Gelareh Vakili | Data Science and Analytics | Innovative Research Award

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Innovative Research Award

Gelareh Vakili
University of Maryland, Baltimore County
Gelareh Vakili
Affiliation University of Maryland, Baltimore County
Country United States
Scopus ID 60765665400
Documents 1
Subject Area Data Science and Analytics
Event International Innovator Awards
ORCID 0000-0003-3384-3840

Gelareh Vakili is a researcher affiliated with the University of Maryland, Baltimore County in the United States, with a stated subject area of Data Science and Analytics. The researcher is associated with Scopus Author ID 60765665400 and an ORCID identifier that provides a persistent digital identifier for scholarly activities. The supplied researcher record lists one document; citation and h-index values were not provided in the source information for this article.[2]

Abstract

Innovative Research Award profiles the academic and research record of Gelareh Vakili, affiliated with the University of Maryland, Baltimore County, United States. The supplied information associates the researcher with Data Science and Analytics and identifies a Scopus Author ID and ORCID record. Scopus is a major bibliographic and citation database used to index scholarly literature and provide author-level publication information. ORCID provides persistent identifiers intended to distinguish researchers and connect them with their scholarly contributions. On the basis of the supplied record, the profile documents one indexed publication and provides a foundation for describing the researcher’s academic activity without making unsupported claims about citation impact or research excellence.[1]

Keywords

Data Science and Analytics; Data Science; Analytics; Research Innovation; Academic Research; Scholarly Communication; Bibliometrics; Researcher Profile; University of Maryland, Baltimore County; International Innovator Awards; ORCID; Scopus.

Introduction

Data science and analytics encompass methodological approaches for collecting, processing, interpreting, and communicating information derived from data. Contemporary research in these areas commonly integrates statistical reasoning, computational methods, data management, and analytical techniques to address questions across scientific and applied domains. A researcher’s scholarly profile can therefore be considered through several complementary dimensions, including documented publications, subject-area classification, persistent identifiers, institutional affiliation, and measurable bibliographic indicators. [1]

Research Profile

The supplied academic profile places Gelareh Vakili at the University of Maryland, Baltimore County and identifies Data Science and Analytics as the principal subject area. The available bibliographic information lists one document in the supplied Scopus record. Because no citation count or h-index value was supplied, those indicators are intentionally reported as unavailable rather than estimated. This distinction is important because bibliometric measures can vary according to database coverage, publication type, indexing status, and the date on which the record is examined. [1]

Research Contributions

The available information supports describing Gelareh Vakili’s research profile in relation to Data Science and Analytics. However, a detailed assessment of specific methodological contributions requires access to the researcher’s publications, abstracts, datasets, software, or other scholarly outputs. Accordingly, the contribution profile below is limited to areas that can be reasonably connected with the supplied subject classification and bibliographic record. [2]

Publications

The supplied record specifies 1 document associated with the Scopus profile. No publication title, journal, year, authorship details, pages, or DOI were included in the input data. Consequently, no publication-specific bibliographic information or DOI has been inferred for this article. [3]

Research Impact

Research impact may be evaluated using multiple forms of evidence, including citations, scholarly dissemination, adoption of research outputs, collaboration, policy or industry use, and contributions to subsequent research. Bibliometric indicators such as citation counts and h-index values can provide useful quantitative signals, but they should be interpreted in relation to disciplinary norms and the coverage of the database being used. [1]

Award Suitability

The International Innovator Awards provides the stated recognition context for this profile. Based on the supplied information, Gelareh Vakili has a documented affiliation with the University of Maryland, Baltimore County, a research classification in Data Science and Analytics, an indexed Scopus record, and persistent scholarly identifiers. These elements provide verifiable components for an academic recognition profile. [1]

Conclusion

Gelareh Vakili is presented in the supplied academic record as a researcher affiliated with the University of Maryland, Baltimore County and associated with Data Science and Analytics. The available information includes a Scopus Author ID, an ORCID identifier, and one reported Scopus document. These identifiers and bibliographic details provide a basis for documenting the researcher’s scholarly profile.[2]

References

  1. Elsevier. (2026). Scopus author details: Gelareh Vakili, Author ID 60765665400. Scopus.https://www.scopus.com/authid/detail.uri?authorId=60765665400
  2. ORCID. (2026). ORCID record: Gelareh Vakili, ORCID iD 0000-0003-3384-3840. ORCID.https://orcid.org/0000-0003-3384-3840
  3. International Innovator Awards. (2026). Official website of the International Innovator Awards.https://innovatorawards.org/

Hongbin Yan | Applied Soft Computing | Research Excellence Award

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Prof.  Hongbin Yan | Applied Soft Computing | Research Excellence Award

School of Business, East China University of Science and Technology | China 

Yan Hongbin is a professor of Management Science and Engineering at East China University of Science and Technology (ECUST), where he also serves as a PhD supervisor. He earned a PhD from the Japan Advanced Institute of Science and Technology, following earlier degrees in management from Dalian University of Technology. His teaching covers management information systems, information system analysis and design, IT service management (for MBA students), and research methodology for master and doctoral students. His research centers on decision analysis under uncertainty, new product development, service and quality management, technological innovation, and Kansei (emotion-based) engineering. Over his career, he has authored many peer-reviewed journal and conference papers in outlets such as Computers & Industrial Engineering, Omega, IISE Transactions and others; his work has attracted substantial scholarly attention. According to his public academic profile, his publications have been cited hundreds of times, and his citation count on one platform exceeds seven hundred. Overall, his scholarly output and impact place him among the active contributors in the fields of management science and decision support.

Profile: ORCID 

Featured  Publications 

Yan, H.-B., Qu, L., & Huynh, V.-N. (2025).
A probability based linguistic decision making approach to reliable Kano model for classifying quality attributes. Applied Soft Computing, 114381.

Chen, Z., Zhou, X., Zhang, Z., Yan, H., Niu, X., & Li, Y. (2025).
Using the decomposed theory of planned behavior and a structural equation model with partial least squares to investigate construction and demolition waste reduction behavior. Journal of Construction Engineering and Management, 15810.

Wang, W., Li, Y., Yan, H., Zhao, W., Zhao, Q., & Luo, K. (2025).
A two-phase algorithm for the dynamic time-dependent green vehicle routing problem in decoration waste collection. Expert Systems with Applications, 125570.

Mr. Syed Adeel Haneef Zaidi – Digital Twins in Supply Chian Management Performance – Best Researcher Award

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Mr. Syed Adeel Haneef Zaidi - Digital Twins in Supply Chian Management Performance - Best Researcher Award

École de technologie supérieure ÉTS - Canada

Author Profile

GOOGLE SCHOLAR

Early academic pursuits 🎓

Syed Adeel Haneef Zaidi began his academic journey with a deep passion for engineering and systems management. his educational foundation was built through a master's degree in engineering, which allowed him to specialize in industrial systems. this strong academic background not only gave him theoretical knowledge but also practical insights into the world of industrial systems engineering. his studies laid the groundwork for his future professional endeavors, where he combined academic excellence with practical expertise.

Professional endeavors 🏭

Adeel Zaidi has carved out a significant career in both academia and industry. since july 2018, he has been serving as a lab instructor ii in the industrial systems engineering department at the university of regina. in this role, he oversees laboratory experiments, develops new course content, and actively contributes to academic and administrative matters. before transitioning into academia, he worked in the fast-paced manufacturing industry at peel plastic products ltd. in brampton, ontario. here, he contributed to continuous improvement initiatives, troubleshooting automated machinery, and enhancing production processes.

Contributions and research focus 🔬

his contributions extend to both industrial and academic sectors. in academia, he plays a pivotal role in developing and revising laboratory contents for courses in industrial systems engineering, ensuring the continuous improvement of learning outcomes. he is involved in the installation and setup of cutting-edge lab equipment, ensuring students have access to up-to-date experimental setups. his research focus Digital Twins in Supply Chian Management Performance includes the application of simulation techniques and the integration of new equipment to enhance both learning and productivity in industrial processes.

Accolades and recognition 🏅

adeel zaidi's efforts in both the academic and industrial spheres have been met with recognition. at the university of regina, he is highly regarded for his dedication to student development, as he assists students with modeling, simulation, data collection, and project interpretation. his Digital Twins in Supply Chian Management Performance commitment to continuous professional development has enabled him to transfer valuable skills and knowledge to the next generation of engineers. his work at peel plastic products ltd. also demonstrated his ability to solve real-world problems, leading to improvements in quality and production efficiency.

Impact and influence 🌟

Adeel Zaidi's impact is felt in multiple areas. in academia, his role as a lab instructor influences the educational journey of countless engineering students, preparing them for successful careers in industrial systems. in the manufacturing sector, his contributions to continuous improvement Digital Twins in Supply Chian Management Performance and process optimization have directly led to enhanced production capacities and reduced costs. his work ensures that both the academic and industrial sectors benefit from his expertise in modern engineering solutions.

Legacy and future contributions 🔮

as a dedicated educator and engineer, adeel zaidi's legacy is one of innovation and continuous improvement. his contributions to developing state-of-the-art laboratory setups at the university of regina will benefit students for years to come. furthermore, his ability to apply advanced engineering principles to real-world industrial challenges positions him as a forward-thinking professional. his future contributions will likely focus on further enhancing educational techniques and improving industrial processes, ensuring his impact continues to grow.

Notable Publications 

Implementation of Inventory Management System in a furniture company 2012(16)

Unlocking the potential of digital twins in supply chains: A systematic review  2024

Dr. Ajay K. Palit – Computational Intelligence – Best Researcher Award

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Dr. Ajay K. Palit - Computational Intelligence - Best Researcher Award

University of Bremen - Germany

Professional Profile 

SCOPUS

EARLY ACADEMIC PURSUITS 🎓

Ajay K. Palit and Dobrivoje Popovic, distinguished scholars in the field of computational intelligence, began their academic journeys with a robust foundation in engineering and mathematics. Their early work laid the groundwork for their future contributions to the field of time series forecasting and industrial process control. Both scholars pursued advanced studies and research in their respective areas, developing a deep understanding of computational techniques and their applications in real-world scenarios.

PROFESSIONAL ENDEAVORS 🏢

Dr. Ajay K. Palit and Dr. Dobrivoje Popovic are both affiliated with the University of Bremen, Germany, where they continue to drive innovation in computational intelligence. Their professional careers are marked by significant roles in academia and industry, focusing on enhancing the effectiveness of time series forecasting through advanced computational techniques. Their expertise extends to the practical applications of these techniques in industrial systems and process control.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Palit and Popovic have made notable contributions to the field of computational intelligence, particularly in time series forecasting. Their research encompasses a range of intelligent technologies, including neural networks, fuzzy logic, and evolutionary computation. They have pioneered hybrid computational approaches, such as neuro-fuzzy and transparent fuzzy/neuro-fuzzy modeling, which offer improved quality, Computational Intelligence model building, and predictive control in industrial processes. Their work addresses the challenges of on-line application and computational efficiency in industrial settings.

ACCREDITATIONS AND RECOGNITION 🏅

Their pioneering work has been widely recognized and has earned them respect in the academic and industrial communities. The book "Computational Intelligence in Time Series Forecasting: Theory and Engineering Applications" by Palit and Popovic is acclaimed for its Computational Intelligence comprehensive exploration of intelligent technologies and their practical applications. The authors' contributions are integral to the ongoing development and refinement of computational tools used in industrial process control and forecasting.

IMPACT AND INFLUENCE 🌍

The influence of Palit and Popovic’s work extends across various industries, including manufacturing, process control, and research. By advancing computational intelligence techniques, they have significantly improved the ability to forecast and control industrial processes. Their research has helped bridge the gap between theoretical knowledge and practical application, making a tangible impact on industrial efficiency Computational Intelligence and predictive accuracy.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Ajay K. Palit and Dobrivoje Popovic continue to inspire and lead in their field, shaping the future of computational intelligence in time series forecasting. Their legacy is reflected in their innovative approaches and the ongoing relevance of their research in addressing complex industrial challenges. As they advance their work, they remain committed to exploring new computational techniques and applications, ensuring their contributions will have a lasting impact on the field.

NOTABLE PUBLICATIONS

Fault diagnosis of crosstalk induced glitches and delay faults  2010(1)

Test pattern generation and compaction for crosstalk induced glitches and delay faults  2010(6)

Decoupled victim model for the analysis of crosstalk noise between on-chip coupled interconnects  2009(14)

Equivalent victim model of the coupled interconnects for simulating crosstalk induced glitches and delays  2009(7)

Distributed RLGC transient model of coupled interconnects in DSM chips for crosstalk noise simulation 2008(8)