Igor Popov | Robotics & Automation | Engineering Excellence Award

Published on by Superior Engineering

Engineering Excellence Award

Igor Popov — Kurgan State University, Russia

Igor Popov
Affiliation Kurgan State University
Country Russia
Scopus ID 55427914200
Documents 30
Citations 32
h-index 4
Subject Area Robotics & Automation
Event World Superior Engineering Research Awards

The Engineering Excellence Award recognizes scholarly and professional contributions associated with engineering research, technological development, and the advancement of practical engineering knowledge. This recognition profile presents Igor Popov of Kurgan State University in the context of robotics and automation, based on the researcher information supplied for the award record. Bibliographic identifiers and publication metrics should be independently verified through the relevant scholarly databases before formal use. [1]

Abstract

The Engineering Excellence Award profile for Igor Popov highlights an academic research context connected with Kurgan State University and the subject area of robotics and automation. Engineering research in this field commonly integrates mechanical systems, control, computation, sensing, and automated decision-making to develop systems capable of performing complex tasks with increasing levels of precision and autonomy. The award profile is intended to provide a structured academic overview rather than establish unverified claims concerning specific achievements, publications, citation counts, or bibliometric rankings. [2]

Keywords

Engineering Excellence Award; Igor Popov; Kurgan State University; Russia; Robotics and Automation; Engineering Research; Automation Systems; Robotics; Intelligent Systems; Control Engineering; Technological Innovation; Research Recognition.

Introduction

Robotics and automation represent interdisciplinary areas of engineering research concerned with the design, control, integration, and application of systems that can sense their environment, process information, and perform physical or computational tasks. Contemporary robotics research frequently combines engineering principles with computer science, artificial intelligence, electronics, control theory, and systems engineering. [2]

Within this broader context, an engineering recognition such as the Engineering Excellence Award can provide a framework for acknowledging research activity, technical contribution, scholarly communication, and potential practical relevance. The present profile identifies Igor Popov with Kurgan State University and associates the recognition with the World Superior Engineering Research Awards event. Institutional and bibliographic details should be checked against authoritative records when preparing an official nomination or publication. [1]

Research Profile

Igor Popov is presented in the supplied award information as a researcher affiliated with Kurgan State University in Russia, with a stated subject area of Robotics & Automation. The supplied Scopus Author ID is 55427914200. Scopus author identifiers are designed to distinguish researchers and connect indexed scholarly records with individual author profiles. [1]

The supplied information does not provide verified values for document count, citation count, h-index, ORCID identifier, or a complete publication list. These fields are therefore not assigned numerical values in this article. Such restraint helps distinguish documented bibliographic information from information that would require database verification.

Research Contributions

Research in robotics and automation may contribute to engineering through improvements in robotic control, automated manufacturing, autonomous systems, sensing, system integration, optimization, and human–machine interaction. The significance of an individual contribution is normally evaluated through the technical originality of the work, methodological soundness, reproducibility, scholarly dissemination, and relevance to engineering problems. [3]

  • Development or refinement of engineering methods applicable to robotics and automated systems.
  • Integration of sensing, control, computation, and mechanical components within engineered systems.
  • Investigation of automation approaches that may improve system efficiency, reliability, precision, or repeatability.
  • Scholarly communication through peer-reviewed publications, conference contributions, and other recognized research outputs.

Specific contributions should be attributed to the researcher only after examining the corresponding publications, project records, patents, institutional information, or other authoritative documentation. This approach is particularly important when preparing formal award materials or academic profiles.

Publications

The supplied data identifies a Scopus Author ID but does not include a verified publication bibliography. Consequently, this article does not attribute individual papers, journal titles, publication dates, citation totals, or DOI identifiers to Igor Popov without source verification. The Scopus author record can be used as a starting point for confirming indexed documents and distinguishing records belonging to the intended researcher. [1]

For formal academic documentation, each publication should be checked for author identity, title, venue, year, volume or issue where applicable, page range, DOI, and indexing status. DOI records can provide persistent identifiers for scholarly publications and are useful for reliable bibliographic linking. [4]

Research Impact

Research impact in robotics and automation can be assessed across several dimensions, including scholarly influence, technical advancement, industrial applicability, educational value, collaboration, and contribution to engineering practice. Citation counts and h-index values can provide bibliometric indicators, but they should be interpreted alongside publication quality, field-specific citation practices, research maturity, and demonstrated technological outcomes. [5]

For the present recognition profile, no independent numerical citation or h-index data has been supplied. The absence of such figures should not be interpreted as an assessment of research quality; it simply reflects the requirement to avoid presenting unverified metrics as established facts.

Award Suitability

The stated specialization in Robotics & Automation is broadly aligned with an engineering-focused recognition concerned with research excellence. A formal award assessment would ordinarily benefit from evidence demonstrating technical originality, methodological rigor, research productivity, practical or scholarly significance, and sustained contribution to the relevant engineering field.

  1. Technical relevance: Evidence should demonstrate a meaningful relationship between the candidate’s work and robotics, automation, or related engineering disciplines.
  2. Research quality: Publications, projects, methodologies, and results should be evaluated for scholarly rigor and technical validity.
  3. Innovation: The assessment may consider the originality of methods, systems, algorithms, designs, or applications.
  4. Impact: Evidence may include scholarly influence, industrial adoption, technological outcomes, or other documented forms of research contribution.
  5. Documentation: Bibliographic identifiers, institutional affiliations, publications, and supporting evidence should be independently verifiable.

The World Superior Engineering Research Awards website is identified in the supplied information as the relevant award website. Applicants and reviewers should consult the official award documentation for current eligibility conditions, submission requirements, evaluation procedures, deadlines, and recognition terms.

Conclusion

The Engineering Excellence Award profile presents Igor Popov of Kurgan State University, Russia, within the field of Robotics & Automation. The supplied Scopus Author ID provides a useful bibliographic reference point for verifying scholarly records. A comprehensive assessment of engineering excellence should combine authoritative publication data with evidence of technical contribution, innovation, research quality, and documented impact. [1]

This article intentionally avoids unsupported numerical claims concerning publications, citations, or h-index values. Such information should be updated only after verification against authoritative scholarly and institutional sources.

References

  1. Elsevier. (n.d.). Scopus author details: Igor Popov, Author ID 55427914200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55427914200
  2. Siciliano, B., & Khatib, O., eds. (2016). Springer Handbook of Robotics. Springer. DOI:
    https://doi.org/10.1007/978-3-319-32552-1
  3. Craig, J. J. (2005). Introduction to Robotics: Mechanics and Control. 3rd ed. Pearson.
  4. International DOI Foundation. (n.d.). DOI Handbook. DOI Foundation.
    https://doi.org/10.1000/182
  5. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. DOI:
    https://doi.org/10.1073/pnas.0507655102

Csaba Makó | Artificial Intelligence | Innovative Research Award

Published on by Superior Engineering

Innovative Research Award

Csaba Makó
Ludovika University of Public Service, Hungary

Csaba Makó
Affiliation Ludovika University of Public Service
Country Hungary
Scopus ID 6508289335
Documents 49
Citations 585
h-index 10
Subject Area Artificial Intelligence
Event Superior Engineering Research Awards
ORCID 0000-0002-2597-3103

Csaba Makó is a researcher affiliated with the Ludovika University of Public Service in Hungary. The researcher record supplied for this recognition profile identifies 49 documents, 585 citations, and an h-index of 10 in the Scopus-indexed record. The stated subject area is Artificial Intelligence, providing the disciplinary context for consideration under the Innovative Research Award category. [1]

Abstract

This academic recognition profile presents the documented research information of Csaba Makó in relation to the Innovative Research Award. His supplied bibliometric record contains 49 documents, 585 citations, and an h-index of 10. The profile identifies Artificial Intelligence as the relevant subject area and places the researcher within the academic environment of the Ludovika University of Public Service. Bibliographic identifiers provide a basis for distinguishing the researcher and locating associated scholarly records. [2]

Keywords

  • Artificial Intelligence
  • Innovation
  • Research
  • Bibliometrics
  • Academic Publications
  • Research Impact

Introduction

Research recognition commonly considers scholarly output, documented influence, disciplinary relevance, and identifiable research records. In this context, the Innovative Research Award profile records the available bibliometric indicators associated with Csaba Makó and relates them to the stated field of Artificial Intelligence. Scopus author identifiers and ORCID provide complementary mechanisms for researcher identification and scholarly record management. [1] [3]

Research Profile

The supplied profile associates Csaba Makó with the Ludovika University of Public Service in Hungary and identifies Artificial Intelligence as the principal subject area. The reported publication record consists of 49 documents. Its citation count is 585, while the h-index is reported as 10. These indicators describe bibliometric activity but do not, by themselves, characterize the methodological quality or substantive significance of individual publications. [1]

Research Contributions

Within the information supplied for this profile, the research contribution is framed around scholarly activity in Artificial Intelligence. Relevant contributions may be examined through individual publications, research topics, collaborations, methodologies, and documented applications. A complete assessment requires examination of the underlying publications and their research contexts rather than relying solely on aggregate bibliometric indicators. [4]

Publications

The supplied Scopus record reports 49 documents associated with the researcher identifier 6508289335. Individual publication titles, journals, publication dates, citation distributions, and DOI records should be verified against the corresponding bibliographic databases before being used for detailed publication-level analysis. [1]

Research Impact

The reported total of 585 citations and h-index of 10 provides a quantitative description of the researcher’s citation record at the time represented by the supplied data. Citation indicators can vary between databases and over time, and they may also differ according to indexing coverage. Consequently, the figures should be interpreted together with publication-level and disciplinary context. [1] [5]

Award Suitability

The Innovative Research Award profile connects the supplied research record with the Superior Engineering Research Awards event. The documented affiliation, subject area, publication count, citation count, h-index, and persistent researcher identifier provide factual information for an award-review process. Final recognition should be determined according to the applicable award criteria and verification procedures. [6]

Conclusion

Csaba Makó’s supplied academic profile documents a research record associated with the Ludovika University of Public Service, Hungary, and Artificial Intelligence. The reported 49 documents, 585 citations, and h-index of 10 form the principal bibliometric indicators presented in this recognition profile. Persistent identifiers such as Scopus Author ID and ORCID support researcher identification and facilitate further verification of scholarly records.

References

  1. ORCID. (n.d.). Csaba Makó — ORCID record.
    https://orcid.org/0000-0002-2597-3103
  2. Elsevier. (n.d.). Scopus Author Details: Csaba Makó, Author ID 6508289335.
    https://www.scopus.com/authid/detail.uri?authorId=6508289335
  3. Makó, C., Illéssy, M., Pap, J., Farkas, É., & Komlósi, L. (2025). Algorithmic Management in Traditional Workplaces: The Case of High vs. Low Involvement Working Practices. Journal of Labor and Society. https://doi.org/10.1163/24714607-bja10182
  4. Molina, O., Butollo, F., Makó, C., et al. (2023). It takes two to code: A comparative analysis of collective bargaining and artificial intelligence. Transfer: European Review of Labour and Research. https://doi.org/10.1177/10242589231156515
  5. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.

Prof. Dr. Chengli Sun | Artificial Intelligence | Best Researcher Award

Published on by Superior Engineering

Prof. Dr. Chengli Sun | Artificial Intelligence | Best Researcher Award

Prof. Dr. Chengli Sun | Guangzhou Maritime University | China

Prof. Dr. Chengli Sun is a distinguished scholar in the field of signal and information processing, widely recognized for his significant contributions to intelligent acoustic technology and next-generation speech systems.To date, his work has accumulated 336 citations across 303 documents, demonstrating the broad recognition and adoption of his research outcomes by both domestic and international peers. With 46 published documents spanning high-impact journals His research encompasses speech recognition, speech enhancement, acoustic scene analysis, and computer vision, with a strong focus on advancing human–machine voice interaction under complex and noisy environments. He has led a series of high-impact scientific projects, including major National Natural Science Foundation of China grants and key provincial and municipal initiatives, driving breakthroughs in generative adversarial network models, dual-diffusion speech enhancement, sustainable learning-oriented vehicle voice interaction, and speaker-specific keyword spotting. These research outcomes have enabled practical advancements in intelligent transportation, robotics, smart devices, and public safety. Alongside his research achievements, Prof. Dr. Chengli Sun plays an integral role in academic development and scientific service by contributing to expert review committees and supporting the progress of information processing and acoustics disciplines. He remains committed to high-level talent cultivation through leadership in first-class undergraduate teaching programs and the promotion of interdisciplinary innovation in artificial intelligence and signal processing. Collectively, his sustained research efforts, academic influence, and dedication to education position him as a leading figure shaping the future of intelligent voice technologies.

Profiles: Scopus | Orcid

Featured Publications

  • Sun, M., Sun, C., Zou, C., Zhang, J., & Xiang, D. (2025). Modeling of multi-electrode epicardial electrograms for conductivity estimation in atrial fibrillation. IEEE Access.

  • Li, J., Xiang, D., Li, C., Mao, S., Chen, Y., Sun, M., He, W., Deng, Y., & Sun, C. (2025, December 3). Learning student knowledge states from multi-view question–skill networks. Symmetry.

  • Leng, Y., Zhang, E., Zhuang, J., Shen, C., Sun, C., Yuan, Q., & Pan, J. (2025, October). A topic-specific representation learning framework for acoustic scene classification. Applied Soft Computing.

  • Rao, Z., Sun, C., Sun, J., Chen, F., Leng, Y., Sun, M., & Guo, Q. (2025, October 16). A new speech enhancement model based on residual denoising diffusion. Circuits, Systems, and Signal Processing.

  • Wan, M., Zhu, J., Sun, C., Yang, Z., Yin, J., & Yang, G. (2024). Tensor low-rank graph embedding and learning for one-step incomplete multi-view clustering. IEEE Transactions on Multimedia.

 

 

Prof. Dr Adrian Tunduc | Internet of Things | Editorial Board Member

Published on by Superior Engineering

Prof. Dr Adrian Tunduc | Internet of Things | Editorial Board Member

Prof. Dr Adrian Tunduc | Oradea University | Romania

Prof. Dr Adrian Tunduc is a distinguished academic, researcher, and managerial professional whose career spans higher education, strategic research, and successful leadership across multiple industries. As a senior lecturer at the University of Oradea’s Faculty of Environment, he has achieved an exceptional academic performance score, far exceeding standard benchmarks, while teaching and developing key disciplines such as forest management, forest economics, quality management, tourism management, furniture technology, and wildlife resource management for both graduate and master’s students. His academic excellence is complemented by extensive experience in applied research, notably during his tenure as an associate researcher at the National Economic Research Institute of the Romanian Academy, where he led impactful projects on marketing research, feasibility studies for bio-land certification, Horizon 2020 applications, and strategic planning for the Danube microregion. Beyond academia, he has demonstrated strong business leadership through management roles in hospitality, transport, and manufacturing sectors, including transforming Vila De la Lugas into a high-performing guest facility with exceptional customer ratings. His earlier management of production and transport companies further highlights his ability to grow businesses, optimize operations, and innovate within competitive environments. Throughout his career, he has consistently delivered excellence through strategic thinking, academic rigor, and strong organizational development skills.

Profile: Google Scholar

Featured Publications

1. T., Adrian. (2010). E-Marketing in the Romanian agriculture and rural development.

2. T., Adrian. (2021). Forest governance for the future health of the planet.

3. T., Adrian. (2021). Forest economics: From theory to sustainable applications.

4. Tunduc, A. (2010). Marketing electronic în agricultură şi dezvoltarea rurală. Editura Universităţii din Oradea.

5. T., Adrian. (2018). The cluster concept for a sustainable development of thermal spa in România. Analele Universităţii Oradea, Fascicula Protecţia Mediului, 31(23), 273–277.

6. T., Adrian. (2018). Romanian bioresources – The thermal waters as a contribution to the Romanian tourism development. Analele Universităţii Oradea, Fascicula Protecţia Mediului, 30(23), 259–262.

Prof. Ebenezer Esenogho | Artificial Intelligence | Best Researcher Award

Published on by Superior Engineering

Prof. Ebenezer Esenogho | Artificial Intelligence | Best Researcher Award

Prof. Ebenezer Esenogho | University of South Africa | South Africa

Prof. Ebenezer Esenogho (NRF C2-rated) is a distinguished academic and research leader recognized for his extensive contributions to Artificial Intelligence, telecommunications engineering, and digital innovation. With a strong background in computer, electronics, and communication engineering, he has built an influential career marked by advanced research, academic leadership, and international collaboration. He has produced impactful work across areas such as AI-driven wireless systems, 5G networks, cognitive radio, cybersecurity, IoT, smart grid technologies, software-defined systems, big data, and cloud computing. His scholarly influence is reflected in 920 citations from 762 documents, 40 published documents, and an h-index of 12. Prof. Esenogho has secured numerous competitive grants, awards, and research fellowships in recognition of his excellence, and he has contributed to global research advancement through participation in strategic committees, collaborative initiatives, and high-level innovation programs. He has supervised a wide portfolio of postgraduate researchers, contributed to editorial boards, reviewed international grant proposals, and chaired sessions at reputable conferences. Beyond research, he is committed to academic mentorship, capacity building, and advancing technology-driven development through community-focused initiatives. Prof. Ebenezer continues to play a leading role in shaping the future of intelligent systems, next-generation networks, and multidisciplinary innovation across regional and global research landscapes.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

  • Esenogho, E., Mienye, I. D., Swart, T. G., Aruleba, K., & Obaido, G. (2022). A neural network ensemble with feature engineering for improved credit card fraud detection. IEEE Access, 10, 16400–16407.

  • Esenogho, E., Djouani, K., & Kurien, A. M. (2022). Integrating artificial intelligence, Internet of Things, and 5G for next-generation smart grid: A survey of trends, challenges, and prospects. IEEE Access, 10, 4794–4831.

  • Sarah, I. D. M., Ebiaredoh-Mienye, A., Esenogho, E., & Swart, T. G. (2022). A machine learning method with filter-based feature selection for improved prediction of chronic kidney disease. Bioengineering, 9(8).

  • Nguyen, N., Duong, T., Chau, T., Nguyen, V. H., Trinh, T., Tran, D., Ho, T., … Esenogho, E. (2022). A proposed model for card fraud detection based on CatBoost and deep neural network. IEEE Access, 10, 96852–96861.

  • Arnaz, A., Lipman, J., Abolhasan, M., Hiltunen, M., … Esenogho, E. (2022). Toward integrating intelligence and programmability in open radio access networks: A comprehensive survey. IEEE Access, 10, 67747–67770.

  • Obaido, G., Ogbuokiri, B., Swart, T. G., Ayawei, N., Kasongo, S. M., Aruleba, K., … Esenogho, E. (2022). An interpretable machine learning approach for hepatitis B diagnosis. Applied Sciences, 12(21), 11127.

 

Prof. Dr. HyunJe Oh | Cyber-Physical Systems | Best Researcher Award

Published on by Superior Engineering

Prof. Dr. HyunJe Oh | Cyber-Physical Systems | Best Researcher Award

Prof. Dr HyunJe Oh | Korea Institute of Construction Technology | South Korea

Prof. Dr. Hyun Je Oh is a highly respected expert in civil, environmental, and water engineering, known for his extensive contributions as a Senior Research Fellow at the Korea Institute of Construction Technology and as a Professor at the University of Science and Technology. With advanced academic training culminating in a Doctor of Philosophy degree in Civil and Environmental Engineering, he has led 112 national research and development projects completed by 2025, contributing significantly to advancements in water treatment, environmental protection, and engineering innovation. His professional leadership includes long-term service in the Clean Water Forum Committee of the National Assembly, presidency of the Korea Society on Water and Wastewater from 2015 to 2017, and chairing the Seoul Metropolitan Government Tap Water Evaluation Committee from 2010 to 2012. Prof. Dr. Oh’s scholarly achievements include 51 published documents, 69 domestic and international research papers, and 421 academic presentations. His work has received 783 citations from 729 referencing documents, supported by a citation index score of 13. He also maintains a strong record in industrial innovation, with 96 patent applications and registrations, 61 officially granted patents, and 17 technologies successfully transferred to industry, demonstrating substantial impact on clean water systems and sustainable engineering practices.

Profile: Scopus

Featured Publications

Oh, H. J. (2026). Optimal data pooling from multiple waterbodies to improve machine-learning predictions of cyanobacterial blooms. Journal of Contaminant Hydrology.

Oh, H. J. (2026). Evaluating circulation-type membrane capacitive deionization as a dual-function system for ion removal and enrichment. Desalination.

Oh, H. J. (2025). Enhanced desalination performance of pilot-scale membrane capacitive deionization system with circulation process. Desalination.

Oh, H. J. (2024). Performance optimization of a pilot-scale membrane capacitive deionization system operating with circulation process. Separation and Purification Technology.

Oh, H. J. (2023). Optimizing operational conditions of pilot-scale membrane capacitive deionization system. Sustainability.

Dr. Xiuyun Zhang | Control Systems Engineering | Best Researcher Award

Published on by Superior Engineering

Dr. Xiuyun Zhang | Control Systems Engineering | Best Researcher Award

Dr. Xiuyun Zhang | Tianjin University of Technology and Education | China

Dr. Xiuyun Zhang is a lecturer and researcher specializing in motor systems and their control, with a particular emphasis on multi-motor collaborative control. Her teaching covers theoretical foundations such as circuit principles and automatic control principles, while her research explores torque coordination in large-load drives, speed coordination in industrial applications, and position coordination and contour control in high-precision CNC machining. She has published over 20 SCI/EI indexed papers and more than 10 journal publications, with a record of 972 citations from 914 documents, 94 published works, and an h-index of 16. Her innovative contributions are reflected in 16 granted or filed patents, including invention and utility model patents. As a project leader, she has directed research supported by the Tianjin Natural Science Foundation Youth Project, the Tianjin Higher Education Science and Technology Development Fund, an invention patent conversion initiative, and several horizontal projects, while also contributing as a main researcher to a National Natural Science Foundation general project. With more than five completed or ongoing research projects, her work focuses on developing predictive and interactive control strategies that use speed and current as internal system variables, aiming to improve collaborative control accuracy and dynamic response in advanced motor applications.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Zhang, R., Zong, Q., Zhang, X., Dou, L., & Tian, B. (2022). Game of drones: Multi-UAV pursuit-evasion game with online motion planning by deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 7900–7909.

  • Wang, D., Zong, Q., Tian, B., Shao, S., Zhang, X., & Zhao, X. (2018). Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters. ISA Transactions, 73, 208–226.

  • Dou, L., Cai, S., Zhang, X., Su, X., & Zhang, R. (2022). Event-triggered-based adaptive dynamic programming for distributed formation control of multi-UAV. Journal of the Franklin Institute, 359(8), 3671–3691.

  • Liu, D., Dou, L., Zhang, R., Zhang, X., & Zong, Q. (2022). Multi-agent reinforcement learning-based coordinated dynamic task allocation for heterogeneous UAVs. IEEE Transactions on Vehicular Technology, 72(4), 4372–4383.

  • Ye, L., Zong, Q., Tian, B., Zhang, X., & Wang, F. (2017). Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle. ISA Transactions, 70, 161–172.

  • Zhang, X., Zong, Q., Dou, L., Tian, B., & Liu, W. (2020). Finite-time attitude maneuvering and vibration suppression of flexible spacecraft. Journal of the Franklin Institute, 357(16), 11604–11628.

  • Zhang, X., Zong, Q., Dou, L., Tian, B., & Liu, W. (2020). Improved finite-time command filtered backstepping fault-tolerant control for flexible hypersonic vehicle. Journal of the Franklin Institute, 357(13), 8543–8565.

 

 

Assoc. Prof. Dr. Alireza Zirak | Robotics & Automation | Best Researcher Award

Published on by Superior Engineering

Assoc. Prof. Dr. Alireza Zirak | Robotics & Automation | Best Researcher Award

Assoc. Prof. Dr. Alireza Zirak | Nuclear Science and Technology Research Institute | Iran

Prof. Alireza Zirak is an Associate Professor at the Laser and Optics Research School, specializing in electronics, telecommunications, and advanced photonics. His research focuses on tomography and radiotherapy systems, quantum technology, digital signal and image processing, laser applications, IoT, embedded systems, and stochastic modeling. He has received multiple national honors, including top rankings in Iran’s University Entrance Examination and Mathematics Olympiad, the National Science Festival design prize, and recognition at the National Engineer’s Day festival. Prof. Zirak has also contributed as a scientific committee member for major conferences and received acknowledgments from institutions such as the Vice Presidency for Science and Technology. With expertise in optimization, microcontroller programming, and photonics system design, he has played a significant role in advancing interdisciplinary applications of electronics and optics. His academic influence is reflected in 174 citations from 139 documents, 20 publications, and an h-index of 8, demonstrating both his productivity and impact in modern engineering and photonics research.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Nankali, S., Worm, E. S., Weber, B., Høyer, M., Zirak, A., Poulsen, P. R. (2018). Geometric and dosimetric comparison of four intrafraction motion adaptation strategies for stereotactic liver radiotherapy. Physics in Medicine & Biology, 63(14), 145010.

  • Khezerloo, D., Nedaie, H. A., Zirak, A., Farhood, B., Banaee, N., Alidokht, E. (2018). Dosimetric properties of new formulation of PRESAGE® with tin organometal catalyst: Development of sensitivity and stability to megavoltage energy. Journal of Cancer Research and Therapeutics, 14(2), 308–315.

  • Rajabi, H., & Zirak, A. (2016). Speckle noise reduction and motion artifact correction based on modified statistical parameters estimation in OCT images. Biomedical Physics & Engineering Express, 2(3), 035012.

  • Zirak, A. R., & Khademi, M. (2007). An efficient method for model refinement in diffuse optical tomography. Optics Communications, 279(2), 273–284.

  • Zirak, A. R., & Roshani, S. (2016). A reduced switch voltage stress class E power amplifier using harmonic control networks. International Journal of Advanced Computer Science and Applications, 7, 38–42.