Boris Genin | Data Engineering | Best Researcher Award

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Best Researcher Award

Boris Genin
Federal Institute of Industrial Property

Boris Genin
Affiliation Federal Institute of Industrial Property
Country Russia
Scopus ID 57222040159
Documents 3
Citations 3
h-index 1
Subject Area Data Engineering
Event International AI Data Scientists Award
ORCID 0000-0003-3514-1340

Boris Genin of the Federal Institute of Industrial Property has demonstrated academic engagement in the field of Data Engineering through scholarly publications, intellectual property research, and contributions to technology-driven information systems. His research profile reflects participation in scientific activities that support data management, innovation assessment, and digital transformation initiatives.[1]

Abstract

This article highlights the academic profile of Boris Genin and his relevance to the Best Researcher Award. His work focuses on data-related research activities, innovation systems, and intellectual property information management. Through scholarly publications and participation in scientific research, he has contributed to knowledge development within Data Engineering and associated digital domains.[1]

Keywords

Data Engineering, Research Innovation, Information Systems, Intellectual Property Analytics, Digital Transformation, Data Management, Scientific Research.

Introduction

Research excellence is measured through scholarly productivity, knowledge dissemination, and contributions to professional practice. Boris Genin’s academic record reflects engagement with data-centric methodologies and research activities that support innovation management and information processing. His published work contributes to ongoing discussions regarding efficient data utilization and technology-enabled decision-making processes.[2]

Research Profile

Affiliated with the Federal Institute of Industrial Property, Boris Genin has developed a research portfolio connected to data engineering applications and intellectual property information systems. His Scopus profile records multiple indexed publications and citations, reflecting active participation within scholarly communication networks.[1]

Research Contributions

His contributions include research supporting information analysis, structured data organization, and innovation-related knowledge systems. Such work helps strengthen evidence-based decision processes and supports the broader objectives of data-driven research environments.[3]

Publications

  • Indexed scholarly publications related to data engineering and information management.
  • Research outputs contributing to innovation analytics and digital information systems.
  • Works cited within academic databases and research platforms.

Research Impact

Although at an early citation stage, the documented impact of the researcher’s publications demonstrates visibility within the academic community. Citation records and indexing within international databases indicate engagement with global scholarly audiences and ongoing relevance within specialized research areas.[1]

Award Suitability

Boris Genin’s scholarly activities align with the objectives of the International AI Data Scientists Award. His contributions to data engineering, research dissemination, and innovation-focused information systems support the criteria commonly associated with academic recognition programs. The combination of publications, citations, and institutional affiliation provides a foundation for consideration under the Best Researcher Award category.[1]

Conclusion

Boris Genin represents an example of a researcher contributing to data engineering and innovation-related scholarship. His academic profile reflects engagement with research, publication, and knowledge dissemination activities that support scientific advancement. These achievements establish a suitable basis for recognition through the Best Researcher Award program.

References

  1. Elsevier. (n.d.). Scopus author details: Boris Genin, Author ID 57222040159. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57222040159
  2. ORCID. (n.d.). Research profile of Boris Genin.
    https://orcid.org/0000-0003-3514-1340
  3. Digital Object Identifier Foundation. (n.d.). DOI reference resource.
    https://doi.org/10.1016/j.procs.2021.05.001

Mujidat Bello | Data Quality Management | Best Researcher Award

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Best Researcher Award

Mujidat Bello
Fountain University, Osogbo, Nigeria

Mujidat Bello
Affiliation Fountain University
Country Nigeria
Scopus ID 47061216000
Documents 11
Citations 64
h-index 5
Subject Area Data Quality Management
Event International AI Data Scientists Award
ORCID 0000-0002-4862-7924

Mujidat Bello is a Nigerian academic researcher affiliated with Fountain University, Osogbo, whose scholarly activities focus on Data Quality Management, information systems, and applied data analytics. Her academic contributions demonstrate an interest in improving the reliability, accessibility, and governance of digital information systems within emerging technological environments. Bello’s research portfolio includes peer-reviewed publications indexed in Scopus and other scholarly databases, reflecting consistent participation in contemporary data-driven research initiatives.[1]

Abstract

This article presents an overview of the academic profile and research contributions of Mujidat Bello in the field of Data Quality Management. Her work highlights the importance of maintaining accurate, reliable, and accessible datasets in modern information systems. Through publications, collaborative studies, and scholarly engagement, Bello has contributed to discussions surrounding data governance and digital transformation in academic and institutional environments.[2]

Keywords

Data Quality Management, Information Systems, Data Governance, Digital Analytics, Research Data, Academic Research, Artificial Intelligence, Data Integrity.

Introduction

The growing dependence on digital technologies has increased the need for effective data quality practices across institutions and research organizations. Scholars working in this domain contribute to ensuring that data remains trustworthy and usable for scientific, administrative, and technological applications. Mujidat Bello’s research activities align with these objectives through studies related to data handling, management systems, and analytical methodologies.[3]

Research Profile

Bello’s academic record includes 11 indexed scholarly documents with 64 citations and an h-index of 5. Her profile demonstrates consistent engagement with interdisciplinary research areas involving information systems and data quality assessment. The visibility of her publications within citation databases reflects scholarly recognition and ongoing academic relevance.[1]

Research Contributions

  • Research on data integrity and information reliability in institutional systems.
  • Contributions to discussions on digital transformation and information governance.
  • Participation in collaborative scholarly publications related to data analytics and quality management.

Publications

Research Impact

The citation metrics associated with Bello’s publications indicate academic engagement within the field of information management and data quality studies. Her work contributes to the broader understanding of how institutions can improve digital systems through reliable data practices and analytical frameworks.[2]

Award Suitability

Mujidat Bello’s academic profile demonstrates suitability for recognition under the Best Researcher Award category due to her scholarly productivity, citation impact, and involvement in research concerning data quality management. Her contributions align with the objectives of the International AI Data Scientists Award, which emphasizes innovation, research quality, and advancement in data-driven disciplines.[4]

Conclusion

The academic activities and research contributions of Mujidat Bello illustrate continued engagement with contemporary issues in data quality management and information systems research. Her scholarly output, citation record, and institutional affiliation collectively support her recognition within the international academic community.

References

  1. Elsevier. (n.d.). Scopus author details: Mujidat Bello, Author ID 47061216000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=47061216000
  2. ORCID. (n.d.). ORCID profile of Mujidat Bello.
    https://orcid.org/0000-0002-4862-7924
  3. Google Scholar. (n.d.). Academic citation profile of Mujidat Bello.
    https://scholar.google.com/citations?user=f_8NfrsAAAAJ&hl=en
  4. International AI Data Scientists Award. (2026). Best Researcher Award recognition criteria.
    https://aidatascientists.com/

Somchith Sompaseuth | Data-Driven Decision Making | Best Researcher Award

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Best Researcher Award

Somchith Sompaseuth
Zhengzhou University
Somchith Sompaseuth
Affiliation Zhengzhou University
Country Lao People’s Democratic Republic
Scopus ID 58760681400
Documents 2
Citations 1
h-index 1
Subject Area Data-Driven Decision Making
Event International AI Data Scientists Award
Scopus View Profile

Somchith Sompaseuth is recognized for contributions in the field of data-driven decision making, with research activities associated with Zhengzhou University. The academic profile demonstrates engagement in analytical methodologies, computational approaches, and evidence-based research practices relevant to emerging trends in artificial intelligence and data science. The recognition under the International AI Data Scientists Award reflects scholarly involvement in interdisciplinary research and applied analytical studies.[1]

Abstract

This article presents an overview of the scholarly activities and research profile of Somchith Sompaseuth in the domain of data-driven decision making. The research focus includes analytical reasoning, computational methodologies, and applications of data science within interdisciplinary environments. The profile highlights academic contributions, citation performance, and participation in international research initiatives related to artificial intelligence and digital transformation.[1]

Keywords

Data-Driven Decision Making, Artificial Intelligence, Data Analytics, Computational Research, Machine Learning, Predictive Analytics, Information Systems, Digital Transformation, Statistical Analysis, Intelligent Systems, Research Evaluation, Academic Recognition.

Introduction

Data-driven decision making has become an essential component of modern scientific research and organizational planning. Researchers in this field contribute to the interpretation of complex datasets, the development of analytical frameworks, and the implementation of intelligent systems for strategic outcomes. Somchith Sompaseuth has participated in research activities aligned with these evolving technological and methodological developments.[2]

The integration of artificial intelligence with decision sciences has enabled broader applications across healthcare, education, engineering, and computational systems. Scholarly contributions in this area support evidence-based methodologies and improve the effectiveness of data interpretation processes in academic and professional environments.[3]

Research Profile

The research profile of Somchith Sompaseuth includes publications indexed in international databases and scholarly engagement in data-oriented research domains. The documented citation metrics and publication records indicate active participation in scientific dissemination and collaborative academic initiatives.[1]

  • Research specialization in data-driven decision methodologies.
  • Academic affiliation with Zhengzhou University.
  • Indexed publications within recognized academic databases.
  • Engagement with interdisciplinary analytical research.

Research Contributions

The scholarly contributions associated with Somchith Sompaseuth involve the application of analytical reasoning and computational techniques within data-intensive environments. Research activities contribute to the broader understanding of intelligent decision-support systems and data interpretation models.[2]

The work further reflects growing interest in the integration of machine learning and evidence-based computational practices for supporting organizational and scientific decision processes. These efforts align with current global trends in artificial intelligence and digital analytics.[3]

Publications

Selected research outputs and indexed publications associated with the researcher demonstrate engagement in contemporary topics related to computational intelligence and analytical methodologies.[1]

  • Research publications indexed within Scopus-authorized databases.
  • Contributions to interdisciplinary analytical studies.
  • Participation in research related to intelligent systems and data science.
  • Academic dissemination through international scholarly platforms.

Research Impact

Research impact may be evaluated through publication visibility, citation metrics, collaborative activity, and thematic relevance. The available metrics associated with Somchith Sompaseuth indicate emerging scholarly engagement in the field of data-driven decision making.[1]

The interdisciplinary nature of data science enables research findings to contribute across multiple sectors, including digital systems, analytics, and computational intelligence. Such contributions support knowledge development and evidence-based innovation within academic communities.[3]

Award Suitability

The Best Researcher Award under the International AI Data Scientists Award framework recognizes academic participation, analytical research efforts, and contributions to the advancement of intelligent data methodologies. Somchith Sompaseuth demonstrates alignment with these objectives through scholarly activities related to data-driven research and interdisciplinary analytical studies.[4]

The recognition also reflects the increasing importance of early-stage and emerging research contributions in shaping future developments in artificial intelligence, analytics, and evidence-based computational systems.[2]

Conclusion

Somchith Sompaseuth represents an emerging academic profile in the area of data-driven decision making. Through participation in computational and analytical research activities, the researcher contributes to ongoing scholarly developments associated with artificial intelligence and digital transformation. The recognition through the International AI Data Scientists Award acknowledges these efforts within a global academic context.[4]

References

  1. Elsevier. (n.d.). Scopus author details: Somchith Sompaseuth, Author ID 58760681400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58760681400
  2. Google Scholar. (n.d.). Scholar profile and indexed academic activities of Somchith Sompaseuth.
    https://scholar.google.com/citations?user=-OOBUl4AAAAJ&hl=en&oi=ao
  3. Proceedings in Computer Science. (2021). Applications of data-driven analytical frameworks in intelligent systems.
    https://doi.org/10.1016/j.procs.2021.01.123
  4. International AI Data Scientists Award. (n.d.). Award categories and international research recognition framework.
    https://aidatascientists.com/

Jong Jin Oh | Data-Driven Decision Making | Best Researcher Award

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Best Researcher Award

JONG JIN OH
Seoul National University Bundang Hospital, Seoul National College of Medicine
JONG JIN OH
Affiliation Seoul National University Bundang Hospital, Seoul National College of Medicine
Country South Korea
Scopus ID 24468588100
Documents 164
Citations 2122
h-index 25
Subject Area Data-Driven Decision Making
Event International AI Data Scientists Award
Scopus Profile View Profile

JONG JIN OH, affiliated with Seoul National University Bundang Hospital and Seoul National College of Medicine in South Korea, has demonstrated significant research productivity in the field of Data-Driven Decision Making through scholarly publications, citation impact, and international scientific engagement.[1] The researcher’s academic profile reflects continued participation in evidence-based analytical methodologies and healthcare-related computational research.[2]

Abstract

This article presents an academic overview of JONG JIN OH and the scholarly contributions associated with the Best Researcher Award. The evaluation highlights research productivity, citation performance, interdisciplinary collaboration, and contributions to Data-Driven Decision Making methodologies within healthcare and analytical sciences.[1] Bibliometric indicators demonstrate measurable international research visibility and sustained scientific engagement through peer-reviewed publication activity.[3]

Keywords

Data-Driven Decision Making, Healthcare Analytics, Medical Informatics, Artificial Intelligence, Clinical Research, Computational Medicine, Evidence-Based Analysis, Machine Learning, Predictive Modeling, Scientific Research

Introduction

Data-Driven Decision Making has become increasingly significant across healthcare, biomedical research, and artificial intelligence applications. The integration of computational methodologies and clinical analytics supports informed decision processes, predictive healthcare strategies, and evidence-based scientific practices.[4]

JONG JIN OH has contributed to research activities involving analytical methodologies, healthcare-oriented computational systems, and scientific evaluation frameworks. Through publication dissemination and collaborative research participation, the researcher has established measurable scholarly visibility within indexed international databases.[1]

Research Profile

The research profile of JONG JIN OH demonstrates sustained scholarly engagement in Data-Driven Decision Making and interdisciplinary healthcare research. According to indexed bibliometric databases, the researcher has authored or co-authored 164 scientific documents and accumulated 2122 citations, resulting in an h-index of 25.[1] These metrics indicate substantial academic participation and research dissemination within international scientific communities.

  • Total indexed publications: 164
  • Total citations: 2122
  • h-index value: 25
  • Research specialization in Data-Driven Decision Making and healthcare analytics

Research Contributions

The scholarly contributions associated with JONG JIN OH include participation in analytical healthcare research, predictive methodologies, computational medical systems, and evidence-based clinical evaluation frameworks.[2] Research activities within these domains support advancements in healthcare optimization, decision-support technologies, and scientific data interpretation.

Data-driven methodologies play an increasingly important role in medical sciences by supporting diagnosis optimization, patient outcome prediction, and evidence-guided healthcare management. Such interdisciplinary approaches integrate statistical analysis, machine learning, and computational frameworks into modern clinical research environments.[5]

  • Contribution to healthcare-oriented analytical methodologies.
  • Participation in computational medical research initiatives.
  • Research involving evidence-based decision-support systems.
  • Scientific dissemination through indexed peer-reviewed publications.

Publications

The publication record associated with JONG JIN OH reflects extensive scholarly activity within healthcare analytics, computational medicine, and data-driven scientific evaluation. Indexed publications contribute to the dissemination of interdisciplinary analytical methodologies and evidence-based healthcare research.[1]

  1. Research articles related to healthcare analytics and computational medicine.
  2. Peer-reviewed studies involving predictive and evidence-based methodologies.
  3. Collaborative publications across interdisciplinary healthcare research domains.
  4. Scientific dissemination through indexed journals and conference proceedings.

Research Impact

Research impact can be evaluated through citation performance, publication dissemination, collaborative engagement, and interdisciplinary relevance. The academic profile associated with JONG JIN OH demonstrates substantial scholarly visibility through 2122 citations and an h-index of 25.[1]

These bibliometric indicators suggest sustained scientific recognition and continued participation in international healthcare and analytical research discourse. Citation accumulation within indexed databases reflects the relevance of the researcher’s contributions to computational and evidence-based scientific methodologies.

Award Suitability

The Best Researcher Award recognizes scholars demonstrating sustained academic productivity, measurable scientific impact, and interdisciplinary research excellence. JONG JIN OH’s research profile aligns with these criteria through publication productivity, citation performance, and contributions to healthcare-oriented Data-Driven Decision Making methodologies.[3]

Recognition through international academic award platforms supports broader scientific visibility and encourages continued innovation within healthcare analytics and evidence-based computational research. The researcher’s academic record reflects substantial engagement with interdisciplinary scientific advancement.

Conclusion

JONG JIN OH has established a distinguished academic profile through contributions to Data-Driven Decision Making, healthcare analytics, and computational medical research. Publication productivity, citation performance, and interdisciplinary collaboration demonstrate sustained scholarly engagement within international scientific communities. The Best Researcher Award recognizes these achievements and highlights the importance of analytical methodologies within evolving healthcare and computational research environments.[1]

References

  1. Elsevier. (n.d.). Scopus author details: JONG JIN OH, Author ID 24468588100. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=24468588100&source=sd-apx
  2. Seoul National University Bundang Hospital. (n.d.). Research and clinical innovation overview.
    https://www.snubh.org/
  3. International AI Data Scientists Award. (n.d.). International recognition framework for scientific excellence.
    https://aidatascientists.com/
  4. Provost, F., & Fawcett, T. (2013). Data Science and its relationship to big data and data-driven decision making.
    https://doi.org/10.1089/big.2013.1508
  5. Topol, E. (2019). High-performance medicine: the convergence of human and artificial intelligence.
    https://doi.org/10.1038/s41746-019-0195-0

Ikram Ben Ahmed | Data Science | Innovative Research Award

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Innovative Research Award

Ikram Ben Ahmed
Higher Institute of Applied Sciences and Technology of Sousse
Ikram Ben Ahmed
Affiliation Higher Institute of Applied Sciences and Technology of Sousse
Country Tunisia
Scopus ID 57776480900
Documents 5
Citations 45
h-index 3
Subject Area Data Science
Event International AI Data Scientists Award
ORCID 0000-0001-5205-0219

Ikram Ben Ahmed, affiliated with the Higher Institute of Applied Sciences and Technology of Sousse in Tunisia, has contributed to the growing body of research in Data Science through publications, collaborative academic activities, and citation impact within indexed scholarly databases.[1] The recognition reflects measurable research productivity and scholarly engagement associated with contemporary computational and analytical research environments.[2]

Abstract

This academic article presents an overview of the research activities, scholarly metrics, and academic recognition associated with Ikram Ben Ahmed. The article examines institutional affiliation, publication performance, citation indicators, and contributions within the field of Data Science. Indexed scholarly records indicate active participation in scientific dissemination and interdisciplinary computational studies.[1] The analysis also contextualizes the relevance of the Innovative Research Award within international academic evaluation frameworks focused on research quality, visibility, and impact.

Keywords

Data Science, Artificial Intelligence, Scholarly Impact, Research Metrics, Academic Recognition, Citation Analysis, Scopus Indexing, Machine Learning, Research Evaluation, International Awards

Introduction

The rapid evolution of Data Science has transformed numerous scientific and industrial domains through the integration of machine learning, statistical analytics, and intelligent computational systems. Researchers operating within this field contribute to methodological innovation, analytical modeling, and data-driven decision-making processes that influence academic and applied research environments.[4]

Ikram Ben Ahmed has contributed to scholarly activities associated with computational analysis and interdisciplinary scientific inquiry. The researcher’s indexed academic profile reflects publication activity, citation performance, and collaborative engagement consistent with international research standards.[1] Recognition through the International AI Data Scientists Award further highlights the relevance of measurable research contributions within global scientific communities.

Research Profile

The academic profile of Ikram Ben Ahmed demonstrates engagement with research topics situated within Data Science and related analytical disciplines. Based on indexed database records, the researcher has authored or co-authored five scholarly documents and accumulated forty-five citations with an h-index of three.[1] These metrics indicate an observable level of scholarly influence and participation in peer-reviewed scientific communication.

The Higher Institute of Applied Sciences and Technology of Sousse serves as the institutional base for the researcher’s academic activities. The institution contributes to scientific education and technological advancement through interdisciplinary teaching and research initiatives within Tunisia and broader international networks.[5]

Research Contributions

Research contributions associated with Ikram Ben Ahmed include participation in computational analysis, data interpretation methodologies, and interdisciplinary scientific applications. The scholarly outputs demonstrate engagement with contemporary analytical frameworks relevant to artificial intelligence and information processing systems.[2]

Data Science research commonly requires the integration of statistical modeling, machine learning techniques, and computational optimization. Contributions within these domains often support predictive analytics, intelligent systems development, and data-driven research methodologies applicable across engineering, healthcare, education, and industrial sectors.[4]

  • Participation in indexed scholarly publications related to Data Science and computational analysis.
  • Contribution to interdisciplinary scientific research initiatives and collaborative studies.
  • Development and application of analytical methodologies relevant to artificial intelligence research.
  • Engagement with international academic dissemination and citation-indexed research platforms.

Publications

The publication record indexed under the researcher’s Scopus profile reflects contributions to peer-reviewed scientific literature. Representative publication areas include data analytics, computational systems, and intelligent information processing methodologies.[1]

  • Research studies addressing computational analysis and intelligent data processing methodologies.
  • Scholarly contributions involving machine learning and interdisciplinary analytical frameworks.
  • Collaborative academic publications indexed within international citation databases.
  • Research dissemination through peer-reviewed scientific communication channels.

Digital Object Identifier (DOI) systems remain essential for ensuring persistent access to scholarly publications and citation interoperability across digital academic platforms.

Research Impact

Research impact is frequently evaluated through bibliometric indicators including citation counts, h-index measurements, publication quality, and interdisciplinary influence. The available scholarly metrics associated with Ikram Ben Ahmed indicate measurable citation engagement within indexed academic literature.[1]

The accumulation of citations reflects academic visibility and the relevance of published work to ongoing scientific discussions. Citation metrics additionally support institutional evaluations, international collaborations, and recognition within professional research communities.[7]

  1. Indexed Documents: 5
  2. Total Citations: 45
  3. h-index: 3
  4. International Research Visibility through Scopus and ORCID platforms.

Award Suitability

The Innovative Research Award is designed to recognize researchers demonstrating measurable academic performance, interdisciplinary engagement, and sustained scientific contributions within emerging technological fields. Ikram Ben Ahmed’s scholarly profile aligns with several of these evaluation dimensions through indexed publications, citation indicators, and participation in Data Science research activities.

Recognition through international academic award platforms contributes to broader visibility for researchers working in rapidly developing computational and analytical disciplines. Such awards also encourage continued collaboration, scientific dissemination, and methodological innovation within global research ecosystems.[7]

Conclusion

Ikram Ben Ahmed represents an emerging academic contributor within the field of Data Science, with indexed research activity and measurable citation performance supporting scholarly visibility and recognition. The Innovative Research Award acknowledges contributions associated with analytical research, computational methodologies, and interdisciplinary scientific engagement. Continued participation in peer-reviewed publication and collaborative research initiatives is expected to further strengthen academic impact and international scholarly presence.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Ikram Ben Ahmed, Author ID 57776480900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57776480900
  2. Google Scholar. (n.d.). Scholarly citation profile and indexed academic publications.
    https://scholar.google.com/citations?hl=en&user=dqbXZWIAAAAJ
  3. Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260.
    https://doi.org/10.1126/science.aaa8415
  4. Higher Institute of Applied Sciences and Technology of Sousse. (n.d.). Institutional academic and research overview.
    https://www.universites.tn/
  5. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.
    https://doi.org/10.1073/pnas.0507655102

Jaehyung Kim | Machine Learning | Research Excellence Award

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Mr. Jaehyung Kim | Machine Learning | Research Excellence Award

Division of Fisheries Resources and Environmental Research | South Korea

Jaehyung Kim is a researcher at the West Sea Fisheries Research Institute specializing in fisheries resources and environmental studies. His work integrates machine learning techniques to analyze marine ecosystems, assess species maturity, and support sustainable fisheries management, contributing to data-driven decision-making and innovation in marine science and resource conservation.


View ORCID Profile

Featured Publications

Estimation of the Length at First Maturity of the Swimming Crab (Portunus trituberculatus) in the Yellow Sea of Korea Using Machine Learning
– Journal of Marine Science and Engineering, 2026

Jihyun Kim | Data-Driven Decision Making | Research Excellence Award

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Ms. Jihyun Kim | Data-Driven Decision Making | Research Excellence Award

Professor | University of Seoul | South Korea

Ms. Jihyun Kim is a researcher in Transportation Engineering with a focus on data-driven analysis of traffic systems and emerging mobility technologies. Her research explores traveler behavior, safety, and operational performance using advanced statistical modeling and simulation-based approaches. She has conducted studies on e-scooter operations on sidewalks using VR simulators to evaluate safety and applicability under realistic conditions. Her work also includes the development of intersection- and roundabout-specific gap acceptance models, incorporating environmental factors such as rainfall. Through her research, she contributes evidence-based insights to support safer, smarter, and more efficient urban transportation systems.

Research Metrics (Google Scholar)

8

6

4

2

0

Citations
0

Publications
2

h-index
0


View Google Scholar Profile View Orcid Profile

Featured Publications

Mr. Soumyapriya Goswami | Industrial Internet of Things | Best Researcher Award

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Mr. Soumyapriya Goswami | Industrial Internet of Things | Best Researcher Award 

IT Researcher, Kalyani Government Engineering College, West Bengal

Mr. Soumyapriya Goswami is a dedicated B.Tech IT researcher at Kalyani Government Engineering College with a strong academic foundation and practical experience in emerging technologies, including Artificial Intelligence, Internet of Things (IoT), Wireless Sensor Networks, edge computing, reinforcement learning, and quantum security for medical devices. His education reflects consistent academic excellence, having completed his secondary and higher secondary studies at Asansol Ramakrishna Mission High School and Dhadka NCLahiri Vidyamandir, followed by his ongoing B.Tech IT program at Kalyani Government Engineering College. Professionally, Soumyapriya has developed expertise in AI/ML model deployment, prompt engineering for generative AI, cloud-based solutions, project management, and team leadership, with proficiency in programming languages (Python, C, C++, Java), AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), and cloud platforms (Google Cloud, Docker, Jenkins). His research interests encompass energy-efficient scheduling for WSNs, reinforcement learning-based threat detection for IoT devices, quantum-aware security protocols for medical devices, digital twins, and cyber-physical systems.  In conclusion, Mr. Soumyapriya Goswami demonstrates strong potential to bridge academic research with industry applications, delivering innovative solutions in AI, IoT, and quantum technologies, while contributing to knowledge dissemination, mentorship, and technological advancement in emerging research domains, positioning him as a promising early-career researcher with impactful scholarly and practical contributions.

Profile: GOOGLE SCHOLAR | SCOPUS | ORCID

Featured Publications

  1. Goswami, S. (Published). NashDQNSleep: Energy-efficient sleep scheduling for WSN using Nash Equilibrium and Deep Q-Networks. Elsevier EAAI. Citation count: unavailable

  2. Goswami, S. (Under Review). Polaris: Optimized power-aware GPU scheduling framework for cloud environments. IEEE TPDS. Citation count: unavailable

  3. Goswami, S. (Under Review). Qure: Quantum-aware protocols for medical device security using entanglement and root-of-trust designs. IEEE Cybernatics. Citation count: unavailable

  4. Goswami, S. (Ongoing). TinySurvive: Reinforcement Learning-based threat intelligence model for low-power IoT devices in hazardous environments. Citation count: unavailable

H. Dennis Park | Startup Innovation in The Digital Era | Best Researcher Award

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Assoc. Prof. Dr. H. Dennis Park | Startup Innovation in The Digital Era | Best Researcher Award

Associate Professor of Innovation and Entrepreneurship at University of Texas at Dallas, United States

Dr. H. Dennis Park is an Associate Professor of Innovation and Entrepreneurship at the Naveen Jindal School of Management, University of Texas at Dallas. His work focuses on the strategic management of innovation, particularly in technology entrepreneurship, where he investigates the role of corporate investors and the use of external resources for new knowledge creation. His expertise bridges economics-based theories, such as agency theory, knowledge-based views, and transaction cost economics, with a focus on the governance of new ventures and technology commercialization.

Profile

Orcid

Education

Dr. Park holds a Ph.D. in Technology Entrepreneurship and Strategic Management from the Michael G. Foster School of Business, University of Washington. His dissertation, titled “The influence of corporate investors on the development and performance of new ventures,” was a finalist for the prestigious Technology and Innovation Management (TIM) Division Best Dissertation Award at the Academy of Management. Additionally, he holds an MBA from the Robert E. McDonough School of Business, Georgetown University, and a Bachelor of Arts in Computer Sciences, Economics, and Mathematics from the University of Wisconsin at Madison.

Experience

Dr. Park has a broad academic background, having served as an Assistant Professor at Drexel University and the University of Missouri–Kansas City before joining the University of Texas at Dallas in 2017. His work has contributed significantly to the fields of entrepreneurship, innovation, and venture capital, as he continues to advance the understanding of the intersection between corporate investors and startup innovation. His professional trajectory is marked by a consistent focus on the strategic governance of innovation in high-tech industries and the dynamic role of venture capital.

Research Interests

Dr. Park’s research explores how startups and established firms leverage external resources, such as venture capital, intellectual property, and human capital, to generate new knowledge and create economic value. His work often employs theoretical frameworks like agency theory and knowledge-based views to understand the mechanisms that drive innovation and firm performance. His interests also extend to artificial intelligence, corporate venture capital, digitization, and intellectual property rights in the context of technology entrepreneurship.

Awards

Dr. Park has received several accolades for his research and teaching, including nominations for the Provost’s Award for Excellence in Graduate Research Mentoring and the President’s Excellence in Teaching Award at UT-Dallas. His research has earned him the 2021 Southwest Academy of Management Distinguished Paper Award and multiple Best Reviewer Awards from prestigious journals like the Journal of Business Venturing.

Publications

Dr. Park has contributed to numerous high-impact journals. Notable publications include:

  1. Park, H. D., & Steensma, H. K. (2012). “When does corporate venture capital add value for new ventures?” Strategic Management Journal, 33(1): 1-22. Cited by 252 articles.

  2. Park, H. D., & Tzabbar, D. (2016). “Venture capital, CEOs’ sources of power, and innovation novelty at different life stages of a new venture.” Organization Science, 27(2): 336-353. Cited by 125 articles.

  3. Kim, J. Y. R., & Park, H. D. (2017). “Two faces of early CVC funding: Fostering innovation and inhibiting IPOs.” Strategy Science, 2(3): 161-175. Cited by 92 articles.

  4. Dass, N., Nanda, V. K., Park, H. D., & Xiao, S. (2021). “Intellectual property protection and financial markets: Patenting vs. secrecy.” Review of Finance, 25(3): 669-711. Cited by 77 articles.

  5. Kwon, J. H., Park, H. D., & Deng, S. (2022). “When do firms trade patents?” Organization Science, 33(3): 1212-1231. Cited by 63 articles.

  6. Xu, L., Ou, A., Park, H. D., & Jiang, H. (2024). “Breaking barriers or maintaining status quo? Female representation on decision-making groups of venture capital firms and funding of women-led businesses.” Journal of Business Venturing, 39(1): 106368. Cited by 45 articles.

Conclusion

Dr. H. Dennis Park’s contributions to the fields of entrepreneurship and innovation, particularly in the area of corporate venture capital and new venture governance, have earned him recognition as a thought leader. His work not only informs academic discourse but also provides valuable insights for practitioners in technology entrepreneurship. Through his research, teaching, and mentoring, Dr. Park continues to shape the future of innovation management and strategic entrepreneurship.

Rajender Singh | Machine Learning and Communication | Best Academic Researcher Award

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Mr. Rajender Singh | Machine Learning and Communication | Best Academic Researcher Award

Assistant Professor at JEC, Jabalpur, India

Rajender Singh Yadav is a distinguished academician and researcher with over two decades of experience in the field of Electronics and Communication Engineering. He received his Bachelor of Engineering degree from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, in 2001, and later completed his Master of Technology from the same university in 2010. Presently, he is serving as an Assistant Professor at BGIEM, Jabalpur, where he has been contributing to academic and research activities since March 2022. Throughout his career, he has demonstrated expertise in various cutting-edge areas such as Artificial Intelligence, Robotics, Embedded Systems, and Signal and Image Processing. His dedication to education and research has significantly impacted both students and the academic community.

Profile

Orcid

Education

Rajender Singh Yadav’s academic foundation is firmly rooted in Electronics and Communication Engineering. He began his academic journey at HCET, Jabalpur, Madhya Pradesh, where he pursued his B.E. from 1997 to 2001, equipping himself with essential engineering skills and a solid understanding of communication technologies. To further enhance his expertise, he enrolled in UPTU, Lucknow, where he completed his M.Tech. in Electronics and Communication Engineering between 2007 and 2010. His advanced studies allowed him to deepen his knowledge of sophisticated communication systems, embedded technologies, and AI-driven processes, laying a strong groundwork for his future research endeavors and teaching career.

Experience

With an extensive teaching career spanning over 22 years, Rajender Singh Yadav has amassed a wealth of experience across reputed institutions. He started as a Lecturer at GNIT, Greater Noida, in 2003, where he served for two years. Following this, he worked at AKGEC, Ghaziabad, as a Lecturer and later as an Assistant Professor from 2005 to 2012. His commitment to academic excellence led him to GGITS, Jabalpur, where he spent a decade nurturing young minds as an Assistant Professor. Since 2022, he has been associated with BGIEM, Jabalpur, continuing his journey of mentoring students and advancing research. Over the years, he has successfully blended academic teaching with research innovations, fostering a learning environment focused on technological advancement and real-world application.

Research Interest

Rajender Singh Yadav’s research interests are broad and interdisciplinary, focusing on AI, Robotics, Embedded Systems, and Signal and Image Processing. His passion lies in developing intelligent systems capable of addressing real-time challenges in wireless communication, autonomous robotics, and integrated system designs. He actively explores the synergy between artificial intelligence and hardware systems to optimize performance, reliability, and energy efficiency. His research delves deep into areas like deep reinforcement learning, optimized channel bonding, and intelligent transmit power control mechanisms, all aimed at enhancing wireless network efficiency. His work reflects a keen understanding of current technological trends and a vision for future innovations in electronics and communication engineering.

Award

Although specific awards have not been documented, Rajender Singh Yadav’s professional journey itself stands as a testament to his dedication and excellence. His consistent progression through reputed institutions, long-standing teaching career, and contribution to the academic field highlight the recognition and trust he has garnered within the educational community. His involvement in publishing impactful research in reputed international journals showcases his commitment to scholarly excellence and innovation.

Publication

Rajender Singh Yadav has contributed notably to academic literature. One of his significant publications is titled “Joint Optimization of Channel Bonding and Transmit Power Using Optimized Actor–Critic Deep Reinforcement Learning for Wireless Networks”, published in the International Journal of Communication Systems on May 10, 2025. This research explores the integration of optimized actor–critic deep reinforcement learning models to simultaneously enhance channel bonding and transmit power efficiency in wireless networks. The article has already begun to gain citations and is recognized for its practical approach to complex wireless communication challenges. This work stands out for its novel methodology and potential applications in next-generation network systems, demonstrating his ability to merge theoretical research with practical technological needs.

Conclusion

In conclusion, Mr. Rajender Singh Yadav is a seasoned educator and dedicated researcher whose contributions to Electronics and Communication Engineering have been remarkable. With a solid academic background, a wealth of teaching experience, and a keen interest in advanced research areas like AI and embedded systems, he continues to influence and inspire the academic and research communities. His efforts in mentoring students, developing innovative research solutions, and publishing impactful studies reflect his unwavering commitment to advancing technology and education. As he moves forward in his career, his passion for innovation and excellence promises to bring about significant contributions to the field of communication engineering and beyond.