICT) and the Internet of Things (IoT). Seamless connectivity through a smart communication system is arguably an important component of such platform (Figure 3). Smartphones are clearly a critical, enabling technology for smart communication because of their ubiquity, mobility and provision for customized collection of data (Jiang and McGill 2010).

 

Figure 3. Smartphone-based enabling technology in Smart Cities (Alavi and Buttlar 2019).

 

The pervasive smartphones are poised for a bright future as unique mobile sensing units for smart civil infrastructure monitoring (Alavi and Buttlar 2018, 2019; Buttlar et al. 2018). Modern smartphones are instrumented with various sensors such as a barometer, gyroscope, accelerometer, proximity sensor, camera, touch screen, microphone, ambient light sensor, magnetometer, and have significant on-board computing capabilities. They are equipped with batteries that are charged by their users and have storage in the order of gigabytes. Moreover, smartphones are supported by mobile operating systems and wireless communication hardware that can be used for field data collection and uploading real-time data to a server via Bluetooth, Wi-Fi, 3G, 4G and 5G networks. All these features imply that smartphones can become central to future civil infrastructure monitoring systems. The main goal of our research in this arena is to harness the power of smartphone technology to improve the health and well-being of the US citizens via developing a transformative and human-centered CIS monitoring methodology. The proposed methodology essentially creates a cyber-physical system (CPS) through mobile crowdsourcing. This CPS platform links the physical, sensor, and cyber system objects through a multilayered information processing framework (Figure 4). The platform will be integrated with Big Data analytics and machine learning methods that can adaptively explore the patterns and provide powerful toolset for intelligent decision-making.

 

Figure 4. A conceptual smartphone-based CPS for civil infrastructure monitoring.

References:

Alavi, A.H., Buttlar, W.G., (2018). Data Analytics Applications for Smart Cities. Taylor & Francis, CRC Press, 1st Edition, Boca Raton, FL.

Alavi, A.H., Buttlar, W.G., (2019). An overview of smartphone technology for citizen-centered, real-time and scalable civil infrastructure monitoring, Future Generation Computer Systems, 93:651-672.

Buttlar, W.G., Alavi, A., Brown, H., Sills, H., Mesa, A., and Okenfuss, E. (2018). Pavement Roughness Measurement Using Android Smartphones: Case Study of Missouri Roads and Airports. Report #TR201709. Missouri Department of Transportation (MoDOT), Jefferson City, MO.

ASCE (2017). A Comprehensive Assessment of America’s Infrastructure. 2017 Report Card for Amirica's Infrastructure, American Society of Civil Engineers (ASCE), Reston, VA.

Frost & Sullivan, (2013). Strategic Opportunity Analysis of the Global Smart City Market. Report M920-01, San Antonio, TX.

Jiang M., McGill W. L., (2010). Human-Centered Sensing for Crisis Response and Management Analysis Campaigns. In Proceedings of the 7th International Conference on Information Systems for Crisis Response and Management.

 

Civil Infrastructure (Big) Data Mining

The operation and maintenance of civil engineering systems are now undergoing noticeable transformation as a result of huge amount of information provided by emerging testing and monitoring systems. Evidently, the main concern of the I/SHM community is not the lack of data but rather how to deal with the large amounts of data generated during projects. The key role of data mining techniques in this transformation is well-understood. Data mining is a multi-disciplinary field including variety of techniques such as statistical analysis, optimization, machine learning, pattern recognition, artificial intelligence (AI) and database management. One of the missions of the Pitt’s iSMaRT group is measuring, acquiring, processing, and analyzing the massive amount of data obtained from civil infrastructure projects such as pavement conditions, roadway feature inventory, bridge maintenance, road characteristics inventory, etc. throughout the state. The next major goal is to extract the useful information from sensor data for long-term condition assessment of the monitored structures. We are interested in exploring the fairly new concept of “Big Data Analytics” for the interpretation of civil infrastructure massive data (see Figure 5). Despite the significance of the Big Data approach for the analysis of modern large-scale data, there is no serious attempt in the literature on this topic. Big Data Analytics will not only improve our ability to extract knowledge and insights from large and complex collections of data, but also helps accelerate development of Smart Cities in US. The intent of our team is to serve as a pioneering organization in this field from different perspectives such as research and infrastructure development, and education and workforce development.

Figure 5. Data stream processing and Big Data Analytics for smart cities at Pitt’s iSMaRT group


PUBLICATIONS

Citations: > 8,000; h-index: 45; Link: Google Scholar

 

Books

Alavi A.H., Buttlar W.G., “Data Analytics Applications for Smart Cities”, Taylor & Francis, New York, NY, 2018. [ISBN: 978-113-83-0877-0]

Rajsingh E.B., Veerasamy J., Alavi A.H., Peter J.D., “Advances in Big Data and Cloud Computing”, Springer Nature, Singapore, 2018. [ISBN: 978-981-10-7199-7]

Gandomi A.H., Alavi A.H., Ryan C., “Handbook of Genetic Programming Applications”, 665 pages, Springer, Switzerland, 2015. [ISBN: 978-3-319-20882-4]

Yang X.S., Gandomi A.H., Talatahari S., Alavi A.H., “Metaheuristics in Water Resources, Geotechnical and Transportation Engineering”, 496 pages, Elsevier, Waltham, MA, USA, 2012. [ISBN: 9780123982964]

Gandomi A.H., Yang X.S., Talatahari S., Alavi A.H., “Metaheuristic Applications in Structures and Infrastructures”, 430 pages, Elsevier, Waltham, MA, USA, 2013. [ISBN: 9780123983640]

 

Edited Special Issues

Alavi A.H., Buttlar W.G., Golparvar-Fard M., “Special Issue on Smart Infrastructure, Construction and Building Internet of Things (SICB-IoT)”, Automation in Construction, Elsevier, 2017.

Gandomi A.H., Alavi A.H., “Special Issue on Metaheuristics in Reliability and Risk Analysis”, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems: Part A, 2018.

Alavi A.H., Blessing E., Dinesh Peter J., “Special Issue on Big-Data and Cloud Technologies”, Elsevier Computers and Electrical Engineering, Elsevier, 2017.

Alavi A.H., Gandomi A.H., “Special Issue on Big Data in Civil Engineering”, Automation in Construction, Elsevier, 2016.

Alavi A.H., Gandomi A.H., Lary D., “Special Issue on Progress of Machine Learning in Geosciences”, Geoscience Frontiers, Elsevier, 2015.

Talatahari S., Singh V.P., Alavi A.H., Kang F., “Special Issue on Soft Computing Methods in Civil Engineering”, The Scientific World Journal, Hindawi, 2015.

Talatahari S., Chen S., Gandomi A.H., Alavi A.H., “Special Issue on Advances of Artificial Intelligence in Mechanical Engineering”, Advances in Mechanical Engineering, SAGE, 2014.

 

Selected Journal Papers

2019

Alavi A.H., Buttlar W.G., "An overview of smartphone technology for citizen-centered, real-time and scalable civil infrastructure monitoring", Future Generation Computer Systems, 93:651-672, 2019.

Jiao P., Alavi A.H., " Size-dependent buckling instability and recovery of beam-like, architected microstructures", Materials & Design, 162, 405-417, 2019.

Jiao P., Borchani W., Alavi A.H., Lajnef N., " Small and large deformation models of post-buckled beams under lateral constraints", Mathematics and Mechanics of Solids, 24 (2), 386-405, 2019.

Majidifard H., Jahangiri B., Buttlar W.G., Alavi A.H., " New machine learning-based prediction models for fracture energy of asphalt mixtures", Measurement, 135, 438-451, 2019.

Mirzahosseini M., Jiao P., Barri K., Riding K.A., Alavi A.H., " New machine learning prediction models for compressive strength of concrete modified with glass cullet", Engineering Computations, 36 (3), 876-898, 2019.

Jiao P., Roy M., Barri K., Zhu R., Ray I., Alavi A.H., " High-performance fiber reinforced concrete as a repairing material to normal concrete structures: Experiments, numerical simulations and a machine learning-based prediction model", Construction and Building Materials 223, 1167-1181, 2019.

 

2018

Alavi A.H., Jiao P., Buttlar W.G., Lajnef N., “Internet of Things-Enabled Smart Cities: State-of-the-Art and Future Trends”, Measurement 129, 589-606, 2018.

Jiao P., Borchani W., Alavi A.H., Lajnef N., "Micro-Composite Films Constrained by Irregularly Bilateral Walls: A Size-Dependent Post-Buckling Analysis", Composite Structures, in press, 2018.

Jiao P., Borchani W., Alavi A.H., Hasni H., Lajnef N., "An Energy Harvesting and Damage Sensing Solution Based on Post-Buckling Response of Non-Uniform Cross-Section Beams", Structural Control and Health Monitoring, 25:e2052, 2018.

Hasni H., Jiao P., Alavi A.H., Lajnef N., Masri S.F., "Structural Health Monitoring of Steel Frames Using a Network of Self-powered Strain and Acceleration Sensors: A Numerical Study", Automation in Construction, 85, 344-357, 2018.

Hasni H., Jiao P., Lajnef N., Alavi A.H., "Damage Localization and Quantification in Gusset Plates: A Battery‐Free Sensing Approach", Structural Control and Health Monitoring, in press, 2018.

 

2017

Alavi A.H., Hasni H., Jiao P., Borchani W., Lajnef N., “Fatigue Cracking Detection in Steel Bridge Girders through a Self-Powered Sensing Concept”, Journal of Constructional Steel Research, 128, 19–38, 2017.

Hasni H., Alavi A.H., Lajnef N., Abdelbarr M., Masri S.F., Chakrabartty S., Self-Powered Piezo-Floating-Gate Sensors for Health Monitoring of Steel Plates, Engineering Structures, 148, 584-601, 2017. DOI: Link

Hasni H., Alavi A.H., Jiao P., Lajnef N., “Detection of Fatigue Cracking in Steel Bridge Girders: A Support Vector Machine Approach”, Archives of Civil and Mechanical Engineering, 17(3), 609-622, 2017.

Hasni H., Alavi A.H., Chatti K., Lajnef N., “A Self-Powered Surface Sensing Approach for Detection of Bottom-Up Cracking in Asphalt Concrete Pavements: Theoretical/Numerical Modeling”, Construction and Building Materials, 144, 728–746, 2017.

Wang G., Gandomi A. H., Alavi A. H., A Comprehensive Review of Krill Herd Algorithm: Variants, Hybrids and Applications" Artificial Intelligence Review, 1-30, 2017.

 

2016

Alavi A.H., Hasni H., Lajnef N., Chatti K., Faridazar F., “An Intelligent Structural Damage Detection Approach Based on Self-Powered Wireless Sensor Data”, Automation in Construction, 62: 24–44, 2016.

Alavi A.H., Hasni H., Lajnef N., Chatti K., Faridazar F., “Damage Detection Using Self-Powered Wireless Sensor Data: An Evolutionary Approach”, Measurement, 82, 254–283, 2016.

Alavi A.H., Hasni H., Lajnef N., Chatti K., Faridazar F., “Continuous Health Monitoring of Pavement Systems Using Smart Sensing Technology”, Construction and Building Materials, 114, 719–736, 2016.

Alavi A.H., Hasni H., Lajnef N., Chatti K., “Damage Growth Detection in Steel Plates: Numerical and Experimental Studies”, Engineering Structures, 128, 124–138, 2016.

Alavi A.H., Gandomi A.H., Lary D.J., “Progress of Machine Learning in Geosciences”, Geoscience Frontiers, Elsevier, 7 (1): 1-2, 2016.

Jiao, P., Borchani, W., Hasni, H., Alavi, A.H. and Lajnef, N. Post-Buckling Response of Non-Uniform Cross-Section Bilaterally Constrained Beams. Mechanics Research Communications, 78: 42-50.

Alavi A.H., Sadrossadat E., “New Design Equations for Estimation of Ultimate Bearing Capacity of Shallow Foundations Resting on Rock Masses”, Geoscience Frontiers, 7 (1), 91-99, 2016.

Lary D.J., Alavi A.H., Gandomi A.H., Walker A.L., “Machine Learning in Geosciences and Remote Sensing”, Geoscience Frontiers, Elsevier, 7 (1): 3-10, 2016.

Gandomi A.H., Alavi A.H., Kazemi S., Arjmandi P., “Formulation of Shear Strength of Slender RC Beams Using Gene Expression Programming. Part II: with Shear Reinforcement.” Measurement, Elsevier, 95, 367-376, 2016.

Wang G., Gandomi A. H., Alavi A. H., “Chaotic Cuckoo Search” Soft Computing, Springer, 20 (9), 3349-3362, 2016.

 

2015

Mirzahosseini M.R., Najjar Y.M., Alavi A.H., Gandomi A.H., “Next-Generation Models for Evaluation of Flow Number of Asphalt Mixtures”, International Journal of Geomechanics, 15(6): 04015009, 2015.

Shahnazari H., Dehnavi Y., Alavi A.H., “The Next-Generation Constitutive Correlations for Simulation of Cyclic Stress-Strain Behavior of Sand.” Journal of Civil Engineering and Management, 21: 31-44, 2015.

Sarveghadi M., Gandomi A.H., Bolandi H., Alavi A.H., “Development of prediction models for shear strength of SFRCB using a machine learning approach.” Neural Computing & Applications, 1-10, 2015.

 

2014

Wang G., Gandomi A. H., Alavi A.H., “An Effective Krill Herd Algorithm with Migration Operator in Biogeography-based Optimization,” Applied Mathematical Modelling, 38(9–10), 2454–2462, 2014.

Wang G., Gandomi A. H., Yang X.S., Alavi A. H., “A Novel Improved Accelerated Particle Swarm Optimization Algorithm for Global Numerical Optimization,” Engineering Computations, 31(7), 1198-1220, 2014.

Gandomi A.H., Alavi A.H., Kazemi S., Gandomi M., “Formulation of Shear Strength of Slender RC Beams Using Gene Expression Programming. Part I: without Shear Reinforcement”, Automation in Construction, 42, 112–121, 2014.

Gandomi A.H., Mohammadzadeh D., Pérez JL. Alavi A.H., “Linear Genetic Programming for Shear Strength Prediction of Reinforced Concrete Beams without Stirrups”, Applied Soft Computing, 19: 112–120, 2014.

Wang G., Gandomi A. H., Alavi A.H., “An Effective Krill Herd Algorithm with Migration Operator in Biogeography-based Optimization,” Applied Mathematical Modelling, 38(9–10), 2454–2462, 2014.

Wang G., Gandomi A.H., Alavi A.H., “Stud Krill Herd Algorithm”, Neurocomputing, Elsevier, 128(27), 363-370, 2014.

 

2013

Gandomi A.H., Yang X.S., Talatahari S., Alavi A.H., “Firefly Algorithm with Chaos”, Communications in Nonlinear Science and Numerical Simulation, 18(1): 89–98, 2013.

Alavi A.H., Gandomi A.H., Chahkandi Nejad H., Mollahasani A., Rashed A. “Design equations for prediction of pressuremeter soil deformation moduli utilizing expression programming systems.” Neural Computing & Applications, Springer, 23(6), 1771-1786, 2013.

Gandomi A.H., Yang X.S., Alavi A.H., “Cuckoo Search Algorithm: A Metaheuristic Approach to Solve Structural Optimization Problems”, Engineering with Computers, 29(1), 17-35, 2013.

Gandomi A.H., Alavi A.H., Mohamadzadeh S.D., Sahab M.G., “An Empirical Model for Shear Capacity of RC Deep Beams Using Genetic-Simulated Annealing”, Archives of Civil and Mechanical Engineering, 13(3): 354–369, 2013.

Babanajad S.K., Gandomi A.H., Mohammadzadeh S.D., Alavi A.H., “Numerical Modeling of Concrete Strength under Multiaxial Confinement Pressures Using Linear Genetic Programming”, Automation in Construction, 36, 136-144, 2013.

Gandomi A.H., Alavi A.H., Asghari A. Niroomand H., Matin Nazar., A., “An Innovative Approach for Modeling of Hysteretic Energy Demand in Steel Moment Resisting Frames”, Neural Computing & Applications, Springer, 2013, in press. DOI: Link

Gandomi A.H., Yun G.J., Alavi A.H., “An evolutionary approach for modeling of shear strength of RC deep beams”, Materials and Structures, Springer, 2013, in press.

 

2012

Alavi A.H., Gandomi A.H., “Energy-Based Models for Assessment of Soil Liquefaction”, Geoscience Frontiers, Elsevier, 3(4): 541-555, 2012.

Gandomi A.H., Alavi A.H., “Krill Herd Algorithm: A New Bio-Inspired Optimization Algorithm”, Communications in Nonlinear Science and Numerical Simulation, 17(12): 4831–4845, 2012.

Rashed A., Bolouri Bazaz J., Alavi A.H., “Nonlinear Modeling of Soil Deformation Modulus through LGP-Based Interpretation of Pressuremeter Test Results”, Engineering Applications of Artificial Intelligence, 25(7): 1437-1449, 2012.

Alavi A.H., Mollahasani A., Gandomi A.H., Bolouri Bazaz J., “Formulation of Secant and Reloading Soil Deformation Moduli Using Multi Expression Programming”, International Journal for Computer-Aided Engineering and Software-Engineering Computations, 29(2), 173-197, 2012.

Gandomi A.H., Babanajad S.K., Alavi A.H., Farnam Y., “Novel Approach to Strength Modeling of Concrete under Triaxial Compression”, Journal of Materials in Civil Engineering, ASCE, 24 (9): 1132–1143, 2012.

Alavi A.H., Gandomi A.H., Mousavi S.M., “Discussion on Prediction of Shear Strength Parameters of Soils Using Artificial Neural Networks and Multivariate Regression Methods”, Engineering Geology, 137–138: 107–108, 2012.

Alavi A.H., Gandomi A.H., “Discussion on Models to Predict the Deformation Modulus and the Coefficient of Subgrade Reaction for Earth Filling Structures”, Advances in Engineering Software, 52: 44–46, 2012.

 

2011

Mollahasani A., Alavi A.H., Gandomi A.H., “Empirical Modeling of Plate Load Test Moduli of Soil via Gene Expression Programming”, Computers and Geotechnics, Elsevier, 38(2): 281-286, 2011.

Alavi A.H., Gandomi A.H., Modaresnezhad M., Mousavi M., “New Ground-Motion Prediction Equations Using Multi Expression Programming”, Journal of Earthquake Engineering, 15(4): 511–536, 2011.

Alavi A.H., Ameri M., Gandomi A.H., Mirzahosseini M.R., “Formulation of Flow Number of Asphalt Mixes Using a Hybrid Computational Method”, Construction and Building Materials, 25(3): 1338–1355, 2011.

Alavi A.H., Gandomi A.H., “Prediction of Principal Ground-Motion Parameters Using a Hybrid Method Coupling Artificial Neural Networks and Simulated Annealing”, Computers and Structures, Elsevier, 89 (23-24): 2176-2194, 2011.

Gandomi A.H., Yang X.S., Alavi A.H., “Mixed Variable Structural Optimization Using Firefly Algorithm”, Computers and Structures, 89(23-24): 2325-2336 2011.

Alavi A.H., Aminian P., Gandomi A.H., Arab Esmaeili M., “Genetic-Based Modeling of Uplift Capacity of Suction Caissons”, Expert Systems with Applications, Elsevier, 38(10): 12608-12618, 2011.

Alavi A.H., Gandomi A.H., “A Robust Data Mining Approach for Formulation of Geotechnical Engineering Systems”, International Journal for Computer-Aided Engineering and Software-Engineering Computations, 28(3): 242-274, 2011.

Gandomi A.H., Alavi A.H., Mirzahosseini M.R., Moghadas Nejad F., “Nonlinear Genetic-Based Models for Prediction of Flow Number of Asphalt Mixtures”, Journal of Materials in Civil Engineering, ASCE, 23(3): 248–263, 2011.

Mousavi S.M., Alavi A.H., Gandomi A.H., Mollahasani A., “A Hybrid Computational Approach to Formulate Soil Deformation Moduli Obtained from PLT”, Engineering Geology, 123: 324-332, 2011.

Gandomi A.H., Alavi A.H., “Multi-Stage Genetic Programming: A New Strategy to Nonlinear System Modeling”, Information Sciences, 181(23): 5227-5239, 2011.

Gandomi A.H., Alavi A.H., Mousavi M., Tabatabaei S.M. “A Hybrid Computational Approach to Derive New Ground-Motion Attenuation Models”, Engineering Applications of Artificial Intelligence, 24(4): 717–732, 2011.

Mirzahosseini M.R., Aghaeifar A., Alavi A.H., Gandomi A.H., Seyednour, M., “Permanent Deformation Analysis of Asphalt Mixtures Using Soft Computing Techniques”, Expert Systems with Applications, Elsevier, 38(5): 6081–6100, 2011.

 

2010

Alavi A.H., Gandomi A.H., Sahab M.G., Gandomi M., “Multi Expression Programming: A New Approach to Formulation of Soil Classification”, Engineering with Computers, 26(2): 111-118, 2010.

Alavi A.H., Gandomi A.H., Mollahasani A., Heshmati A.A.R., Rashed A., “Modeling of Maximum Dry Density and Optimum Moisture Content of Stabilized Soil Using Artificial Neural Networks”, Journal of Plant Nutrition and Soil Science, Wiley-VCH, 173(3): 368-379, 2010.

Alavi A.H., Gandomi A.H., Mousavi M., Mollahasani A., “High-Precision Modeling of Uplift Capacity of Suction Caissons Using a Hybrid Computational Method”, Geomechanics and Engineering, 2(4): 253-280, 2010. PDF Link

Mousavi S.M., Gandomi A.H., Alavi A.H., Vesalimahmood M., “Modeling of Compressive Strength of HPC Mixes Using a Combined Algorithm of Genetic Programming and Orthogonal Least Squares”, Structural Engineering and Mechanics, 36(2), 225-241, 2010. PDF Link

Mousavi S.M., Alavi A.H., Gandomi A.H., Arab Esmaeili M., Gandomi M., “A Data Mining Approach to Compressive Strength of CFRP Confined Concrete Cylinders”, Structural Engineering and Mechanics, 36(6), 2010. PDF Link

Shahnazari H., Dehnavi Y., Alavi A.H., “Numerical Modeling of Stress-Strain Behavior of Sand under Cyclic Loading”, Engineering Geology, 116(1-2): 53-72, 2010.

Gandomi A.H., Alavi A.H., Sahab M.G., “New Formulation for Compressive Strength of CFRP Confined Concrete Cylinders Using Linear Genetic Programming”, Materials and Structures, 43(7): 963-983, 2010.

Gandomi A.H., Alavi A.H., Sahab M.G., Arjmandi P., “Formulation of Elastic Modulus of Concrete Using Linear Genetic Programming”, Journal of Mechanical Science and Technology, 24(6): 1011-1017, 2010.

Alavi A.H., Gandomi A.H. Heshmati A.A.R., “Discussion on Soft computing approach for real-time estimation of missing wave heights”, Ocean Engineering, 37(13): 1239-1240, 2010.

Alavi A.H., Gandomi A.H., Gandomi M., “Comment on Genetic Programming Approach for Flood Routing in Natural Channels”, Hydrological Processes, 24(6): 798-799, 2010.

 

2009

Gandomi A.H., Alavi A.H., Kazemi S., Alinia M.M., “Behavior Appraisal of Steel Semi-Rigid Joints Using Linear Genetic Programming.” Journal of Constructional Steel Research, Elsevier, 65: 1738-1750, 2009.

Heshmati A.A.R., Alavi A.H., Keramati M., Gandomi A.H., “A Radial Basis Function Neural Network Approach for Compressive Strength Prediction of Stabilized Soil”, Geotechnical Special Publication, ASCE, No. 191: 147-153, 2009. PDF Link

Alavi A.H., Gandomi A.H., Gandomi M., Sadat Hosseini S.S., “Prediction of Maximum Dry Density and Optimum Moisture Content of Stabilized Soil Using RBF Neural Networks”, The IES Journal Part A: Civil & Structural Engineering, 2(2): 98-106, 2009. Link

Gandomi A.H., Alavi A.H., “Discussion on Predicting the Shear Strength of Reinforced Concrete Beams Using Artificial Neural Networks”, Engineering Structures, 31(11): 2801, 2009.

Chapters in Book

Gandomi A.H., Alavi A.H., Talatahari S., “Structural Optimization using Krill Herd Algorithm” Swarm Intelligence and Bio-Inspired Computation: Theory and Applications, XS Yang et al., Elsevier, Chapter 15, 335-350, 2013. PDF Link

Gandomi A.H., Alavi A.H., “Expression Programming Techniques for Formulation of Structural Engineering Systems” Metaheuristic Applications in Structures and Infrastructures, AH Gandomi et al. (Eds.), Elsevier, Chapter 18, 437-454, 2013.

Alavi A.H., Gandomi A.H., Mollahasani A., Bolouri J., “Linear and Tree-Based Genetic Programming for Solving Geotechnical Engineering Problems” Metaheuristics in Water Resources, Geotechnical and Transportation Engineering, XS Yang et al. (Eds.), Elsevier, Chapter 12, 289-310, 2012.

Gandomi A.H., Alavi A.H., “Applications of Computational Intelligence in Behavior Simulation of Concrete Materials”, Chapter 9 in Computational Optimization and Applications in Engineering and Industry, XS Yang & S Koziel (Eds.), Springer, Studies in Computational Intelligence, 359, 221-243, 2011.

Alavi A.H., Gandomi A.H., Mollahasani A., “A Genetic Programming-Based Approach for Performance Characteristics Assessment of Stabilized Soil”, Variants of Evolutionary Algorithms for Real-World Applications, Springer-Verlag, Berlin, Chapter 9, 343-375, 2011.

 

Conference Papers

Alavi A.H., Hasni H., Jiao P., Aono K., Lajnef N., Chakrabartty S., " Self-charging and self-monitoring smart civil infrastructure systems: current practice and future trends", SPIE Smart Structures + Nondestructive Evaluation, 2019, Denver, Colorado, 2019.

Jiao P., Lu K., Hasni H., Alavi A.H., Al-Ansari A.M., Lajnef N., " A multistable mechanism to detect thermal limits for structural health monitoring", SPIE Smart Structures + Nondestructive Evaluation, 2019, Denver, Colorado, 2019.

Alavi, A.H., Hasni, H., Jiao, P. and Lajnef, N., “Structural Health Monitoring Using a Hybrid Network of Self-Powered Accelerometer and Strain Sensors”, In: American Professional Society of Photographic Instrumentation Engineers (SPIE), Smart Structures/NDE, Portland, Oregon, 2017.

Hasni, H., Alavi, A.H., Jiao, P., Lajnef, N., “A New Method for Detection of Fatigue Cracking in Steel Bridge Girders Using Self-Powered Wireless Sensors”, In: American Professional Society of Photographic Instrumentation Engineers (SPIE), Smart Structures/NDE, Portland, Oregon, 2017.

Jiao, P., Borchani, W., Hasni, H., Alavi, A.H., Lajnef, N., “A Buckling-Based Mechanism for Energy Harvesting and Structural Damage Sensing”, In: American Professional Society of Photographic Instrumentation Engineers (SPIE), Smart Structures/NDE, Portland, Oregon, 2017.

Chatti K., Alavi A.H., Hasni H., Lajnef N., Faridazar F., “Self-Powered Sensors for Detection of Damage in Pavement Structures”, In: 8th Rilem International Conference on Mechanisms of Cracking and Debonding in Pavements (MCD2016), Nantes, France, 2015.

Alavi A.H., Hasni H., Lajnef N., Chatti K., Faridazar F., “A Novel Self-Powered Approach for Structural Health Monitoring”, In: 1st International Conference on Sustainable Mobility Applications, Renewables and Technology (SMART2015), Kuwait, 2015.

Mirzahosseini M.R., Najjar Y.M., Alavi A.H., Gandomi A.H., “ANN-Based Prediction Model for Rutting Propensity of Asphalt Mixtures”, In Proceedings of the 92nd Transportation Research Board (TRB) Annual Meeting, Washington, D.C., Paper No. 13-2180, 2013.

Sadrossadat E., Soltani F., Marandi S.M., Alavi A.H., “A New Nonlinear Model for the Prediction of Ultimate Bearing Capacity of Shallow Foundations on Granular Soils”, In Proceedings of the 9th International Congress on Civil Engineering, Isfahan University of Technology, Isfahan, Iran, 2012.

Mollahasani A., Alavi A.H., Gandomi A.H., Bolouri Bazaz J., “Deriving Prediction Models for Soil Deformation Modulus Based on PLT Results”, “, In Proceedings of the 9th International Symposium on Computational Civil Engineering, New Approaches in Numerical Analysis in Civil Engineering, Romania, p. 53-61, 2011.

Alavi A.H., Gandomi A.H., Mollahasani A., Rashed A., “Nonlinear Modeling of Soil Cohesion Intercept Using Generalized Regression Neural Network”, In Proceedings of the 8th International Symposium on Computational Civil Engineering, New Computational Concepts in Civil Engineering, Romania, p. 69-86, 2010.

Alavi A.H., Gandomi A.H., “Nonlinear Modeling of Liquefaction Behavior of Sand-Silt Mixtures in terms of Strain Energy”, In Proceedings of the 8th International Symposium on Highway and Bridge Engineering, Technology and Innovation in Transportation Infrastructure, Romania, p. 50-69, 2010.

Mirzahosseini M.R., Alavi A.H., Moghadas Nejad F., Gandomi A.H., Ameri M., “Evaluation of Rutting Potential of Asphalt Mixtures Using Linear Genetic Programming”, In Proceedings of the 11th International Conference on Asphalt Pavements (ISAP2010), Nagoya, Japan, Paper ID. 90316, 2010.

Heshmati A.A.R., Sahab M.G., Alavi A.H., Gandomi A.H., “Soil Classification Using a Combined Algorithm of Simulated Annealing and Genetic Programming”, In Proceedings of the 8th International Congress on Civil Engineering, Iran, Paper No. G0273, 2009.

Alavi A.H., Heshmati A.A.R., Gandomi A.H., Askarinejad A., Mirjalili M., “Utilisation of Computational Intelligence Techniques for Stabilised Soil”, In Proceedings of the 6th International Conference on Engineering Computational Technology, Civil-Comp Press, United Kingdom, Paper No. 175, 2008.

Alavi A.H., Heshmati A.A.R., Salehzadeh H., Gandomi A.H., Askarinejad A., “Soft Computing Based Approaches for High Performance Concrete”, In Proceedings of the 6th International Conference on Engineering Computational Technology, Civil-Comp Press, United Kingdom, Paper No. 86, 2008.

Moradi M., Alavi A.H., Pashabavandpour M.A., Gandomi A.H., Askarinejad A., “Soft Computing-Based approaches for the Prediction of Compressive Strength of Lime-Microsilica Stabilized Clayey Soils”, In Proceedings of the 6th International Symposium on Computational Civil Engineering, Computational Models for Civil Engineering, Romania, p. 350-365, 2008.

Gandomi A.H., Alavi A.H., Sahab M.G., Gandomi M., Safari Gorji M., “Empirical Models for the Prediction of Flexural Resistance and Initial Stiffness of Welded Beam-Column Joints”, In Proceedings of the 11th East Asia-Pacific Conference on Structural Engineering & Construction, Taiwan, Paper No. 320, 2008.

Services

Editor/Guest Editor

•  Editor, Sensors Journal, MDPI (IF = 3.031)

•  Editor, International Journal of Bio-Inspired Computation, Inderscience (IF = 3.395)

•  Editor, Case Studies in Construction Material, Elsevier

•  Associate Editor, The Journal of Engineering, The Institution of Engineering and Technology (IET)

•  Editor, Cogent Engineering, Taylor & Francis

•  Editor, International Journal of Big Data Intelligence, Inderscience

•  Editor, Smart Cities Journal, MDPI

•  Editor, Inventions Journal, MDPI

•  Editor, Technologies Journal, MDPI

•  Guest Editor, Automation in Construction, Elsevier (IF = 4.313)

•  Guest Editor, Geoscience Frontiers, Elsevier (IF = 4.160)

•  Guest Editor, Advances in Mechanical Engineering, Sage (IF = 1.024)

•  Guest Editor, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems: Part A, ASCE

 

Review Panel

•  Proposal Review Panel:

- The National Academies of Sciences, Engineering, and Medicine (The Academies), Washington, DC.

- Science Foundation Ireland (SFI), Dublin, Ireland.

- National Center for Science and Technology Evaluation (NCSTE), Ministry of Education and Science, Republic of Kazakhstan.

 

•  Regular Reviewer for Elsevier, Springer, ASCE, Wiley, Taylor & Francis, etc, including:

- 16 Elsevier journals (e.g. Construction and Building Materials, Sensors and Actuators, Journal of Sound and Vibration, Automation in Construction, Engineering Applications of Artificial Intelligence, Applied Mathematics and Computation);

- 14 Springer journals (e.g. Neural Computing and Applications, Soft Computing, Energy Efficiency, Natural Hazards, Journal of Supercomputing, Bulletin of Earthquake Engineering);

- 5 Taylor & Francis journals (e.g. Journal of Earthquake Engineering, Road Materials and Pavement Design);

- 3 Techno Press journals (Smart Structures and Systems, Computers and Concrete, Earthquakes and Structures);

- 2 IEEE journal (IEEE Computational Intelligence MagazineIEEE Transactions on Services Computing); 

- 1 Wiley journal (Journal of Forecasting);

- 2 ASCE journal (Journal of Computing in Civil Engineering, Journal of Transportation Engineering);

- Several journals from other publishers including Sage, Emerald, and ICE, Inderscience.

 

Membership in Professional Societies/Committees

•  American Society of Civil Engineers (ASCE)

•  The Institute of Electrical and Electronics Engineers (IEEE)

•  World Federation on Soft Computing (WFSC)

•  Member, BEACON:  The NSF Science and Technology Center for the Study of Evolution in Action

•  Organizing Committee Member and Invited Speaker, The 3rd International Conference on Computer Science & Cloud Computing (ICCSCC-2020), Montreal, Canada, 2020.

•  Organizing Committee Member and Invited Speaker, International Conference and Expo on Infrastructure and Construction, Session “Advance Methods for Sustainable Infrastructure and Constructions”, Kuala Lumpur, Malaysia, 2020.

•  Technical Program Committee, International Symposium on Pavement, Roadway, and Bridge Life Cycle Assessment 2020 (LCA 2020), Sacramento, California, 2020.

•  Technical Program Committee, The 3rd International Conference on Big Data and Education (ICBDE 2020), Imperial College, London, UK, 2020.

•  Technical Program Committee, The 4th International Conference on Internet of Things, Big Data and Security (IoTBDS 2020), Prague, Czech Republic, 2020.

•  Publicity Chair, The 12th International Conference on Computer Research and Development (ICCRD 2020), Haiphong City, Vietnam.

•  Publicity Chair, The 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020), Haiphong City, Vietnam.

•  Session Chair (Mechanical Metamaterials), The 7th International Conference on Smart Materials and Nanotechnology in Engineering (SMN2019), Harbin, China, 2019.

•  Technical Program Committee, International Conference on Internet of Things and Big Data (IoTBD 2019), Crete, Greece, 2019.

•  Technical Program Committee, The International Conference on Big Data and Smart City (ICBDSC 2019), Bali, Indonesia, 2019.

•  Technical Program Committee, The 6th International Conference on Big Data and Smart Computing (IEEE BigComp 2019), Kyoto, Japan, 2019.

•  Technical Program Committee, International Conference on Mathematics and Artificial Intelligence (ICMAI 2019), Chengdu, China, 2019.

•  Technical Program Committee, The 8th International Conference on Big Data & Data Science, Barcelona, Spain, 2019.

•  Technical Program Committee, The 8th IEEE International Symposium on Cloud and Services Computing (SC2 2018), Paris, France, 2018.

•  Special Session Organizer, The 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2019), Crete, Greece, 2019.

•  Program Chair, The 7th IEEE International Symposium on Cloud and Services Computing (SC2 2017), Kanazawa, Japan, 2017.

•  Technical Program Committee, International Conference on Sustainable Energy and Environment Sensing (SEES 2018), Cambridge, UK, 2018.

•  Technical Program Committee, International Conference on Mathematics and Artificial Intelligence (ICMAI 2018), Chengdu, China, 2018.

•  Program Chair, 2nd Int. Conference on Frontiers of Sensors Technologies (ICFST 2017), Shenzhen, China, 2017.

•  Publication Chair, Int. Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI17), Hong Kong, 2017.

•  Program Chair, Int. Conference on Big-Data and Cloud Computing (ICBDCC), Tamilnadu, India, 2017, 2018.

•  Technical Program Committee, The 4th Int. Conference on Big Data and Smart Computing (BigComp 2017), Jeju, Korea, 2017.

•  Publication Chair, 2nd IEEE Int. Conference on Big Data Intelligence and Computing (IEEE DataCom 2016), Auckland, New Zealand, 2016.

•  Technical Program Committee, 3rd Int. Conference on Big Data and Smart Computing (BigComp 2016), Hong Kong, China, 2016.

•  Technical Program Committee, 3rd IEEE Int. Conference on Big Data and Smart City (ICBDSC 2016), Muscat, Oman, 2016.

•  Technical Program Committee, 2016 IEEE Int. Conference on Big Data Analysis (ICBDA 2016), Hangzhou, China, 2016.

•  Technical Program Committee, 2nd Int. Conference on Big Data & Analytics for Business, New Delhi, India, 2016.

•  Technical Program Committee, 2nd Workshop on Big Data and Data Mining Challenges on IoT and Pervasive Systems (BigD2M 2016), Madrid, Spain, 2016.

•  Scientific Committee, The 15th EU/ME (the European Metaheuristics Community) Workshop, Istanbul, Turkey, 2014.

•  Scientific Committee, The Int. Student Competition in Structural Optimization (ISCSO), Istanbul, Turkey, 2012, 2013, 2015.

•  Scientific Committee, Int. Conference on Soft Computing & Machine Intelligence (ISCMI), New Delhi, India, 2014, 2015.

•  Scientific Committee, Int. Symposium on Computational & Business Intelligence (ISCBI15), New Delhi, India, 2014, 2015.

• Technical Program Committee, The 3rd Int. Conference on Consumer Electronics, Communications and Networks (CECNet 2013), Xianning, China, 2013.



Contact


Amir H. Alavi, PhD
Swanson School of Engineering
Department of Civil and Environmental Engineering
University of Pittsburgh

 

Address: 209 Benedum Hall, 3700 O'Hara Street, Pittsburgh, PA 15261, USA.

Phone: +1 (412) 648-4385

Fax: +1 (412) 624-0135

Email: alavi@pitt.edu

 

© 2019 Amir H. Alavi. All rights reserved.