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Korkut

Kaynardag

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Research 

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Education

Education

The University of Texas at Austin (2016 to present)

Ph.D. in Civil Engineering

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Bogazici University (2013 to 2016)

M.Sc. in Civil Engineering

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Bogazici University (2008-2013)

B.Sc. in Civil Engineering

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Czech Technical University (2012 Fall)

Exchange semester 

Technical Interests and Skill

Experience

  • Lead Data and System Engineer in Graduate Research Assistant Rile- The University of Texas at Austin (2016 to present)

  • To detect defects (outliers) in railway tracks at higher speeds, designed and developed a non-contact laser sensor-based predictive maintenance system framework using vibration and acoustic data.

  • Decreased cost by 40% and increased speed by 25%.

  • Developed noise reduction and data cleaning algorithms: supervised learning, artificial neural networks (semi-organizing maps), time-series methods, wavelets, signal smoothing algorithms, and bilinear interpolation for noise signal detection/noise-free signal estimation.

  • Applied hypothesis testing and multivariate statistical methods combined with transfer function-based system identification methods to enhance anomaly detection and defect classification.

  • Integrated an LSTM autoencoder deep-learning anomaly detection approach with feature selection (TensorFlow) to the framework.

  • Parametrically tested different signal processing and system identification methods to improve noise reduction.

  • Developed numeric computational models (acoustic wave propagation simulations), and integrated them with experimental data to simulate the developed predictive maintenance system.

  • Collaborated to develop analytical transfer function-based methods to compute the attenuation and propagation zones of acoustic wave modes in continuous periodically supported solid (i.e., rail).

  • Carried out novel speckle noise tests for Laser Doppler vibrometers.

  • Carried out laboratory and field testing of the system.

  • Prepared 11 journals (5 published, 6 in submission), 2 of which are on deep learning, gave 5 conference presentations and 1 invited talk.

  • Data and System Engineer in Graduate Research Assistant Role - Bogazici University (2013 to 2016)

  • Applied noise reduction, signal processing, and system identification methods to vibration signals for condition monitoring and predictive maintenance of a tall building, a wind turbine, a suspension bridge (1560 meters long), a masonry building, and 13 masonry bridges.

  • Applied convex-optimization-based model updating methods to enhance the model predictability of engineering structures’ simulations as well as probabilistic methods for reliability estimation.

  • Carried out dynamic and seismic assessments through analytical methods as well as FEM simulations.

  • Developed a real-time remote sensing and automated dashboard.

  • Published 1 journal and made 4 conference presentations.

Additional Machine Learning Projects

  • Vehicle price prediction: Applied linear regression models with different regularization approaches as well as XGBoost regression on Python to predict vehicle prices.  

  • Bank account fraud detection: highly imbalanced dataset, created a pipeline using supervised models (KNN, support vector machines, random forest, ADA boost, and XGBoost) and improved detection performance using stacking and up/down sampling on Python.

  • Customer segmentation: Applied unsupervised classification (i.e., DBScan, MeanShift, Ward, K-means) and dimensionality reduction to perform customer segmentation analysis on Python.

Courses - Certificates -Testing Experience - Soft Skills

Courses

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Advanced Mathematics                                               Structural Dynamic               

Earthquake Engineering                                             Finite Element Method I & II   

Structural Reliability                                                   Structural Health Monitoring

Advanced Mechanics of Materials                            Advanced Behavior of Concrete

Advanced Steel Behavior                                            Acoustic I & II                 

Stochastic Process-Estimation- Control                Machine Learning (Audited)     

Neural Networks   (Audited)

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Certificates

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University of Michigan Phyton Course – Coursera (May 2022)

2 certificates in Python programming and data structures

IBM Machine Learning Course – Coursera (April 2023)

4 certificates in Explotary Data Analysis and Feature engineering, Regression, Supervised and Unsupervised learning

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International Courses

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1.  4th Summer School on Smart Materials and Structures, 2015, Trento, Italy 

2. COST-Action: Quantifying the value of structural health monitoring 2nd workshop, 2015, Istanbul, Turkey 

3.  Workshop on Bridge Health Monitoring, 2015, Istanbul, Turkey

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Sensor and Data Acquisition System Experience

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Laser Doppler vibrometry            

Acoustic Sensors

Oscilloscope                    

Linear potential meters

Strain gauges                 

Modal mass shakers

Accelerometers (force-balance and piezoelectric)

DAQ systems (PXI, Dewesoft, Kinemetrics)

Sensor integration of accelerometers, acoustic sensors, and lasers.

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Soft Skills

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Communication and data storytelling: prepared 12 peer-reviewed research papers; prepared 18 technical reports for funding agencies; made 8 conference presentations; supported funding proposals; got 2 commercialization and entrepreneurship awards; and made pitches to funding agencies.

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Teamwork and leadership: created and led 9 different research and technical groups.

Problem-solving and critical thinking: developed algorithms and solutions to 7 complex data-based predictive maintenance and structural health monitoring/NDT research projects.

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Education and collaboration: created educational sections on engineering systems and their dynamics as well as signal processing, optimization, and machine learning on the personal webpage; mentored students; teaching assistant to several engineering courses; peer-reviewer for engineering journals.

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Time management: helped plan the scheduling of different data-based predictive maintenance and structural health monitoring/NDT projects; successfully completed the projects on time; carried out several tests in laboratories and on fields on time.

Publications and Presentations

Journal Publications

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  1. M Shamszadeh, K Kaynardag, C Yang, S Salamone “Deep learning and system identification integrated detection of rail defects using a non-contact rail defect detection system”, IEEE Transactions on Automation Science and Engineering, (in preparation).

  2. K Kaynardag, A Pirotta, S Salamone “Using scanning measurements to represent the speckle noise in rail measurements performed by an laser Doppler vibrometer placed on a moving platform”, Measurement, (to be submitted in summer 2023).

  3. C Yang, K Kaynardag, S Salamone “LSTM autoencoder based automated railway anomaly detection using laser Doppler vibrometer measurements”, Structural Health Monitoring, (submitted).

  4. C Yang, K Kaynardag, S Salamone “Missing rail fastener detection based on laser doppler vibrometer measurements”, Journal of Nondestructive Evaluation, (submitted).

  5. C Yang, K Kaynardag, S Salamone “Investigation of wave propagation and attenuation in periodic supported rails using wave finite element method”, Acta Mechanica, (available online).

  6. K Kaynardag, C Yang, S Salamone “A rail defect detection system based on laser doppler vibrometer measurements”, NDT & E International, (accepted).

  7. K Kaynardag, C Yang, S Salamone “An impulsive noise filter for rail vibration measurements performed through a laser doppler vibrometer placed on a moving platform”, Mechanical Systems and Signal Processing, (in revision).

  8. C Yang, K Kaynardag, S Salamone “Evaluation of fastening modeling approaches for dynamic assessment of rail based on finite element method”, Journal of Engineering Mechanics, 148 (9), 04022048, 2022

  9. K Kaynardag, C Yang, S Salamone “The numerical simulations to examine the interaction of train-induced guided waves with transverse cracks”, Transportation Research Record, (available online), 2022.

  10. K Kaynardag, G Battaglia, A Ebrahimkhanlou, A Pirotta, S Salamone “Identification of bending modes of vibration in rails by a laser doppler vibrometer on a moving platform”, Experimental Techniques, 45 (1), 13-24, 2021

  11. K Kaynardag, G Battaglia, C Yang, S Salamone “Experimental investigation of the modal response of a rail span during and after wheel passage”, Transportation Research Record, 2674 (12), 15-24, 2020

  12. K Kaynardag, S Soyoz “Effect of identification on seismic performance assessment of a tall building”, Bulletin of Earthquake Engineering, 15 (8), 3227-3243, 2017

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Conference Proceedings

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  1. C Yang, K Kaynardag, S Salamone “LSTM autoencoder for anomaly detection in rails using laser doppler vibrometer measurements”, 14th  International Workshop on Structural Health Monitoring (IWSHM), 2023 (submitted)

  2. S Soyoz, E Karcioglu, E Aytulun, K Kaynardag, S C Pevlan, A Karadeniz, “Dynamic identification - model updating – seismic performance assessment of stone arch bridges”, Proceedings of the 4th Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures, 2017

  3. S Soyoz, U Dikmen, N Apaydin, K Kaynardag, E Aytulun, S Senkardesler, N Catbas, H Lus, E Safak, M Erdik, “System identification of bogazici suspension bridge under hanger replacement”, Procediea Engineering, 199, 1026-1031, Part of X International Conference on Structural Dynamics, EURODYN 2017, 2017.

  4. H Sesigur, G Erol, S Soyoz, K Kaynardag, S Gonen, “Repair and retrofit of ketchaouo mosque in Algeria”, In Structural Analysis of Historical Constructions: Anamnesis, Diagnosis, Theraphy, Controls, CRC Press, 1824-1831, 2016

  5. K Kaynardag, S Soyoz, “Seismic performance assessment of a tall building based on real-time monitoring”, SECED 2015 Conference: Earthquake Risk and Engineering towards a Resilient World, 2015

  6. K Kaynardag, S Soyoz, “Structural health monitoring of a tall building”, Second European Conference on Earthquake Engineering and Seismology, 2014

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Conference Presentations

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  1. K Kaynardag, C Yang, S Salamone “Detection of rail defects using guided ultrasonic waves and laser doppler vibrometry”, Society for Experimental Mechanics Conference-XLI, Austin, 2023

  2. K Kaynardag, C Yang, S Salamone “Rail defect detection by noncontact vibration measurements”, Engineering Mechanics Institute Conference, John Hopkins, Baltimore, 2022

  3. K Kaynardag, G Battaglia, S Salamone “Applicability of laser Doppler vibrometer placed on a moving platform for rail vibration measurements”, Transportation Research Board Annual Meeting 2021, Washington DC, 2021

  4. K Kaynardag, A Ebrahimkhanlou, S Salamone “Modal based detection of cracks in railway tracks and applicability of moving laser Doppler vibrometer”, Engineering Mechanics Institute Conference, MIT, Boston, 2018

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Invited Talk

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  1. “Development of a noncontact laser Doppler vibrometer based rail damage detection system”, Weekly Acoustic Seminar at Mechanical Engineering Department, The University of Texas at Austin, Austin, 2023

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Attended Conferences

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  1. The AI Summit and IoT World Austin, Austin, TX, USA, November 2022

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