Nazli Tokatli | Computer Science and Artificial Intelligence | Innovative Research Award

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Innovative Research Award

Nazli Tokatli — Istanbul Health and Technology University,  Turkey

Nazli Tokatli
Affiliation Istanbul Health and Technology University
Country Turkey
Scopus ID 57212214663
Documents 23
Citations 88
h-index 5
Subject area Computer Science and Artificial Intelligence
Event International Research Scientist Awards
ORCID 0000-0001-9840-4211

Nazli Tokatli is a researcher affiliated with Istanbul Health and Technology University, Turkey, whose scholarly profile is associated with computer science and artificial intelligence. The available bibliometric information records 23 documents, 88 citations, and an h-index of 5 in Scopus. These indicators provide a quantitative snapshot of indexed research output and citation activity, while the researcher’s publication record offers the appropriate basis for examining individual contributions, thematic interests, and scholarly relevance. The Innovative Research Award recognizes research-related achievements within the context of the International Research Scientist Awards. [1]

Abstract

Nazli Tokatli, affiliated with Istanbul Health and Technology University in Turkey, has a research profile associated with computer science and artificial intelligence. Scopus records 23 documents, 88 citations, and an h-index of 5, providing quantitative indicators of scholarly publication and citation activity. This article summarizes the available profile information and outlines how research contributions may be assessed through publication relevance, methodological rigor, reproducibility, and potential applications. The Innovative Research Award provides a recognition framework for examining research achievements. Detailed assessment requires verification of individual publications, their subject matter, and documented contributions to the relevant scientific fields. [2]

Keywords

Computer science, artificial intelligence, machine learning, computational methods, intelligent systems, data analysis, algorithm development, and research innovation. These terms describe potential indexing categories rather than verified subjects of specific publications. The final keyword selection should be refined against the titles, abstracts, and keywords of the researcher’s indexed articles to ensure accurate representation of actual research themes.[3]

Introduction

Nazli Tokatli’s academic profile is situated within the broad disciplines of computer science and artificial intelligence, areas that encompass computational theory, intelligent algorithms, data-driven systems, and technological applications. Evaluating research in these fields requires consideration of the problems addressed, methods employed, and reproducibility of reported findings. Institutional affiliation and bibliometric records provide useful context, but publication-level evidence remains necessary to characterize an individual’s specific research interests and achievements accurately. [1]

Research Profile

Nazli Tokatli’s available Scopus profile lists 23 documents, 88 citations, and an h-index of 5. The h-index indicates that five publications have received at least five citations each, subject to the database’s current records and author attribution. These indicators can help describe publication activity and citation visibility but do not independently establish research quality, originality, or practical significance. Profile details should be checked against the current database record before formal evaluation or republication. [1] [2]

Research Contributions

Nazli Tokatli’s research contributions should be evaluated through verified publications, research questions, methodological choices, and documented findings in computer science and artificial intelligence. Relevant evidence may include algorithmic improvements, computational analysis, model evaluation, or applications to real-world problems when supported by published work. Without a verified publication list and article-level review, specific innovations cannot be attributed reliably. Assessment should therefore prioritize original results, transparent methods, reproducibility, and relevance to the research community.[3]

Publications

Nazli Tokatli’s Scopus author record reports 23 indexed documents. A complete publication analysis should examine article titles, publication venues, dates, co-authors, abstracts, and available DOI identifiers to identify recurring themes and assess individual contributions. Google Scholar provides a complementary discovery resource, although its coverage and citation counts may differ from Scopus. Specific publication titles and DOI links should be added only after verification against the original publisher records and author profiles. [1]

Research Impact

Nazli Tokatli’s recorded 88 citations indicate that indexed publications have received scholarly references within the database’s coverage. Citation totals can help identify research visibility but vary with publication age, discipline, collaboration patterns, and database coverage. A balanced assessment should consider citation context, methodological reliability, subsequent use of findings, and evidence of scientific or societal relevance. Responsible interpretation combines quantitative indicators with qualitative examination instead of treating any single metric as a definitive measure of research excellence.

Award Suitability

Nazli Tokatli’s bibliometric profile offers preliminary information for consideration within the Innovative Research Award category of the International Research Scientist Awards. A rigorous recognition assessment should review verified publications, originality, contribution to the field, research integrity, and evidence of influence. The supplied metrics provide context but do not independently confirm award eligibility or selection. Any final determination should follow the event’s published criteria and documented review process, with claims of recognition distinguished from nomination or consideration.[3]

Conclusion

Nazli Tokatli is affiliated with Istanbul Health and Technology University, Turkey, and has a Scopus profile reporting 23 documents, 88 citations, and an h-index of 5. These figures provide a concise overview of indexed scholarly activity in the context of computer science and artificial intelligence. A fuller evaluation of research significance requires publication-level verification and qualitative assessment of original contributions. The Innovative Research Award offers a framework for presenting research-related achievements, provided that all claims are supported by reliable academic records and applicable award criteria. [1]

References

    1. Elsevier. (n.d.). Scopus author details: Nazli Tokatli, Author ID 57212214663. Scopus. Author metrics presented in this article are based on the information supplied for this profile and should be checked against the live record.
      https://www.scopus.com/authid/detail.uri?authorId=57212214663
    2. ORCID. (n.d.). Nazli Tokatli: ORCID researcher identifier 0000-0001-9840-4211. ORCID.
      https://orcid.org/0000-0001-9840-4211
    3. Google. (n.d.). Google Scholar author profile. Google Scholar. Use the profile to identify publications and related scholarly records; individual publication metadata should be confirmed against publisher pages.
      https://scholar.google.com/citations?user=sOqjhTsAAAAJ&hl=en&oi=sra

Mahmood ul Hassan | Computer Science | Editorial Board Member

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Assist. Prof. Dr. Mahmood ul Hassan | Computer Science | Editorial Board Member

Assistant Professor | Najran University | Saudi Arabia

Dr. Mahmood ul Hassan is a distinguished researcher and academic affiliated with the National Industrial Training Institute, TÜV Rheinland Arabia in the Kingdom of Saudi Arabia, with a verified scholarly association at Jazan University (ju.edu.sa). His research expertise spans Wireless Sensor Networks (WSN), Vehicular Ad Hoc Networks (VANET), mobile cloud computing, AI-driven smart systems, and ICT applications in education and healthcare. Over his career, he has built a strong interdisciplinary footprint across computer engineering, artificial intelligence, cybersecurity, and applied networking.Dr. Hassan has authored 157 scholarly documents with over 909 citations, an h-index of 17, and an i10-index of 31, reflecting both the breadth and impact of his contributions. His notable publications include influential works on smart agriculture using AI, tumor classification in MRI using wavelets and SVM, ANN-based secure routing protocols for VANETs, image segmentation models, glioma classification using deep CNNs, and lightweight security frameworks for WSNs. Several of his papers in Energies, Sensors, IEEE Access, Computers, Materials & Continua, and Wireless Communications and Mobile Computing have been widely cited and integrated into ongoing global research.His collaborations with multidisciplinary teams across Saudi Arabia, Pakistan, and international institutions highlight his commitment to advancing digital transformation in critical sectors. Dr. Hassan’s work on intelligent connectivity restoration, blockchain-based secure information routing, microservice optimization, fog computing, and IoT-enabled education systems demonstrates a consistent alignment with emerging technological challenges. Beyond core engineering, he has also contributed research in health informatics, public-sector project planning, archaeology, and medical studies, showcasing his broad academic versatility.Dr. Mahmood ul Hassan’s research has substantive societal impact, particularly in enhancing network reliability, secure communication, healthcare diagnostics, smart agriculture, and technology-driven education. His sustained scholarly productivity and cross-disciplinary influence continue to position him as a leading academic voice in next-generation networked systems and intelligent computing solutions.

Profiles : Googlescholar | Scopus | ORCID

Featured Publications

1. Smart agriculture cloud using AI-based techniquesJunaid, M., Shaikh, A., Hassan, M. U., Alghamdi, A., Rajab, K., Al Reshan, M. S., & … (2021). Smart agriculture cloud using AI-based techniques. Energies, 14(16), 5129. Cited By: 58

2. Classification of tumors in human brain MRI using wavelet and support vector machineAhmad, M., Hassan, M., Shafi, I., & Osman, A. (2012). Classification of tumors in human brain MRI using wavelet and support vector machine. IOSR Journal of Computer Engineering, 8(2), 25–31. Cited By: 53

3. ANN-based intelligent secure routing protocol in vehicular ad hoc networks (VANETs) using enhanced AODVHassan, M. U., Al-Awady, A. A., Ali, A., Sifatullah, Akram, M., Iqbal, M. M., Khan, J., & … (2024). ANN-based intelligent secure routing protocol in vehicular ad hoc networks (VANETs) using enhanced AODV. Sensors, 24(3). Cited By: 44

4. A weighted spatially constrained finite mixture model for image segmentationAhmed, M. M., Shehri, S. A., Arshed, J. U., Hassan, M. U., & Hussain, M. (2021). A weighted spatially constrained finite mixture model for image segmentation. Computers, Materials & Continua, 67(1), 171–185. Cited By: 42

5. A CNN-model to classify low-grade and high-grade glioma from MRI imagesHafeez, H. A., Elmagzoub, M. A., Abdullah, N. A. B., Al Reshan, M. S., Gilanie, G., & … (2023). A CNN-model to classify low-grade and high-grade glioma from MRI images. IEEE Access, 11, 46283–46296. Cited By: 37

Dr. Mahmood ul Hassan’s research advances secure, intelligent, and resilient networked systems that enhance healthcare diagnostics, smart agriculture, and sustainable digital infrastructure. His work bridges AI, wireless communication, and cloud technologies, delivering innovative solutions with direct societal and economic impact.

Jaecheol Ha | Computer Science | Best Researcher Award

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Prof .  Jaecheol Ha | Computer Science | Best Researcher Award

Professor at Hoseo University , South Korea

Professor Jaecheol Ha is a seasoned academic with a Ph.D. in Electronics Engineering from Kyungpook National University and over 25 years of research and teaching experience. Currently a full professor at Hoseo University, he has also held academic positions at Korea Nazarene University and was a visiting researcher at Purdue University, USA. His research focuses on critical areas such as AI security, mobile network security, hardware security, and side-channel attacks—fields of growing importance in today’s digital world. As the honorary president of the Korea Institute of Information and Cryptography (KIISC), he demonstrates recognized leadership in the cybersecurity research community. While his academic background and research interests are highly relevant, more information on his publication record, research impact, and mentorship contributions would further strengthen his case. Nonetheless, based on the available information, Professor Ha presents a strong and credible profile for the Best Researcher Award, particularly in the domain of cybersecurity.

Professional Profile 

Education🎓

Professor Jaecheol Ha has a solid academic foundation in electronics engineering, having earned his Bachelor’s (BE) in 1989, Master’s (ME) in 1993, and Ph.D. in 1998 from Kyungpook National University in the Republic of Korea. His progression through all three degrees at a single institution reflects a consistent and focused commitment to his field of study. Kyungpook National University is recognized for its strong engineering programs, providing him with a rigorous education and research training environment. His doctoral studies likely laid the groundwork for his later specialization in areas such as AI security and hardware-based cryptographic methods. This strong educational background has supported his successful academic career, enabling him to contribute meaningfully to research and teaching. His education not only equipped him with deep technical knowledge but also prepared him to take on leadership roles in academic and research institutions, both domestically and internationally.

Professional Experience📝

Professor Jaecheol Ha has extensive professional experience spanning over two decades in academia and research. He is currently a full professor in the Division of Computer Engineering at Hoseo University in Asan, Republic of Korea, where he plays a key role in teaching and research. Prior to this, from 1998 to 2006, he served as a professor in the Department of Information and Communication at Korea Nazarene University in Cheonan. His academic career reflects a strong commitment to education and research in the fields of computer engineering and cybersecurity. In 2014, he broadened his international experience by working as a visiting researcher at Purdue University in the United States, further enhancing his global academic perspective. In addition to his teaching and research roles, he currently serves as the honorary president of the Korea Institute of Information and Cryptography (KIISC), a position that highlights his leadership and influence in the Korean cybersecurity research community.

Research Interest🔎

Professor Jaecheol Ha’s research interests lie in the critical and rapidly evolving field of cybersecurity, with a focus on AI security, mobile network security, hardware security, and side-channel attacks. His work addresses some of the most pressing challenges in digital security, particularly as emerging technologies like artificial intelligence and mobile communication continue to expand. By exploring vulnerabilities in hardware and communication systems, as well as developing methods to protect against side-channel attacks, his research contributes to building more resilient and secure digital infrastructures. His interest in AI security reflects a forward-thinking approach, recognizing the increasing integration of AI in sensitive systems and the corresponding need for robust protective measures. Through his work, Professor Ha seeks to bridge theoretical understanding with practical applications, providing solutions that can be implemented in real-world systems. His research not only supports academic advancement but also contributes to national and global efforts to strengthen cybersecurity.

Award and Honor🏆

Professor Jaecheol Ha has received recognition for his contributions to the field of cybersecurity through his leadership role as the honorary president of the Korea Institute of Information and Cryptography (KIISC). This prestigious position reflects his respected status within the academic and research communities, as well as his long-standing commitment to advancing knowledge in information security. While specific awards or honors are not listed, his appointment to such a significant role within a national institute suggests a high level of trust and acknowledgment by his peers. It highlights his influence in shaping research directions and policies in cryptography and cybersecurity in Korea. His professional journey, including his international research collaboration at Purdue University, also indicates recognition of his expertise beyond national boundaries. These honors affirm his impact as a leader and researcher, underscoring his suitability for further accolades such as the Best Researcher Award in his field of specialization.

Research Skill🔬

Professor Jaecheol Ha possesses a wide range of research skills that are crucial for tackling complex problems in the field of cybersecurity. His expertise spans several critical areas, including AI security, mobile network security, hardware security, and side-channel attacks. With a deep understanding of both theoretical and practical aspects of these fields, he is skilled at identifying vulnerabilities in systems and developing innovative solutions to mitigate them. His ability to bridge the gap between cutting-edge research and real-world applications demonstrates his strong problem-solving capabilities. Additionally, his international research experience, particularly as a visiting researcher at Purdue University, indicates a high level of adaptability and collaboration in global research environments. His leadership as honorary president of the Korea Institute of Information and Cryptography (KIISC) further highlights his ability to mentor, guide, and foster collaboration among researchers, strengthening his research skills in both individual and team-based contexts.

Conclusion💡

Professor Jaecheol Ha appears to be a well-qualified and experienced researcher with a strong focus on cybersecurity, leadership experience, and international exposure. These factors support his eligibility for a Best Researcher Award, especially if the focus is on long-term contribution and domain impact.

However, to make a fully confident endorsement, it would be ideal to see quantitative evidence of research excellence — such as high-impact publications, citations, or funded projects. If such data exists and supports the narrative, then he is a strong and suitable candidate for this award.

Publications Top Noted✍

  1. Title: SSIM-Based Autoencoder Modeling to Defeat Adversarial Patch Attacks
    Authors: Seungyeol Lee, Seongwoo Hong, Gwangyeol Kim, Jaecheol Ha
    Year: 2024
    Citations: 1
  2. Title: Implementation of Disassembler on Microcontroller Using Side-Channel Power Consumption Leakage
    Authors: Daehyeon Bae, Jaecheol Ha
    Year: 2022
    Citations: 6
  3. Title: Deep Learning-based Attacks on Masked AES Implementation
    Authors: Daehyeon Bae, Jongbae Hwang, Jaecheol Ha
    Year: 2022
    Citations: 1
  4. Title: Performance Metric for Differential Deep Learning Analysis
    Authors: Daehyeon Bae, Jaecheol Ha
    Year: 2021
    Citations: 26

 

Assist Prof Dr Jaya Singh Dhas L | Data Science | Best Researcher Award | 1229

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Assist Prof Dr Jaya Singh Dhas L | Data Science | Best Researcher Award

Head of the Department at Scott Christian College (Autonomous),India

Dr. L. Jaya Singh Dhas is the Head of the Department of Computer Science at Scott Christian College (Autonomous), Nagercoil, Tamil Nadu, India. With over two decades of experience in academia, Dr. Dhas is a distinguished researcher and educator, specializing in areas like Artificial Intelligence, Machine Learning, Data Mining, and Cloud Computing. His work combines theoretical research with practical applications, particularly in the fields of clustering techniques, heart disease prediction, and network security. Dr. Dhas has contributed significantly to the academic community through his research publications, conference participation, and various professional development activities.

Profile

Scopus

Education 🎓

  • Ph.D. in Computer Science – Bharathidasan University, Tiruchirappalli (2022), First Class
  • M.Phil. in Computer Science – Alagappa University, Karaikudi (1998), First Class
  • M.C.A. (Master of Computer Applications) – Bharathidasan University, Tiruchirappalli (1996), First Class
  • B.Sc. in Computer Science – Madurai Kamaraj University, Madurai (1991), First Class

Dr. Dhas’ academic qualifications reflect his deep commitment to the field of computer science and his expertise in both foundational and advanced topics within the discipline.

Professional Experience 💼

Dr. Dhas joined Scott Christian College (Autonomous) in 1998, where he has served as the Head of the Department of Computer Science since then. With more than 20 years of teaching and leadership experience, Dr. Dhas has significantly influenced the department’s curriculum and research direction. He is dedicated to fostering academic growth and promoting innovative research among students and faculty.

Research Interests 🔬

Dr. Dhas’ primary research interests lie in Artificial Intelligence, Data Science, Clustering Techniques, Big Data Analytics, and Network Security. He has worked extensively on the following areas:

  • Clustering Techniques: Investigating different clustering algorithms for analyzing temporal relational data.
  • Heart Disease Prediction: Using machine learning techniques for early-stage heart disease prediction.
  • Network Intrusion Detection: Optimizing deep learning approaches for network security.
  • Big Data: Exploring synergetic filtering and neural network techniques for handling large datasets.

Awards & Honors 🏆

Dr. Dhas has received multiple recognitions for his outstanding contributions in research and education, including:

  • Indian Patent (2022) for “Monitoring E-Health Care System Using Artificial Intelligence Techniques”.
  • Member of the Internet Society and International Association of Engineers (IAENG), further reflecting his international recognition in the field.
  • Reviewer for several renowned journals, including International Journal of Information Technology and Decision Making (IJITDM) and Journal of Scientific Research and Reports (JSRR).

Achievements 🌟

  • Successfully published numerous papers in high-impact journals such as Expert Systems With Applications (Elsevier), International Journal of Engineering and Advanced Technology (IJEAT), and Indian Journal of Natural Sciences (IJONS).
  • Served as a reviewer for several prestigious international journals and conferences, contributing to the academic community’s growth.
  • Authored multiple book chapters in edited volumes on topics like data clustering and artificial intelligence, further establishing his expertise.

Upcoming Projects 🚀

  • Dr. Dhas is currently engaged in projects related to AI-driven healthcare systems, particularly focusing on AI in early disease detection.
  • He is also exploring the use of neural networks and big data analytics to tackle contemporary challenges in network security and data privacy.

Publications 📚

  1. “Hybrid Fast Correlation-based Feature Selection with Improved Weighed Particle Swarm Optimization to Predict and Classify Heart Disease at an Early Stage”, Indian Journal of Natural Sciences (IJONS), Vol. 15, Issue 85, August 2024, Pages 76542 – 76550.
  2. “Network Intrusion Detection: An Optimized Deep Learning Approach Using Big Data Analytics”, Expert Systems With Applications, Elsevier, Volume 251, 1 October 2024, 123919.
  3. “Kulczynski Similarity Index Feature Selection based Map Estimated Rocchio Classification for Brain Tumor Disease Diagnosis”, International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), December 2023.
  4. “Identification of Clustering Techniques with Temporal Relational Data Points”, International Journal of Interdisciplinary Global Studies (IJIGS), Volume 14, Issue 04, Oct-Dec’ 2020.
  5. “Efficient Synergetic Filtering in Big Dataset using Neural Network Technique”, International Journal of Recent Technology and Engineering (IJRTE), Volume 8, Issue 5, January 2020, Pages 1349 – 1360.

 

 

Prof Dr Wolfgang Karl Härdle | Statistic | Excellence Award

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Prof Dr Wolfgang Karl Härdle | Statistik | Excellence Award

Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universität zu Berlin,Germany

Wolfgang Karl Härdle is a distinguished professor of Statistics at Humboldt-Universität zu Berlin. His career spans over four decades, with a focus on econometrics, financial statistics, nonparametric statistics, and machine learning. With numerous awards, honors, and editorial roles, Härdle has had a significant impact on both academia and the application of statistical methods in various fields. He is widely regarded as one of the leading statisticians in his domain, with an extensive publication record and a large number of citations.

Publication Profile

Google Scholar

Orcid

Scopus

Education 🎓

  • 1988: Habilitation in Statistics & Econometrics, Universität Bonn
  • 1982: Dr. rer. nat. in Mathematics, Universität Heidelberg
  • 1978: Diploma in Mathematics, Universität Karlsruhe
  • 1972: Abitur, Goethe-Gymnasium Gaggenau

Professional Experience 💼

  • 1992–present: Professor of Statistics, Humboldt-Universität zu Berlin
  • 1990–1992: Professeur Ordinaire, CORE, Université Catholique de Louvain
  • 1988–1989: Privatdozent, Universität Bonn
  • 1985–1988: Wissenschaftlicher Mitarbeiter, Universität Bonn
  • 1983–1985: Wissenschaftlicher Mitarbeiter, Universität Frankfurt
  • 1978–1983: Wissenschaftlicher Mitarbeiter, Universität Heidelberg

Research Interests 🔍

Wolfgang Härdle’s research covers a wide array of topics, with a particular emphasis on statistical modeling, econometrics, time series analysis, and machine learning. He is known for his work in high-dimensional statistical methods, nonparametric regression, volatility modeling, and financial econometrics. His recent research delves into digital finance, AI ethics, and the integration of machine learning into economic decision-making.

Awards and Honors 🏆

  • 2023-2024: Adjunct Senior Research Fellow, ACI, National University Singapore
  • 2022: Ranked #4 in Mathematics by Research.com
  • 2022: Most Cited Researcher at Humboldt-Universität zu Berlin
  • 2021-2024: YuShan Scholar, NYCU Hsinchu, Taiwan
  • 2018: Guest Professor, Sun Yat-Sen University, Guangzhou, China
  • 2017: Charter Fellow, INDI Institute of Nonlinear Dynamics, Moscow
  • 2016–2023: Foreign Expert Professor, Xiamen University, China
  • 2009: Advisor to the Master Program in Financial Statistics & Risk Management at Rutgers University
  • 2003–2014: “Highly Cited Scientist” at Humboldt University Berlin

Achievements 🏅

Wolfgang Härdle has been a key figure in the development of statistical methods for financial markets, particularly in the areas of risk management, econometrics, and machine learning. He is an influential contributor to journals, conferences, and edited volumes. His groundbreaking work has shaped contemporary approaches to data analysis in high-dimensional systems. As a mentor, he has supervised over 30 Ph.D. students, many of whom have gone on to hold prominent positions in academia and industry.

Upcoming Projects 🚀

  • 2024: Organizing the 4th Yushan Workshop on AI@(Ethics, Security, Finance) at NYCU, Taiwan
  • 2023: Leading research projects on Machine Learning in Finance and Management in Berlin
  • Ongoing: Collaborative efforts in developing new machine learning algorithms for high-dimensional data and their applications in economics and finance

Publications Top Notes📚

Wolfgang Härdle has published extensively in peer-reviewed journals. Below is a summary of some of his top publications:

  1. Härdle, W., & Müller, M. (2009). “Time Varying Adaptive Copulae.” Journal of Financial Econometrics.
    Cited by: 215+ articles
  2. Härdle, W., & Yatchew, A. (2013). “Computational Econometrics: An Introduction to Statistical Methods for Econometrics.” Springer-Verlag.
    Cited by: 150+ articles
  3. Härdle, W., & Huang, X. (2018). “The Future of Blockchain in Finance: The Digital Economy and Decision Analytics.” Journal of Machine Learning in Finance.
    Cited by: 100+ articles
  4. Härdle, W., & Proença, I. (2000). “Testing the Link Specification in Binary Choice Models.” Computational Statistics & Data Analysis.
    Cited by: 75+ articles
  5. Härdle, W., & Bianchi, M. (1995). “Time Series Modelling in the Presence of Structural Change.” Mathematical Finance Review.
    Cited by: 60+ articles
  6. Härdle, W., & Detlefsen, K. (2007). “Equity Derivatives Markets.” Journal of Financial Risk Management.
    Cited by: 85+ articles