Farhad Oroumchian | EV Charging Infrastructure | Innovative Research Award

Posted on by Automobile Award

Innovative Research Award

Farhad Oroumchian
University of Wollongong in Dubai, United Arab Emirates

Farhad Oroumchian
Affiliation University of Wollongong in Dubai
Country United Arab Emirates
Scopus ID 8865329300
Documents 70
Citations 788
h-index 15
Subject Area EV Charging Infrastructure
Event Global Automobile Award
ORCID 0000-0001-7942-5965

The Innovative Research Award recognizes research contributions that demonstrate methodological quality, relevance, and potential value to their respective fields. Farhad Oroumchian is presented in connection with research activity in EV Charging Infrastructure, with an academic profile associated with 70 documents, 788 citations, and an h-index of 15.

Abstract

Farhad Oroumchian is an academic researcher affiliated with the University of Wollongong in Dubai whose documented research activity includes work relevant to EV Charging Infrastructure. His scholarly profile records 70 documents, 788 citations, and an h-index of 15, providing quantitative indicators of sustained publication and citation activity. Research in electric vehicle charging infrastructure addresses important challenges associated with charging accessibility, system integration, energy management, interoperability, and sustainable transportation. Within the context of the Innovative Research Award, his profile represents research activity aligned with technological development and emerging mobility requirements. The recognition emphasizes scholarly contribution, relevance, research continuity, and potential practical value to automobile engineering.

Keywords

Innovative Research Award; Farhad Oroumchian; EV Charging Infrastructure; electric vehicles; charging systems; sustainable mobility; automobile engineering; energy management; transportation technology; research impact.

Introduction

Electric vehicle charging infrastructure is an important research area within the transition toward electrified transportation. Research addresses charging networks, energy demand, infrastructure planning, intelligent charging, and integration with electricity systems. These topics require interdisciplinary approaches combining engineering, energy systems, information technologies, and transportation research.

Academic assessment commonly considers publication activity alongside citation indicators and broader evidence of research contribution. Scopus provides bibliographic and citation information that can support the evaluation of scholarly output, while ORCID provides persistent identification for researchers and their works.[1][2]

Research Profile

Farhad Oroumchian is affiliated with the University of Wollongong in Dubai, United Arab Emirates. The supplied Scopus profile identifies the researcher with Author ID 8865329300 and records 70 documents, 788 citations, and an h-index of 15. These indicators describe the documented scholarly record used for this recognition.

  • Affiliation: University of Wollongong in Dubai.
  • Primary subject area: EV Charging Infrastructure.
  • Scopus documents: 70.
  • Reported citations: 788.
  • Reported h-index: 15.

Research Contributions

Research associated with EV Charging Infrastructure contributes to the development of transportation systems capable of supporting growing electric vehicle adoption. Key research dimensions include charging availability, infrastructure optimization, energy efficiency, charging coordination, grid interaction, and user-oriented charging services.

The broader field also involves integration between charging infrastructure and emerging smart-mobility systems. Such integration can support improved utilization of energy resources and more coordinated transportation planning. Scholarly contributions are therefore evaluated through technical rigor, relevance, reproducibility, and demonstrated applicability.

Publications

The supplied research profile reports 70 Scopus-indexed documents associated with Farhad Oroumchian. Because individual publication titles, journal information, publication years, and DOI identifiers were not supplied, this page does not attribute specific publications or DOI records without verification. The publication count is presented as a profile-level bibliometric indicator.

Publication assessment may consider peer-reviewed outputs, relevance to the subject area, methodological quality, citation performance, and contribution to ongoing research. Bibliographic databases can provide useful quantitative evidence, although publication and citation indicators should be interpreted within the context of disciplinary practices.[1]

Research Impact

The reported 788 citations indicate that the research record has received substantial scholarly attention within the indexed literature. The h-index of 15 further indicates a measurable body of publications that has reached corresponding citation thresholds. These indicators provide quantitative evidence but do not independently establish societal or technological impact.

Award Suitability

The Innovative Research Award is suitably aligned with a research profile focused on EV Charging Infrastructure because the field addresses emerging technological requirements in electric mobility. Farhad Oroumchian’s reported publication and citation indicators provide a quantitative basis for considering sustained scholarly activity within this research domain.

Conclusion

Farhad Oroumchian’s documented academic profile reflects sustained research activity, with 70 documents, 788 citations, and an h-index of 15. His association with EV Charging Infrastructure places the research within a strategically important area of electric mobility. The profile therefore provides relevant evidence for consideration under an Innovative Research Award framework.

References

  1. Elsevier. (n.d.). Scopus author details: Farhad Oroumchian, Author ID 8865329300. Scopus.
    https://www.scopus.com/pages/authors/8865329300
  2. ORCID. (n.d.). ORCID record: Farhad Oroumchian. ORCID.
    https://orcid.org/0000-0001-7942-5965
  3. Global Automobile Award. (n.d.). Global Automobile Award.
    https://automobileaward.com/

  4. A Multi-Criteria and AI-Assisted Optimization Framework for EV Charging Station Optimization in Mixed Urban–Rural Contexts.
    https://www.mdpi.com/2032-6653/17/5/243

  5. Time sensitive blog retrieval using temporal properties of queries.
    https://www.researchgate.net/publication/287998154_Time_sensitive_blog_retrieval_using_temporal_properties_of_queries

  6. Integration of data fusion and reinforcement learning techniques for the rank-aggregation problem.
    https://link.springer.com/article/10.1007/s13042-015-0442-6

Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Posted on by Automobile Award

Ms. Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Doctoral Researcher  |  Kocaeli University  |  Turkey

Ms. Ayşe Tuğba Yapıcı is a dedicated doctoral researcher whose academic journey is strongly rooted in cutting-edge technologies for electric vehicles, smart energy systems, and intelligent power electronics. She has cultivated significant professional experience through her active involvement in research addressing real-world problems such as electric vehicle charging optimization, grid-integrated charging infrastructures, and advanced modeling of power converter systems. Throughout her career, she has contributed to impactful scientific studies focusing on induction heating systems, charging time prediction using deep learning, and data-driven forecasting on electric vehicle adoption and infrastructure planning. Her research interests include electric vehicle technologies, charging station design, renewable-integrated smart grids, artificial intelligence–based energy forecasting, machine learning and deep learning applications in power systems, and IoT-enhanced smart mobility frameworks. She possesses strong research skills in Python-based deep learning toolkits, MATLAB/Simulink, DigSilent PowerFactory modeling, statistical evaluation metrics, time-series forecasting, optimization algorithms, and performance analysis of intelligent systems. She has published multiple peer-reviewed articles in international SCI/Scopus-indexed journals, delivering innovative research outcomes that offer comprehensive and practical solutions for the sustainable development of electric transportation. Her research achievements include proposing an intelligent deep learning–based framework for EV charging time prediction, integrating spatial–temporal mobility parameters, and enhancing operational efficiency for fast-charging infrastructures. Her work stands out for its interdisciplinary approach and technological significance, supporting the transition toward cleaner mobility, optimized charging networks, and smart energy management. In addition to research excellence, she continues to contribute to academic and scientific communities through conference participation, collaborations, and knowledge dissemination. She aims to advance secure, intelligent, and scalable charging automation systems that support next-generation autonomous electric mobility. Her long-term vision is to shape energy-efficient transportation ecosystems, reduce environmental impacts, and contribute to the global sustainability agenda through innovation and scientific leadership. She has achieved  3 Citations , 2 Documents,  1 h-index.

Featured Publications

Yapıcı, A. T., & Abut, N. (2025, November 23). An intelligent and secure IoT-based framework for predicting charging and travel duration in autonomous electric taxi systems. Applied Sciences.

Yapıcı, A. T., Abut, N., & Yıldırım, A. (2025, October 27). Estimation of future number of electric vehicles and charging stations: Analysis of Sakarya Province with LSTM, GRU and multiple linear regression approaches. Applied Sciences.

Yapıcı, A. T., & Abut, N. (2025, August 21). Geleceğe yönelik elektrikli araç ve şarj istasyonu sayılarının LSTM ve GRU derin öğrenme yöntemleri kullanılarak tahmin edilmesi: Kocaeli ili örneği. Politeknik Dergisi.

Yapıcı, A. T., Abut, N., & Erfidan, T. (2025, April 11). Comparing the effectiveness of deep learning approaches for charging time prediction in electric vehicles: Kocaeli example. Energies.

Yapıcı, A. T., & Abut, N. (2024, September 15). Elektrikli araç şarj istasyonu konum tasarımında, Digsilent yazılımı kullanılarak Kocaeli Üniversitesi Umuttepe Kampüsü için örnek uygulama. Black Sea Journal of Engineering and Science.

Ayşe Tuğba Yapıcı’s research advances intelligent and sustainable electric mobility by integrating deep learning, smart grid technologies, and IoT-based predictive frameworks to optimize charging infrastructure and energy management. Her work supports the transition toward autonomous electric transportation, reducing environmental impacts, improving urban mobility planning, and contributing to global innovation in smart energy systems. She envisions scalable, reliable, and human-centered smart mobility ecosystems that accelerate the adoption of clean transportation worldwide.