Liana Mogilnikova | Materials Science | Best Researcher Award

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Mrs. Liana Mogilnikova | Materials Science | Best Researcher Award

Liana Mogilnikova  | MISIS | Russia

Mrs. Liana Mogilnikova is a dedicated and accomplished researcher specializing in the study of hexagonal ferrites and magnetically hard materials. Her research focuses on understanding phase transformations and crystal structures, contributing valuable insights into the synthesis and characterization of strontium hexaferrite. Through meticulous experimentation and analytical precision, she has developed a comprehensive methodology for investigating the structural and phase states of ferrite materials. Her scholarly contributions, reflected in publications in reputed journals, demonstrate her commitment to advancing material science and magnetic materials research. With strong skills in data analysis, academic writing, and conference presentation, she effectively communicates complex scientific findings to the research community. Her work not only deepens the understanding of ferrite synthesis mechanisms but also lays the foundation for future innovations in nanostructured and energy-efficient magnetic materials, establishing her as a promising and impactful researcher in her field.

Profiles: Scopus | ORCID

Featured Publications

1. Mogilnikova, L. D., Menushenkov, V. P., Mogilnikov, P. S., & Savchenko, A. G. (2025). Phase transformations in the synthesis process of strontium hexaferrite SrFe₁₂O₁₉ by the sol-gel method. Journal of Alloys and Compounds, 1042, 183995.

Geng-Long Hsu | Medicine and Dentistry | Best Researcher Award

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Prof. Dr. Geng-Long Hsu | Medicine and Dentistry | Best Researcher Award

Director | Hsu’s Andrology | Taiwan

Prof. Dr. Geng-Long Hsu is a distinguished urologist and microsurgical potency reconstruction specialist with decades of experience in clinical practice, research, and education. He has pioneered innovative surgical techniques and contributed significant anatomical and physiological insights in male reproductive medicine. His leadership in multiple research centers and academic institutions has fostered a strong culture of mentorship and collaboration. Dr. Hsu is recognized internationally through memberships in professional societies and numerous awards for both basic and clinical research, highlighting the global impact of his work. His research demonstrates a consistent focus on advancing urological science, integrating clinical expertise with experimental innovation. Through his contributions, he has influenced treatment protocols and surgical outcomes in male reproductive health. His measurable research impact is reflected in Scopus, with 1,521 citations across 68 documents and an h-index of 22, underscoring the significance and reach of his scholarly work.

Profiles: Scopus | ORCID

Featured Publications

1. G.-L. Hsu, “Combining erection restoration and factual penile enhancement based on revolutionary penile fibro-vascular assembly,” Archivos Espanoles De Urologia, 2025.

2. G.-L. Hsu, “A detailed analysis of the penile fibro-vascular assembly,” Journal of Sexual Medicine, 2025.

3. G.-L. Hsu, “Coil embolization is not justified for treating patients with veno-occlusive dysfunction: Case series and narrative literature review,” Life, 2024.

4. G.-L. Hsu, “Emergent penile venous stripping for treating adolescent impotence,” Life, 2024.

5. G.-L. Hsu, “A case report of right cardiac ventricle perforation by uncontrolled embolization coil inserted for treating penile veno-occlusive dysfunction,” Urology Case Reports, 2022.

Panagiota Koutsimani | Neuropsychology | Best Researcher Award

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Dr. Panagiota Koutsimani | Neuropsychology | Best Researcher Award

Adjunt Lecturer | University of Western Macedonia | Greece

Dr. Panagiota Koutsimani is a cognitive neuropsychologist specializing in burnout, cognitive functioning, and mental health. She holds a PhD in Cognitive Psychology from the University of Macedonia and is currently a postdoctoral researcher at Aristotle University of Thessaloniki. Her research has significantly contributed to understanding the relationships between burnout, depression, and anxiety, notably through her widely cited meta-analysis published in Frontiers in Psychology. She has also investigated cognitive performance in non-clinical burnout populations, highlighting the role of family support as a protective factor. Her work employs rigorous methodologies, including longitudinal studies and meta-analyses, reflecting a strong commitment to advancing psychological research. In addition to her research, Dr. Koutsimani has extensive teaching and dissertation supervision experience, mentoring emerging researchers in both cognitive and neuropsychology fields. According to her Google Scholar profile, total citations 1903, since 2020 citations 1854, h-index 8, i10-index 7.

Profile: Scopus | Google Scholar

Featured Publications

1. P. Koutsimani, A. Montgomery, and K. Georganta, “The relationship between burnout, depression, and anxiety: A systematic review and meta-analysis,” Frontiers in Psychology, vol. 10, p. 429219, 2019.

2. A. Kariou, P. Koutsimani, A. Montgomery, and O. Lainidi, “Emotional labor and burnout among teachers: A systematic review,” International Journal of Environmental Research and Public Health, vol. 18, no. 23, p. 12760, 2021.

3. P. Koutsimani, A. Montgomery, E. Masoura, and E. Panagopoulou, “Burnout and cognitive performance,” International Journal of Environmental Research and Public Health, vol. 18, no. 4, p. 2145, 2021.

4. P. Koutsimani, A. Montgomery, and K. Georganta, “The relationship between burnout, depression, and anxiety: A systematic review and meta-analysis,” Frontiers in Psychology, vol. 10, p. 284, 2019.

5. P. Koutsimani and A. Montgomery, “A two-wave study on the associations of burnout with depression and anxiety: The mediating and moderating role of perceived family support,” Psychological Reports, vol. 126, no. 1, pp. 220–245, 2023.

Dr. Zeinab Shahbazi | Computer Science | Best Researcher Award

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Dr. Zeinab Shahbazi | Computer Science | Best Researcher Award

Senior Lecturer at Kristianstad University, Sweden

Dr. Zeinab Shahbazi is an accomplished researcher specializing in Reinforcement Learning, Deep Learning, Natural Language Processing, Blockchain, and Knowledge Discovery. With a Ph.D. in Computer Engineering from Jeju National University, South Korea, she has over eight years of research experience in AI and data-driven technologies. Dr. Shahbazi has held postdoctoral positions in Spain and Sweden and is currently a Senior Lecturer in AI at Kristianstad University. Her research focuses on enhancing state-of-the-art architectures and developing innovative solutions in software-based intelligent systems. She has been recognized with several academic awards, including a Presidential Award and Best Paper Presentation honors. Fluent in multiple languages and technically skilled in programming and data systems, she actively contributes as a reviewer for high-impact journals. Her international collaborations and funded research projects reflect her commitment to advancing AI applications. Dr. Shahbazi is a dedicated and forward-thinking researcher making significant contributions to the field of computer science.

Professional Profile 

Google Scholar

Education

Dr. Zeinab Shahbazi holds a Ph.D. in Computer Engineering from Jeju National University, South Korea, where she completed her dissertation on cryptocurrency price prediction using blockchain frameworks, graduating with an impressive CGPA of 4.32/4.5. She also earned a Master’s degree in Computer Engineering from Chonbuk National University, Korea, with a thesis on deep learning techniques for paragraph focus analysis. Her foundational education includes a Bachelor’s degree in Computer Engineering from Pooyesh University in Iran. Throughout her academic journey, she received several scholarships and honors, reflecting her consistent academic excellence. Her education has been firmly rooted in AI, software systems, and intelligent technologies, providing her with a robust theoretical and practical grounding. This strong academic background has played a pivotal role in shaping her as a multidisciplinary researcher with global exposure, capable of addressing complex problems in AI and data science with both depth and innovation.

Professional Experience

Dr. Zeinab Shahbazi has accumulated diverse international professional experience in research and academia. She is currently a Senior Lecturer in Artificial Intelligence at Kristianstad University, Sweden. Prior to this, she held postdoctoral researcher positions at Halmstad University in Sweden and at the BCN-AIM Lab at the University of Barcelona in Spain. Her work has consistently focused on applied AI, reinforcement learning, and blockchain-based systems. Dr. Shahbazi has also led and participated in international research collaborations, notably securing a Vinnova-funded international staff exchange project with a partner institution in South Korea. Her career path showcases her ability to transition between theoretical research and practical implementations, including experience in advanced programming, system architecture, and AI model development. These roles have enabled her to contribute to both the academic and industrial applications of intelligent technologies, while also strengthening her leadership and mentoring capabilities in multidisciplinary, multicultural environments.

Research Interest

Dr. Zeinab Shahbazi’s research interests are deeply rooted in intelligent computing systems, with a focus on Reinforcement Learning, Deep Learning, Natural Language Processing (NLP), Blockchain, Knowledge Discovery, and their integration within modern technological ecosystems such as IoT, edge computing, and big data platforms. Her core research ambition lies in improving existing AI models and architectures, addressing their limitations, and introducing novel components to enhance performance and applicability. She has made notable contributions to the software aspects of AI, particularly through her work on knowledge-driven systems and blockchain-based data prediction. Dr. Shahbazi combines theoretical advancements with practical implementations, bridging the gap between academic research and real-world applications. Her multidisciplinary focus reflects a keen interest in innovation, system integration, and cross-domain problem-solving. This makes her work highly relevant to both academic audiences and industry stakeholders interested in deploying intelligent, data-driven systems for practical and scalable use.

Award and Honor

Dr. Zeinab Shahbazi has received multiple awards and honors in recognition of her academic excellence and research contributions. During her Ph.D. at Jeju National University, she was awarded the prestigious Presidential Award for distinguished research publications. She also received a university research grant in 2021 for her outstanding output during 2019–2020. Earlier in her academic career, she was a recipient of the BK government scholarship and multiple semester-based scholarships during her Master’s studies at Chonbuk National University. Her early academic promise was also recognized with a government-funded scholarship during her undergraduate studies in Iran. Additionally, she won the Best Paper and Presentation Award at the ITEC Conference in 2019, further solidifying her reputation in the research community. These honors demonstrate a consistent trajectory of excellence, reflecting both the quality and impact of her research work, as well as her ability to compete and stand out in international academic environments.

Conclusion

Dr. Zeinab Shahbazi exemplifies a dynamic and impactful researcher in the field of computer science, particularly in AI, machine learning, and data-driven systems. Her strong educational background, diverse international research experience, and cross-disciplinary expertise make her a well-rounded academic and innovator. Her ability to secure research funding, collaborate internationally, and publish high-quality work underlines her potential for long-term academic leadership. Recognized through various awards and honors, she has demonstrated excellence not only in individual performance but also in contributing to the broader scientific community through peer review and collaboration. Fluent in multiple languages and culturally adaptive, Dr. Shahbazi brings global perspective and technical depth to every role she undertakes. With a forward-thinking mindset and a commitment to advancing the state of AI, she stands as a strong candidate for high-level recognitions such as the Best Researcher Award and is poised to continue making meaningful contributions to academia and beyond.

Publications Top Notes

  • Title: Integration of blockchain, IoT and machine learning for multistage quality control and enhancing security in smart manufacturing
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2021
    Citations: 187

  • Title: A procedure for tracing supply chains for perishable food based on blockchain, machine learning and fuzzy logic
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2020
    Citations: 140

  • Title: Towards a secure thermal-energy aware routing protocol in wireless body area network based on blockchain technology
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2020
    Citations: 123

  • Title: Smart manufacturing real-time analysis based on blockchain and machine learning approaches
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2021
    Citations: 72

  • Title: Toward improving the prediction accuracy of product recommendation system using extreme gradient boosting and encoding approaches
    Authors: Z. Shahbazi, D. Hazra, S. Park, Y.C. Byun
    Year: 2020
    Citations: 68

  • Title: Improving transactional data system based on an edge computing–blockchain–machine learning integrated framework
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2021
    Citations: 64

  • Title: Product recommendation based on content-based filtering using XGBoost classifier
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2019
    Citations: 64

  • Title: Agent-based recommendation in E-learning environment using knowledge discovery and machine learning approaches
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2022
    Citations: 63

  • Title: Fake media detection based on natural language processing and blockchain approaches
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2021
    Citations: 63

  • Title: Improving the cryptocurrency price prediction performance based on reinforcement learning
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2021
    Citations: 60

  • Title: Machine learning-based analysis of cryptocurrency market financial risk management
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2022
    Citations: 58

  • Title: Lithium-ion battery estimation in online framework using extreme gradient boosting machine learning approach
    Authors: S. Jafari, Z. Shahbazi, Y.C. Byun, S.J. Lee
    Year: 2022
    Citations: 58

  • Title: Blockchain-based event detection and trust verification using natural language processing and machine learning
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2021
    Citations: 51

  • Title: Knowledge discovery on cryptocurrency exchange rate prediction using machine learning pipelines
    Authors: Z. Shahbazi, Y.C. Byun
    Year: 2022
    Citations: 42

  • Title: Lithium-ion battery health prediction on hybrid vehicles using machine learning approach
    Authors: S. Jafari, Z. Shahbazi, Y.C. Byun
    Year: 2022
    Citations: 36

Shishir Tewari | Computer Science | Technology and Innovation Leadership Award

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Mr. Shishir Tewari | Computer Science | Technology and Innovation Leadership Award

Senior Manager, Data Engineering at Procore Technologies, United States

Shishir Tewari is a seasoned technology leader with over 19 years of experience driving innovation in data engineering, data warehousing, and analytics across top-tier organizations such as Google, Amazon, Morgan Stanley, and Microsoft. He currently leads strategic data initiatives at Procore Technologies, where he has spearheaded the development of AI/ML-driven platforms, cloud migrations, and real-time analytics systems. Known for his expertise in building scalable, high-performance data solutions, Shishir has successfully led global engineering teams and transformed complex data ecosystems on AWS, GCP, and Databricks. His technical vision, operational excellence, and commitment to data quality and governance have consistently delivered measurable business value. Shishir’s continuous pursuit of innovation and deep cross-functional leadership make him a standout contributor in the technology landscape. With a strong foundation in data science, cloud architecture, and team mentorship, he exemplifies the qualities of a forward-thinking, impact-driven technology leader worthy of recognition.

Professional Profile 

Google Scholar

Education

Shishir Tewari holds a Bachelor of Technology in Information Technology from U.P.T.U., India, graduating in 2006. Demonstrating a commitment to lifelong learning and innovation, he further enhanced his credentials with a specialization in Data Science and Analytics from Rutgers University, New Jersey, in 2018–2019. This advanced academic training equipped him with modern analytical techniques, machine learning algorithms, and statistical modeling—skills that have been instrumental in his professional success. His educational background lays a strong foundation for his technical leadership, blending theoretical knowledge with real-world application. The combination of engineering fundamentals and data science expertise positions Shishir as a well-rounded technology leader who can bridge the gap between innovation and implementation in enterprise environments.

Professional Experience

Shishir Tewari brings over 19 years of robust experience across global technology firms, including Google, Amazon, Morgan Stanley, Microsoft, and currently, Procore Technologies. His career spans technical leadership, large-scale data architecture, and cloud-native platform innovation. At Google, he led a global team optimizing financial data pipelines and infrastructure. At Amazon, he designed high-performance advertising data systems, enabling substantial revenue impact. At Procore, he has driven major initiatives including AI/ML-powered data platforms and cloud migrations. His ability to manage large engineering teams, align data strategy with business goals, and optimize performance at scale reflects his leadership maturity. Shishir’s diverse experience across industries—finance, tech, construction, and advertising—gives him a unique, cross-sector perspective on data-driven transformation.

Research Interest

Shishir Tewari’s research interests lie at the intersection of big data engineering, AI/ML-driven analytics, and cloud computing. He is particularly passionate about optimizing large-scale data systems for performance, governance, and real-time decision-making. With practical expertise in cloud platforms like AWS, GCP, and Databricks, his focus is on leveraging modern data stacks and open-source technologies to power next-generation analytics and automation. He is also interested in the application of machine learning for master data management, anomaly detection, and predictive modeling within business intelligence ecosystems. While not rooted in academic publishing, his work consistently applies research principles to solve real-world business problems, delivering measurable impact. Future interests include exploring the integration of generative AI with enterprise data platforms and advancing data democratization through self-service analytics tools.

Award and Honor

While specific awards and honors are not listed in his profile, Shishir Tewari’s consistent elevation to senior technical and leadership roles in globally respected organizations serves as a testament to his excellence and recognition within the industry. Being entrusted with mission-critical projects at Google, Amazon, and Morgan Stanley speaks to his reliability, vision, and execution skills. His role in leading high-visibility initiatives such as financial data certification, AI/ML-driven analytics platforms, and major cloud migrations reflects the high degree of trust and credibility he commands. He has likely received internal accolades for his contributions to performance optimization, cost reduction, and innovation. A nomination for a Technology and Innovation Leadership Award would further formalize and honor his significant contributions to data-driven transformation and technological advancement in enterprise settings.

Conclusion

Shishir Tewari exemplifies the qualities of a forward-thinking technology leader, with deep expertise in data engineering, cloud architecture, and strategic innovation. His two-decade-long career reflects a commitment to excellence, from hands-on development to executive-level leadership. With advanced training in data science, he brings both theoretical rigor and practical vision to his work. His impactful roles at top-tier organizations demonstrate his ability to lead cross-functional teams, optimize large-scale systems, and implement transformative technologies. Passionate about leveraging AI/ML and cloud platforms to drive business value, Shishir’s professional journey is marked by continuous learning and measurable outcomes. He stands out as a prime candidate for recognition through a Technology and Innovation Leadership Award, not only for his technical contributions but also for his ability to inspire, mentor, and lead organizations into the future of data-driven innovation.

Publications Top Notes

  1. Title: AI Powered Data Governance – Ensuring Data Quality and Compliance in the Era of Big Data
    Authors: S. Tewari
    Year: 2025

  2. Title: Operationalizing Explainable AI in Business Intelligence: A Blueprint for Transparent Enterprise Analytics
    Authors: A. Chitnis, S. Tewari
    Year: 2024

  3. Title: AI and Multi-Cloud Compliance: Safeguarding Data Sovereignty
    Authors: S. Tewari, A. Chitnis
    Year: 2024

  4. Title: Scalable Metadata Management in Data Lakes Using Machine Learning
    Authors: S. Tewari
    Year: 2023
    Citation: (Update needed)

  5. Title: AI-Powered Financial Forecasting: Enhancing Accuracy with Machine Learning in Enterprise System
    Authors: S. Tewari
    Year: 2023)

  6. Title: Detecting Data Drift and Ensuring Observability with Machine Learning Automation
    Authors: A. Chitnis, S. Tewari
    Year: 2022

  7. Title: Anomaly Detection in Large Scale Data Platforms with Machine Learning
    Authors: S. Tewari
    Year: 2022

  8. Title: Leveraging Graph Based Machine Learning to Analyze Complex Enterprise Data Relationships
    Authors: S. Tewari, A. Chitnis
    Year: 2021

Oleg Morozov | Engineering | Best Researcher Award

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Prof. Oleg Morozov | Engineering | Best Researcher Award

Professor at Kazan National Research Technical University n.a. A.N. Tupolev-KAI, Russia

Prof. Oleg G. Morozov is a distinguished academic and researcher in the field of microwave photonics and fiber optic sensor technology. Born on October 30, 1960, in Kazan, Tatarstan, Russia, he has made significant contributions to both fundamental and applied aspects of electrodynamics and photonics. With a professional career spanning over four decades, Prof. Morozov has held various high-impact academic and administrative positions at Kazan National Research Technical University named after A.N. Tupolev-KAI. He is known for his leadership in advancing research at the intersection of electronics, photonics, and cyber-physical systems. His work has been central to establishing several key academic departments and research labs, and he is currently the Head of the IT-COM Department. In addition to his academic duties, he serves as the Chief Editor of the journal Electronics, Photonics and Cyber-Physical Systems. He is widely respected for both his scientific rigor and leadership in research development.

Professional Profile

Education

Prof. Morozov pursued his early higher education in radiotechnics, graduating as an Engineer in 1983 from the Tupolev Aviation Institute in Kazan. Demonstrating academic excellence and deep technical curiosity, he completed his Ph.D. in 1987, focusing on advanced topics in applied physics and communication systems. Further solidifying his standing in the academic community, he earned the prestigious Doctor of Technology degree in 2004 from Kazan National Research Technical University named after A.N. Tupolev-KAI. His educational journey is characterized by a strong foundation in electronics, microwave engineering, and photonics—fields that have informed his research career. Throughout his academic progression, Prof. Morozov has stayed closely involved with evolving technological disciplines, often integrating cross-disciplinary approaches in his teaching and research. His educational background has equipped him not only with in-depth technical knowledge but also with a strategic vision for technology’s role in science and innovation, particularly within the Russian higher education landscape.

Professional Experience

Prof. Morozov’s professional experience is marked by a series of leadership roles within Kazan National Research Technical University. From 1989 to 1993, he was the Head of the Quantum Electronics and Laser Technology R&D Lab, where he initiated numerous pioneering projects. Later, between 2005 and 2014, he led the TV and Multimedia Systems Department, focusing on advancements in signal processing and integrated media technologies. From 2014 to 2023, he served as the Head of the Radiophotonics and Microwave Technology Department, strengthening the university’s position in cutting-edge research. In parallel, he also directed the R&D Institute of Applied Electrodynamics, Photonics, and Life Systems from 2012 to 2021, where he supervised multidisciplinary research teams. Currently, he is a Professor and Head of the IT-COM Department. His professional path reflects a consistent commitment to innovation, interdisciplinary research, and fostering academic excellence in emerging technological domains.

Research Interests

Prof. Morozov’s research interests lie primarily in microwave photonics, fiber optic sensors, and radiophotonic interrogation techniques. His work bridges theoretical innovation and applied research, especially in high-frequency signal processing, quantum electronics, and cyber-physical system integration. He has contributed significantly to the development of advanced sensing technologies, optical communication systems, and integrated photonic devices. His research also explores the role of photonics in healthcare and smart systems, showing an ability to adapt traditional fields to modern technological challenges. Prof. Morozov has consistently aimed to merge physical sciences with engineering applications, contributing to both national and international scientific communities. His leadership in these areas has resulted in a number of collaborative projects and publications that have advanced the state of the art in photonics and related technologies. He also emphasizes system-level thinking, where electronics, optics, and digital technologies converge to build intelligent and adaptive sensing solutions for next-generation applications.

Awards and Honors

Throughout his illustrious career, Prof. Morozov has received numerous awards and honors recognizing his research excellence and academic contributions. Most notably, he was awarded the Frish Medal by the Russian Optical Society (ROS), a prestigious accolade for contributions to optical science and technology. He holds the Senior Member status in three leading professional organizations—IEEE, SPIE, and OSA—which reflects his recognized expertise and longstanding service to the global scientific community. Beyond personal awards, his editorial roles, including Guest and Board Editor positions with IntechOpen and MDPI journals, highlight his influence on the broader research discourse. Currently, he serves as the Chief Editor of the journal Electronics, Photonics and Cyber-Physical Systems, further solidifying his thought leadership in the field. These honors not only affirm his past achievements but also position him as a central figure in shaping future advancements in photonic systems and applied electrodynamics.

Conclusion

Prof. Oleg G. Morozov is highly suitable for the Best Researcher Award due to his long-standing and impactful career in cutting-edge technologies, particularly in photonics and microwave systems. His leadership roles, academic achievements, and recognition by esteemed global societies reinforce his strong candidacy.

Publications Top Notes

  • Title: Superstructured Addressable Fiber Bragg Structures

    • Authors: B. Valeev, R.A. Makarov, T.A. Agliullin, A.Z. Sakhabutdinov, O.G. Morozov

    • Year: 2025

    • Citations: 0

  • Title: OAM Mode Propagation and Supercontinuum Generation in a Nested Photonic Crystal Fiber

    • Authors: S. Punia, A. Saharia, Y. Ismail, G.L. Singh, M. Tiwari

    • Year: 2025

    • Citations: 0

  • Title: A Design of Nested Photonic Crystal Fiber for OAM Mode Propagation (Conference Paper)

    • Authors: S. Punia, A. Saharia, Y. Ismail, G.L. Singh, M. Tiwari

    • Year: Not specified

    • Citations: 0

  • Title: Microscopic Temperature Sensor Based on End-Face Fiber-Optic Fabry–Perot Interferometer

    • Authors: M. Chesnokova, D.I. Nurmuhametov, R.S. Ponomarev, O.G. Morozov, R.A. Makarov

    • Year: 2024

    • Citations: 2

  • Title: Design and Performance Analysis of a Novel Hoop-Cut SPR-PCF Sensor for High Sensitivity and Broad Range Sensing Applications

    • Authors: S. Mittal, A. Saharia, Y. Ismail, M. Tiwari, S. Kumar

    • Year: 2024

    • Citations: 12

  • Title: Ontology of Addressed Fiber Bragg Structures as a New Type of Sensor Elements (Conference Paper)

    • Authors: O.G. Morozov, A.Z. Sakhabutdinov

    • Year: Not specified

    • Citations: 0

  • Title: A Six-Core Microstructured Fiber for Sensing Applications (Conference Paper, repeated thrice)

    • Authors: A. Agarwal, S. Mittal, S. Punia, G.L. Singh, M. Tiwari

    • Year: Not specified

    • Citations: 0

  • Title: Modeling of Multi-Layer Fiber-Optic Fabry–Perot Interferometer as a Sensing Element of Humidity, Pressure and Temperature

    • Authors: A.Z. Sakhabutdinov, T.A. Agliullin, B. Valeev, O.G. Morozov, S.M. Hussein

    • Year: Not specified

    • Citations: 0