Yuyan Zheng | Computer Science | Innovative Research Award

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Innovative Research Award

Yuyan Zheng
Shandong Normal University
Yuyan Zheng
Affiliation Shandong Normal University
Country China
Scopus ID 55869455100
Documents 15
Citations 91
h-index 5
Subject Area Computer Science
Event Computer Science
ORCID 0000-0002-5639-928X

The Innovative Research Award recognizes scholarly excellence demonstrated through impactful scientific contributions, sustained publication activity, and measurable research influence. Yuyan Zheng of Shandong Normal University has established a developing research profile supported by peer-reviewed publications and scholarly citations within the field of Computer Science. The following article presents a structured overview of the researcher’s academic profile, research achievements, publication record, scholarly influence, and suitability for recognition through an international research award, supported by publicly available academic sources.[1]

Abstract

This article presents an overview of the academic accomplishments of Yuyan Zheng, a researcher affiliated with Shandong Normal University, whose work contributes to the advancement of Computer Science. The profile highlights publication performance, citation metrics, collaborative research activities, and measurable scholarly influence based on publicly available academic records. Through peer-reviewed research and continuing scientific engagement, the researcher has demonstrated steady academic development within the international research community. The documented achievements illustrate growing research visibility and support consideration for professional recognition through the Innovative Research Award while reflecting commitment to scientific quality, collaboration, innovation, and continued academic excellence worldwide.[1]

Keywords

Computer Science, Artificial Intelligence, Machine Learning, Research Innovation, Scientific Publications, Citation Analysis, Academic Recognition, Scholarly Impact.

Introduction

Modern scientific research increasingly depends upon interdisciplinary collaboration, reproducible methodologies, and measurable scholarly outcomes. Researchers are evaluated through publication quality, citation performance, collaborative networks, and contributions to advancing knowledge. Academic recognition programs acknowledge these achievements while encouraging continued innovation and international scientific engagement across diverse areas of Computer Science.[2]

Research Profile

Yuyan Zheng is affiliated with Shandong Normal University and has developed a research portfolio reflected by fifteen indexed publications, ninety-one citations, and an h-index of five. These indicators demonstrate consistent academic activity while illustrating increasing recognition among researchers working within Computer Science and related interdisciplinary domains.[1]

Research Contributions

The research contributions emphasize scientifically validated methodologies, collaborative investigations, and publication of peer-reviewed findings that support technological advancement. Continued participation in academic research reflects an ongoing commitment to addressing contemporary computational challenges while promoting knowledge dissemination through recognized scholarly communication channels and interdisciplinary cooperation.[2]

Publications

The documented publication record includes articles indexed within internationally recognized scholarly databases. These publications collectively demonstrate sustained research productivity and contribute to citation growth while enhancing scientific visibility. The research outputs support continued academic development and provide evidence of participation in internationally accessible scientific literature.[1]

Research Impact

Citation metrics indicate that published research has received measurable scholarly attention from the wider academic community. Combined with publication output and collaborative activities, these indicators suggest increasing research visibility and meaningful scientific engagement, supporting continued influence within Computer Science and associated interdisciplinary research environments.[1]

Award Suitability

The documented academic achievements, publication consistency, citation performance, and institutional affiliation collectively indicate qualifications appropriate for consideration within the Innovative Research Award. Recognition through such an award would acknowledge sustained scholarly contributions while encouraging future research excellence and continued participation in international scientific collaboration.[2]

Conclusion

Yuyan Zheng has established a developing academic profile characterized by consistent publication activity, measurable citation impact, and contributions to Computer Science research. The available scholarly indicators support recognition of ongoing scientific achievement while demonstrating continued commitment to high-quality research, collaboration, and international academic advancement.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Yuyan Zheng, Author ID 55869455100. Scopus.
    https://www.scopus.com/pages/authors/55869455100
  2. Applied Sciences. (2024.).StructSim:Meta-Structure-Based Similarity Measure in Heterogeneous Information Networks.
    https://doi.org/10.3390/app14020935
  3. ORCID. (n.d.). Yuyan Zheng researcher profile.
    https://orcid.org/0000-0002-5639-928X

Mingyu Fan | Computer Science | Innovative Research Award

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Innovative Research Award

Mingyu Fan
Donghua University
Mingyu Fan
Affiliation Donghua University
Country China
Scopus ID 36742801900
Documents 60
Citations 1,595
h-index 19
Subject Area Computer Science
Event International Invention Awards
ORCID 0000-0002-0492-4708

Mingyu Fan is a computer science researcher affiliated with Donghua University whose scholarly activities encompass human-computer interaction, intelligent systems, user experience, and emerging computing technologies. His publication record, citation performance, and sustained research productivity demonstrate meaningful academic influence across interdisciplinary computing research. These achievements provide an appropriate foundation for consideration within the Innovative Research Award presented through the International Invention Awards, recognizing sustained scientific contributions supported by internationally indexed scholarly outputs.[1]

Abstract

Mingyu Fan has established a consistent research portfolio within computer science through investigations involving human-computer interaction, intelligent interfaces, user-centered design, and digital innovation. His publications demonstrate methodological rigor, interdisciplinary collaboration, and practical relevance while contributing to internationally indexed scientific literature. Citation performance and publication productivity indicate sustained scholarly influence across multiple research communities. These characteristics align with the objectives of the Innovative Research Award by highlighting measurable academic excellence, continuing research development, knowledge dissemination, and meaningful scientific impact that supports technological advancement and future innovation within contemporary computing disciplines.[1][2]

Keywords

Computer Science, Human-Computer Interaction, Intelligent Systems, User Experience, Artificial Intelligence, Digital Innovation, Research Impact, Scholarly Publications.

Introduction

Computer science continues to evolve through interdisciplinary research integrating intelligent technologies with practical human applications. Mingyu Fan has contributed to this progression by publishing studies that investigate interactive computing environments, digital experiences, and innovative computational methodologies. His work reflects continuous engagement with internationally recognized research communities and contributes to the advancement of knowledge through peer-reviewed scientific dissemination.[1]

Research Profile

Affiliated with Donghua University, Mingyu Fan maintains an active research profile characterized by internationally indexed publications, collaborative investigations, and measurable citation performance. His documented scholarly record demonstrates sustained productivity while addressing contemporary computing challenges through empirical studies that combine technological innovation with user-centered perspectives across diverse academic research environments.[1]

Research Contributions

Research contributions from Mingyu Fan encompass interactive technologies, intelligent computing, usability evaluation, and digital innovation methodologies. His publications demonstrate practical applicability alongside theoretical development, encouraging improvements in computational systems that enhance user engagement and technological effectiveness. Collaborative research further broadens the interdisciplinary significance and academic visibility of these scientific achievements.[3]

Publications

The researcher’s publication portfolio includes sixty indexed scholarly documents covering computer science topics with emphasis on emerging technologies, human-centered computing, and intelligent digital systems. These publications have accumulated significant citation recognition while demonstrating consistent research productivity and sustained participation within reputable international journals and conference proceedings.[1]

Research Impact

With more than one thousand five hundred citations and an h-index of nineteen, Mingyu Fan’s scholarly influence reflects sustained recognition by the international research community. These bibliometric indicators demonstrate continuing relevance, knowledge transfer, and meaningful engagement across multiple computing disciplines while supporting future scientific exploration and collaborative innovation.[1][4]

Award Suitability

The documented academic achievements, publication productivity, international citations, and sustained research engagement position Mingyu Fan as an appropriate candidate for consideration within the Innovative Research Award. The demonstrated combination of scientific productivity, measurable research influence, interdisciplinary collaboration, and continuing innovation corresponds closely with the evaluation principles commonly associated with international academic recognition programs.[5]

Conclusion

Mingyu Fan’s research profile illustrates a sustained commitment to advancing computer science through impactful publications, interdisciplinary collaboration, and internationally recognized scholarly contributions. His academic achievements, supported by measurable bibliometric indicators and continued scientific engagement, provide a balanced basis for recognition through the Innovative Research Award under the International Invention Awards program.[1]

References

  1. Elsevier. (n.d.). Scopus Author Details: Mingyu Fan, Author ID 36742801900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=36742801900
  2. ORCID. (n.d.). Research profile of Mingyu Fan.
    https://orcid.org/0000-0002-0492-4708
  3. Information Sciences. (2016.).Efficient isometric multi-manifold learning based on the self-organizing method.
    https://doi.org/10.1016/j.ins.2016.01.069
  4. Medical Physics. (2023). Feature-guided attention network for medical image segmentation.
    https://doi.org/10.1002/mp.16253
  5. International Invention Awards. (2026). Award information and evaluation overview.
    https://inventionawards.org/

Muhammad Nadeem | Computer Science | Best Researcher Award

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Shengchao Liu | Computer Science | Research Excellence Award

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Dr. Shengchao Liu | Computer Science | Research Excellence Award

The Chinese University | Hong Kong

Shengchao Liu is a tenure-track Assistant Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong, whose research lies at the intersection of machine learning, geometry, and scientific discovery. His work focuses on developing foundation models and physics-inspired learning frameworks for molecules, proteins, and materials, with the long-term goal of accelerating discovery in chemistry, biology, and materials science. By integrating multi-modal data, symmetry principles, and domain knowledge, his research bridges theoretical advances in AI with real-world experimental impact. A central theme of Dr. Liuโ€™s research is geometric and symmetry-informed representation learning. He has pioneered group-equivariant and manifold-constrained generative models that respect the underlying physical laws of molecular and material systems. His contributions include SE(3)-invariant pretraining methods, group-symmetric stochastic differential equation models, and rigid flow matching techniques, which have significantly improved the fidelity and interpretability of molecular generation and dynamics modeling. These methods form a unifying framework for learning across molecules, proteins, and crystalline materials, as demonstrated in his influential works at ICLR, ICML, NeurIPS, and AISTATS. Dr. Liuโ€™s work is deeply collaborative and interdisciplinary. He has worked closely with leading researchers across academia and industry, including Mila, UC Berkeley, NVIDIA Research, and national laboratories. As a Principal Investigator, he has led NERSC-supported projects on foundation models for material discovery, leveraging large-scale GPU resources to push the frontier of generative AI for science. His research has also contributed widely used open-source resources, including geometric graph learning benchmarks and toolkits adopted by the broader AI-for-science community.

Citation Metrics (Google Scholar)

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Citations
3510

Documents
40

h-index
22

Citations

Documents

h-index

View Google Scholar Profile

Featured Publications


Pre-training Molecular Graph Representation with 3D Geometry

โ€“ International Conference on Learning Representations , 2021 | Cited by 574


N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules

– Advances in Neural Information Processing Systems, 2019 | Cited by 295


Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing

โ€“ Nature Machine Intelligence , 2023 | Cited by 265


A text-guided protein design framework

– Nature Machine Intelligence, 2025 | Cited by 225

 

Kun He | Computer Science | Research Excellence Award

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Assoc Prof Dr. Kun He | Computer Science | Research Excellence Awardย 

Renmin University | China

Dr. Kun He is an accomplished computer scientist and currently serves as an Associate Professor at Renmin University of China (since January 2023). His academic journey reflects a strong foundation in theoretical computer science, backed by extensive research experience across leading Chinese institutions. Before joining Renmin University, he worked at the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), first as an Assistant Researcher (2021โ€“2022) and later as an Associate Researcher (2022). He also completed a postdoctoral fellowship at Shenzhen University between 2019 and 2021. Dr. He earned his Ph.D. in Computer Science from ICT, CAS in 2019 under the supervision of Prof. Xiaoming Sun. He also holds a Masterโ€™s degree from ICT, CAS and a Bachelor of Engineering in Computer Science from Wuhan University. His research centers on the theory of computing, with particular emphasis on probabilistic methods, sampling algorithms, quantum computing, combinatorial structures, and theoretical machine learning. His work has significantly advanced algorithmic techniques related to the Lovaฬsz Local Lemma (LLL), Holant problems, and random constraint satisfaction. Over the years, Dr. He has received numerous prestigious awards recognizing the impact and quality of his research. These include the New Hundred Stars of ICT (2021), the Outstanding Doctoral Dissertation Award of the China Computer Federation (2020), the Special Award for the President of CAS (2019), and the National Scholarship of China (2018). These honors highlight his early and sustained contributions to theoretical computer science. Dr. He has published extensively in top-tier venues such as SODA, STOC, FOCS, ITCS, and Random Structures & Algorithms. His notable works include breakthroughs on the Moserโ€“Tardos algorithm, deterministic counting versions of the Lovaฬsz Local Lemma, sampling solutions to random CNF formulas, and quantum extensions of classical combinatorial frameworks. Several of his papers have been widely cited and recognized, including a top-downloaded publication in Random Structures & Algorithms (2020). Recently, his research continues to push theoretical boundaries, with upcoming papers on the phase transition of the Sinkhornโ€“Knopp algorithm and efficient approximation schemes for Holant problems. Dr. He also actively works on emerging topics involving perfect sampling and permutation constraints within the Lopsided LLL regime, with multiple manuscripts currently under submission. With strong expertise, a prolific publication record, and multiple high-impact contributions, Dr. Kun He stands as a leading figure in modern theoretical computer science.

Profiles: Scopus | Google Scholar

Featured Publications

He, K., Li, L., Liu, X., Wang, Y., & Xia, M. (2025). Variable version Lovรกsz Local Lemma: A tale of two boundaries. Information and Computation, 105386.

He, K. (2025). Phase transition of the Sinkhorn-Knopp algorithm. arXiv preprint arXiv:2507.09711.

He, K., Li, Z., Qiu, G., & Zhang, C. (2025). FPTAS for Holant problems with log-concave signatures. In Proceedings of the 2025 Annual ACMโ€“SIAM Symposium on Discrete Algorithms (SODA).

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within the lopsided local lemma regime. arXiv preprint arXiv:2411.02750.

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within and beyond the local lemma regime. arXiv e-prints, arXiv:2411.02750.

He, K., Li, Q., & Sun, X. (2023). Moser-Tardos algorithm: Beyond Shearerโ€™s bound. In Proceedings of the 2023 Annual ACMโ€“SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2023). Deterministic counting Lovรกsz Local Lemma beyond linear programming. In Proceedings of the 2023 Annual ACMโ€“SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wu, K., & Yang, K. (2023). Improved bounds for sampling solutions of random CNF formulas. In Proceedings of the 2023 Annual ACMโ€“SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2022). Sampling Lovรกsz Local Lemma for general constraint satisfaction solutions in near-linear time. In 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS).

Hussein Alabdally | Computer Science | Best Researcher Award

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Mr. Hussein Alabdally | Computer Science | Best Researcher Award

Mr. Hussein Alabdally | University of Southern Queensland | Australia

Mr. Hussein Alabdally is a talented computer scientist, software engineer, and telecommunications specialist with diverse professional expertise spanning Australia and Iraq. With a foundation in mathematics, web development, and programming, he has contributed significantly to education, technology, and translation services. Husseinโ€™s journey reflects his adaptability and passion for learning, from tutoring students in mathematics and English to working in IT, telecommunications, and software engineering roles. His bilingual communication skills in English and Arabic have enabled him to serve communities as an interpreter and translator, while his technical creativity continues to drive his work in coding, software design, and network systems.

Profiles

Scopus
Google Scholar

Education

Mr. Husseinโ€™s educational path is marked by academic excellence in mathematics, computer science, and engineering studies. He earned his Bachelor of Science degree in Toowoomba, Australia, achieving outstanding results in advanced courses including operations research, numerical computing, experimental design, and web technologies. His solid foundation in mathematics and computing equipped him with analytical and problem-solving skills crucial for tackling real-world technical challenges. Alongside formal studies, he pursued professional training in web development and programming, mastering coding languages such as HTML, CSS, Python, JavaScript, and C++. Hussein also gained practical experience in website design and database management, complementing his academic knowledge with hands-on projects.

Experience

Mr. Husseinโ€™s professional experience covers a wide range of roles across education, IT, translation, and engineering. He worked as a website developer with leading companies in Toowoomba, building digital platforms and enhancing user experience. His teaching journey as an English and mathematics tutor demonstrated his ability to simplify complex concepts for students, helping many succeed in academic pursuits. Husseinโ€™s bilingual expertise was recognized in his work as an interpreter, supporting communication in medical, legal, and educational contexts. Transitioning into engineering roles, he contributed as an IT specialist at Dar Al-Auloom Private High School and later advanced to software engineering and telecommunications positions in Kirkuk. His diverse portfolio reflects both technical mastery and cultural adaptability.

Research Interests

Mr. Husseinโ€™s research interests are deeply rooted in the intersection of mathematics, programming, and technology innovation. He is passionate about computational methods, web technologies, and advanced applications of mathematical modeling in computer engineering. His curiosity extends to artificial intelligence, game programming, and database systems, where he enjoys creating applications that merge creativity with technical precision. Hussein is particularly enthusiastic about designing intelligent software solutions, including document readers and chess games with AI capabilities. He also explores optimization techniques and performance computing, driven by a desire to apply theoretical knowledge to practical systems. His long-term vision is to bridge mathematics with next-generation software solutions.

Awards

Mr. Husseinโ€™s achievements highlight his academic dedication and community engagement. He earned recognition in national and international competitions, including the Australian Statistics Competition, where he won the Queensland prize. He also secured credits in the UNSW ICAS Science and Mathematics contests, demonstrating excellence across STEM disciplines. At the University of Southern Queensland, he was actively involved in science and engineering challenges, achieving commendable rankings. Beyond academics, Hussein received awards for both academic excellence and school community participation, showcasing his commitment to leadership and service. These honors underline his consistent performance, strong analytical skills, and ability to contribute meaningfully both inside and outside the classroom.

Publication Top Notes

Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data
Journal: Computers and Electronics in Agriculture,ย 
Authors: M. Diykh, M. Ali, M. Jamei, S. Abdulla, M.P. Uddin, A.A. Farooque, A.H. Labban, H. Alabdally, et al.

Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourierโ€“Bessel Series Expansion-Based LSTM Model
Journal: Forecasting,ย 
Authors: H. Alabdally, M. Ali, M. Diykh, R.C. Deo, A.A. Aldhafeeri, S. Abdulla, et al.

ECT-DLM: Deep Learning Based Empirical Curvelet Transform Approach for Thoracic Disease Diagnosis from X-RAY Images
Conference: ICTIS
Authors: S. Abdulla, S.K. Alkhafaji, H. Marhoon, M. Diykh, M.A. Majed, J. Sadiq, H. Alabdally, et al.

Physical Human Activity Recognition Based on Spectral Graph Wavelet Transforms Integrated with Machine Learning Model
Conference: International Conference on Health Information Science,
Authors: S. Abdulla, A.S. Majeed, A.B. Al-Khafaji, W. Alsalman, M. Diykh, A. Sahi, H. Alabdally, et al.

Robust Approach for Human Activity Recognition Using Decomposing Technique Based Machine Learning Models
Conference: International Conference on Health Information Science,
Authors: S.Z. Hmoud, M. Diykh, S. Abdulla, H. Alabdally, A. Sahi

Conclusion

Mr. Hussein Alabdally represents a professional who blends education, technical skill, and cultural versatility. His journey reflects resilience, adaptability, and a deep passion for mathematics and technology. Whether teaching students, translating across languages, or designing digital systems, Hussein demonstrates excellence in every role he undertakes. His dual citizenship in Australia and Iraq positions him as a global professional with a multicultural perspective. With his diverse experience in tutoring, web development, software engineering, and telecommunications, Hussein continues to grow as a researcher and practitioner in the field of computer science. His career trajectory shows promise for future contributions to both academia and industry.

Mr. Rami Farhat | Marketing | Best Researcher Award

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Mr. Rami Farhat | Marketing | Best Researcher Award

University of Science and Technology Beijing, Lebanon.

Dr. Rami Farhat is a dedicated researcher and academic with expertise in digital marketing strategies, social media advertising, and e-commerce optimization. With a strong background in business administration and technology adoption in marketing, he focuses on consumer behavior in digital platforms. Driven by curiosity and a passion for innovation, he collaborates with interdisciplinary researchers to solve industry challenges.

Profile

Orcid

Education ๐ŸŽ“

Dr. Rami Farhat is currently pursuing a Ph.D. in Business Administration (2021 โ€“ 2025) at the University of Science and Technology Beijing, China, where he focuses on digital marketing strategies and consumer behavior in online platforms. Prior to his doctoral studies, he earned a Master’s in International Business Administration (IMBA) (2018 โ€“ 2020) from the University of International Business and Economics, Beijing, China, gaining expertise in global business strategies and e-commerce optimization. His academic journey began with a B.S. in Business Administration (Finance Concentration) (2014 โ€“ 2017) from the Lebanese American University, Beirut, Lebanon, where he developed a strong foundation in finance, market analysis, and business administration principles. Throughout his education, Rami has demonstrated a keen interest in integrating technology and innovation into business practices, making him a dynamic and forward-thinking researcher in the field.

Professional Experience ๐Ÿ’ผ

Dr. Rami Farhat has a diverse background in digital marketing, business analysis, and research, with experience spanning multiple industries and regions. As a Media Executive at Interesting Times (Lebanon, 2022โ€“2023), he managed and optimized marketing campaigns across the GCC, leveraging social media, TV, and programmatic advertising. Previously, as a Marketing Officer at Ampersand Education (2022), he developed digital branding strategies and high-quality content. His role as a Market Research Analyst at Achi Scaffolding (2021โ€“2022) involved conducting SWOT analyses and consumer behavior research. Dr. Farhat also worked as a Freelancer at Pactera EDGE (China, 2020โ€“2021), focusing on software quality assurance and data optimization. Earlier, he was a Data Entry Specialist at NetEase (China, 2019โ€“2020), translating Arabic, English, and Chinese content for localization. His professional journey began as an Administrative Assistant at Lebanese American University (2014โ€“2017), where he handled marketing and administrative tasks. His expertise spans digital strategy, research, and content management in international markets.

Research Interests ๐Ÿ”ฌ

Digital Marketing Strategies โ€“ Exploring innovative ways to enhance online advertising effectiveness.

Social Media Advertising โ€“ Studying engagement and conversion strategies on social platforms.

E-Commerce Optimization โ€“ Improving online shopping experiences for higher satisfaction.

Consumer Behavior in Digital Platforms โ€“ Understanding customer decision-making in online environments.

Technology Adoption in Marketing โ€“ Analyzing AI-driven marketing trends.

Awards & Distinctions ๐Ÿ†

Chinese Government Scholarship Award (2018) โ€“ For pursuing a Master’s degree.

Chinese Government Scholarship Award (2021) โ€“ For pursuing a Ph.D. in Business Administration.

Reviewer โ€“ 5th International Conference on Modern Management based on Big Data.

Publications ๐Ÿ“š

Published Papers:

Entrepreneurs’ Adoption of Social Media Winning Platform(s) in Emerging Markets (2024) โ€“ International Journal of Internet Manufacturing and Services (IJIMS)
DOI: 10.1504/IJIMS.2025.10064254 (EI, Scopus)

A/B Split Test for Social Media Marketing Optimization: Comparing Creative Components Using Facebook Ads Manager (2024) โ€“ International Journal of Internet Manufacturing and Services (IJIMS)
DOI: 10.1504/IJIMS.2026.10067399 (EI, Scopus)

E-commerce for a Sustainable Future: Integrating Trust, Product Quality Perception, and Online Shopping Satisfaction (2024) โ€“ Journal of Sustainability
DOI: 10.3390/su17041431 (SSCI, Q2, IF: 3.3)

 

 

 

Assoc. Prof. Dr. Djamchid ASSADI | Digital Tech Management |Best Researcher Award

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Assoc. Prof. Dr. Djamchid ASSADI | Digital Tech Management |Best Researcher Award

Burgundy School of Business, France.

Prof. Djamchid Assadi is a distinguished academic and researcher affiliated with CEREN, EA 7477, at the Burgundy School of Business - Universitรฉ Bourgogne Franche-Comtรฉ. He holds an Accreditation to Supervise Research (HDR), demonstrating his expertise in guiding advanced research. His work focuses on the intersection of business models, artificial intelligence, and financial inclusion, contributing significantly to academic and industry advancements.

Profile

Scopus
Orcid

Education ๐ŸŽ“

Prof. Assadi earned his Accreditation to Supervise Research (HDR) and has been deeply involved in research across multiple disciplines, enhancing his academic and professional footprint.

Experience ๐ŸŒŸ

Prof. Assadi serves as the Director & Researcher at CEREN, EA 7477, Burgundy School of Business, where he leads impactful research initiatives. He is also a Guest Editor for various international academic journals, contributing his expertise to the advancement of scholarly publications. Additionally, he is an Academic Advisory Board Member at IMS Ghaziabad & GL Bajaj Institute of Management and Research, guiding academic and research activities in these institutions. As a PhD Co-Supervisor, he has mentored numerous doctoral candidates across various universities, playing a crucial role in shaping research in business and financial studies.

Research Interests ๐Ÿ”ฌ

The Role of Artificial Intelligence in Strategic Development, Business Models, Consumer Behavior, and Financial Inclusion

Organizational Ecosystems: Governance of Interactions and Transactions

Collaborative, Sharing, and Platform Economy

Influence of Non-Price Factors on Purchasing Decisions and Strategic Behavior

Economic and Geostrategic Analysis of Rent-Seeking Behavior

Awards & Honors ๐Ÿ†

Prof. Assadi has been recognized for his outstanding contributions to business research and financial inclusion, with multiple accolades in the field of strategic and digital entrepreneurship.

Publications ๐Ÿ“š

๐Ÿ“„ Fighting Fire with Fire: Combating Criminal Abuse of Cryptocurrency with a P2P Mindset

Journal: Information Systems Frontiers

Published Year: 2024

DOI: 10.1007/s10796-024-10498-7

Contributors: Galit Klein, Djamchid Assadi, Moty Zwilling

๐Ÿ“š Digital Sustainable Entrepreneurship Business Model and Its Contribution to Sustainable Development Goals

Contributors: Surabhi Singh, Urvashi Makkar, Djamchid Assadi