Duygu Bayram Kara is a seasoned academic and researcher with deep expertise in signal processing, soft computing, and machine learning, particularly applied to condition monitoring, diagnostics, and electric machinery. Currently serving as an Associate Professor at Istanbul Technical University in the Department of Electrical Engineering, she brings over a decade of academic and industry experience. Her research combines theoretical innovation with practical application, contributing to the evolving field of intelligent systems. Her academic journey has been rooted in Istanbul Technical University, where she earned her BSc, MSc, and PhD, focusing on induction motor design and diagnostics using advanced analytical tools such as finite element analysis and wavelet transforms. Duygu has complemented her academic work with international research experiences, notably as a Visiting Researcher at the University of Tennessee, Knoxville. She is also actively involved in public outreach and technical consulting, further underlining her multidisciplinary impact. Her commitment to lifelong learning is reflected in a broad range of certifications and training, including predictive modeling, diagnostics platforms, and simulation software. With a balanced profile that merges strong theoretical grounding, industrial relevance, and societal contribution, Duygu Bayram Kara stands out as a compelling candidate for research honors and recognition.

Professional  Profile

• Scopus Profile
• ORCID Profile

Educational Background

Duygu Bayram Kara holds a comprehensive academic background in Electrical Engineering, having completed all her higher education at the prestigious Istanbul Technical University. She earned her Bachelor of Science degree between 2001 and 2006, focusing on the design of squirrel cage induction motors, which laid the groundwork for her future specialization. Her Master’s degree, completed between 2006 and 2009, involved advanced finite element analysis, specifically examining the impact of time harmonic voltages on induction machines. This rigorous technical foundation was further strengthened by her PhD studies from 2009 to 2015, where she developed innovative methodologies for condition monitoring and fault detection in induction motors using geometric trending and stationary wavelet analysis. Her academic training provided her with solid skills in modeling, simulation, and diagnostics, essential for modern-day electrical engineering challenges. During her educational journey, Duygu not only acquired theoretical knowledge but also demonstrated an ability to apply these skills in research settings, earning her recognition as a technically proficient and research-driven scholar. Her educational pathway reflects a deep and focused commitment to mastering complex electromechanical systems and diagnostic methodologies, which she continues to explore in her academic and industrial collaborations.

Professional Experience

Duygu Bayram Kara has cultivated a rich and diverse professional career centered on electrical engineering, diagnostics, and intelligent systems. She currently serves as an Associate Professor in the Electrical Engineering Department of Istanbul Technical University, where she leads the Intelligent Condition Monitoring & Diagnostics Lab. Her academic journey at the university began as a Research Assistant in 2007, culminating in a decade-long role as Assistant Professor from 2016 to 2025. Beyond academia, she has also worked in industry as a Senior Researcher at MEKATRO Mechatronic Systems Research & Development Corp., where she contributed to the design and optimization of electric vehicle drive systems. Her international exposure includes a stint as a Visiting Researcher at the University of Tennessee, Knoxville, collaborating with the PROACT Lab on reliability and maintainability projects. In addition to her academic and research activities, she has provided consultancy and training for organizations such as the Directorate General of Coastal Safety of Turkiye and ARÇELIK, where she played a key role in designing high-efficiency electric motors. This blend of academic rigor, practical industry involvement, and international collaboration highlights her multifaceted professional profile, showcasing her ability to navigate and impact various sectors in the field of electrical engineering and applied diagnostics.

Research Interests

Duygu Bayram Kara’s research interests lie at the intersection of electrical engineering, machine learning, and system diagnostics. Her primary focus areas include signal processing, condition monitoring, fault diagnostics, soft computing, and electric machinery. She has a particular interest in using machine learning and wavelet-based approaches for predictive maintenance and early fault detection in rotating electrical machines such as induction motors. Her academic foundation in electric machine design allows her to approach diagnostics not only from a data perspective but also from an in-depth understanding of electromechanical system behavior. She is also actively engaged in finite element modeling (FEM) and simulation-based analysis, which she applies to complex system evaluations and component-level analysis. Over the years, Duygu has expanded her research to include intelligent monitoring systems, contributing to innovations in both hardware and software solutions for industrial applications. Her collaborative work in international labs and consulting roles further enriches her research perspective, bridging the gap between theoretical development and industrial needs. She continues to explore new frontiers in diagnostics and reliability engineering, ensuring her work remains aligned with technological advancements and real-world challenges in electrical engineering and system optimization.

Research Skills

Duygu Bayram Kara possesses a robust and versatile research skill set that spans theoretical modeling, computational simulation, experimental diagnostics, and machine learning applications. Her technical toolkit includes advanced proficiency in MATLAB, Python, and simulation software such as ANSYS Maxwell, RMxprt, and FEMM. She has substantial expertise in signal processing techniques, including wavelet analysis and time-frequency representations, used for condition monitoring and fault detection in electric machinery. Her ability to apply finite element analysis (FEA) to evaluate the behavior of electrical machines under different conditions highlights her simulation proficiency. Furthermore, Duygu is trained in using specialized tools such as the MATLAB Diagnostics and Prognostics Toolbox and has completed professional training in predictive modeling and empirical prognostics. She effectively integrates soft computing approaches and artificial intelligence algorithms into traditional electrical engineering problems, thereby contributing to the evolution of intelligent monitoring systems. Her experience working with vibration sensing platforms, coupled with her background in electric machine design, enables her to diagnose faults with high accuracy. This multidisciplinary skill set positions her as a valuable asset in both academic and industrial research environments. She demonstrates not only technical excellence but also a practical orientation, making her a well-rounded and impactful researcher.

Awards and Honors

While the provided profile does not list major competitive awards or honors explicitly, Duygu Bayram Kara has earned significant recognition through her academic, professional, and technical accomplishments. Notably, she became a Senior Member of IEEE in July 2021, a status granted to individuals with extensive experience and significant performance in their field. This recognition reflects her leadership, technical proficiency, and professional involvement in the global electrical engineering community. Additionally, she has participated in numerous prestigious training programs, such as IEEE’s Continuing Education workshops on condition-based monitoring and empirical modeling, as well as specialized certifications in predictive analytics and simulation tools. Her consultancy roles with organizations like ARÇELIK and the Directorate General of Coastal Safety indicate a high level of trust and credibility in her applied research expertise. Furthermore, her involvement in socially impactful events, such as organizing the EU Sustainable Energy Week and educational science outreach programs, speaks to her dedication to science communication and community engagement. Although competitive research awards or grant recognitions are not detailed in her profile, her accumulation of professional certificates, trusted consulting roles, and IEEE senior membership validate her achievements and contributions in the field of diagnostics and electric machinery.

Conclusion

In conclusion, Duygu Bayram Kara presents a compelling case as a candidate for the Best Researcher Award. Her work embodies a rare blend of academic depth, technical innovation, practical industry experience, and international collaboration. With a research focus on condition monitoring, signal processing, and electric machinery diagnostics, she has consistently contributed to both theoretical knowledge and practical solutions. Her robust academic background, enhanced by global exposure and multidisciplinary expertise, positions her as a leading figure in her field. Her profile reflects not only excellence in research but also a commitment to societal advancement through education and public engagement. Moreover, her consultancy experience and continuous professional development underscore her dynamic approach to solving real-world engineering challenges. While the profile could benefit from more detailed recognition through competitive research awards or high-profile grants, her achievements across teaching, research, and service clearly indicate sustained impact and leadership. Overall, Duygu Bayram Kara stands out as a researcher who combines innovative thinking with technical mastery, making her a worthy nominee for distinguished research accolades and recognition in the global academic and engineering community.

Publications Top Notes

1. Degradation assessment of an IGBT with recurrence analysis and Kalman filter based data fusion
   Authors: Duygu Bayram Kara
   Journal: Chaos, Solitons and Fractals
   Year: 2024

2. Park vector approach based misalignment detection strategy for IMs (Conference Paper)
   Authors: Ege Kahraman, Anil Erkut Ulusoy, Mehmet Ozan Şerifoğlu, Duygu Bayram Kara
   Year: 2024
   Citations: 1