Mo Jamshidi | Engineering | Best Researcher Award

Prof. Dr. Mo Jamshidi | Engineering | Best Researcher Award

The University of Texas at San Antonio | United States

Prof. Dr. Mo Jamshidi is a globally recognized authority in systems engineering, intelligent systems, and system-of-systems engineering, with seminal contributions spanning soft computing, fuzzy logic, neural networks, robotics, and large-scale complex systems. His research integrates control theory, artificial intelligence, and computational intelligence to address challenges in autonomous systems, energy systems, cloud and cyber-physical infrastructures, and bioinformatics, including influential work on genome-scale metabolic networks. He has played a foundational role in defining and advancing system-of-systems as a discipline, shaping both theoretical frameworks and practical applications. His professional experience reflects sustained leadership in interdisciplinary research, authorship of landmark books, and mentorship that has influenced generations of researchers worldwide.

Citation Metrics (Google Scholar)

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Citations
16,907

i10-index
239

h-index
54

🟦 Citations   🟥 i10-index   🟩 h-index


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Featured Publications

Jinming Liang | Engineering | Best Researcher Award

Mr. Jinming Liang | Engineering | Best Researcher Award

Nanjing University of Aeronautics and Astronautics | China

Mr. Jinming Liang is a dynamic early-career researcher whose work spans electrical impedance tomography, liquid–liquid phase separation, electrochemical impedance spectroscopy, and deep learning for biomedical sensing. His research focuses on developing innovative microscale and portable impedance-based diagnostic systems that enable real-time, high-resolution analysis of cellular behaviors and fluid phase transitions. He has contributed to the advancement of impedance technologies by designing systems capable of accurately monitoring biophysical processes, integrating microfabricated sensors with computational models, and exploring data-driven approaches for improved interpretation of complex impedance signals. His publications include studies on real-time phase separation analysis using electrochemical impedance methods and microscale impedance tomography techniques for detecting cell phase separation, highlighting his ability to translate engineering principles into practical tools for life-science applications. His broader scientific contributions also include work on summarizing progress in phase-separation detection methods as well as participation in patentable innovations related to microscale cell detection and imaging solutions. Through his interdisciplinary expertise, he aims to push the frontier of biomedical instrumentation by creating more compact, intelligent, and accessible sensing platforms that support early diagnosis, mechanistic studies, and precision medicine.

Profile: Orcid

Featured Publications

Liang, J., Zhao, W., Liu, K., Sun, B., Zhu, C., & Yao, J. (2025). Real-time analysis of liquid–liquid phase separation with electrochemical impedance spectroscopy. Microchemical Journal, 116076.

Liang, J., Gao, B., Liu, K., Chai, X., Ji, J., Sun, B., & Yao, J. (2025). Microscale electrical impedance tomography method for cell phase separation detection. IEEE Nanotechnology Magazine.

Tawakalitu Odubiyi | Engineering | Best Researcher Award

Dr. Tawakalitu Odubiyi | Engineering | Best Researcher Award

Research Associate at INTI International University | Malaysia

Dr. Tawakalitu Odubiyi is a Teaching and Research Associate with over six years of international experience spanning Germany, Malaysia, the UK, Finland, South Africa, and Nigeria. She holds a PhD in Civil Engineering from Technische Universität Berlin and a Master’s in Construction Management from the University of Johannesburg. Her expertise lies in Quantity Surveying, Civil Engineering, and the application of Digital Twin and BIM technologies in the built environment.

Profile:

Academic Background

Dr. Odubiyi holds a PhD in Civil Engineering from Technische Universität Berlin, Germany, where her research focused on digital transformation in construction. She also earned a Master of Technology in Construction Management from the University of Johannesburg, South Africa. Her academic background reflects a strong foundation in both technical and managerial aspects of the built environment.

Professional Experience:

Dr. Odubiyi has gained diverse research and teaching experience through various academic and industrial positions. She is currently serving as an Independent Researcher at INTI International University in Malaysia, where she conducts empirical research and leads seminars on sustainable technologies. Previously, she worked as a Research Scientist at Technische Universität Berlin, contributing to projects on business models for Cloud BIM and Digital Twin solutions. Her industry experience includes roles as a BIM Consultant at Bentley Systems in London and a BIM Researcher at Trimble Inc. in Finland, where she developed strategic digital roadmaps and conducted case studies on cost estimation and contract administration. She also served as a Teaching Assistant at the University of Johannesburg and as a Mentor and Lecturer at TU Berlin, demonstrating a strong commitment to student support and academic leadership.

Research and Publications:

Dr. Odubiyi has authored 16 scholarly articles using a mix of qualitative, quantitative, and grounded theory approaches. She has actively presented her findings at international conferences and workshops. Her research focuses on digital transformation in construction, cost management innovation, and the role of BIM in contract and project administration.

Areas of Expertise:

Her core areas of expertise include Quantity Surveying, Construction Management, BIM integration, contract administration (FIDIC, NEC), and curriculum design. She is proficient in BIM tools such as Autodesk Revit, Navisworks, CostX, and Bentley iTwin. She is also experienced in research methodology, grant writing, and academic mentoring across cross-cultural and distance learning environments.

Technical and Professional Skills:

Dr. Odubiyi is skilled in Agile methodologies and tools including Salesforce CRM, Confluence, Jira, Kanban, and BPMN. She has applied these in both academic project management and industry collaborations.

Awards and Recognition:

Dr. Odubiyi has received several prestigious awards, including the Marie Curie Horizon Fellowship from the European Union (2020), the Global Excellence Scholarship from the University of Johannesburg (2019), and the National Research Fellow Bursary (2018). In 2023, she received Community Impact Recognition from the Young Quantity Surveyors of Nigeria for her contributions to the profession.

Citation:

Cited by
All: 141
Since 2020: 132

h-index
All: 8
Since 2020: 8

i10-index
All: 7
Since 2020: 7

Publication Top Notes:

  • Using neural network model to estimate the rental price of residential properties
    2019
    21 citations

  • Strengths, weaknesses, opportunities and threats of virtual team in Nigerian construction industry
    2016
    21 citations

  • Information and communication technology application challenges in the construction industry: A narrative review
    2019
    14 citations

  • A concise review of the evolution of information and communication technologies for engineering innovations
    2021
    13 citations

  • Impact of security on rental price of residential properties: evidence from South Africa
    2019
    13 citations

  • Barriers to implementing quality management system in the Industry 4.0 era
    2019
    12 citations

  • Strategies for building information modelling adoption in the South African construction industry
    2019
    12 citations

  • Impact of Green features on rental value of residential properties: evidence from South Africa
    2024
    8 citations

  • Assessing South African construction worker’s knowledge of modern technologies for effective material management
    2021
    6 citations

  • Evaluation of the use of modern technologies for effective material management in South African construction industry
    2019
    5 citations

  • Bridging the gap between academic and practice Quantity Surveying in Nigerian construction industry
    2019
    5 citations

  • Roles and effects of utilizing recent technologies on material management for construction work in South Africa
    2019
    4 citations

  • Forecasting rental values of residential properties: a neural network model approach
    2020
    3 citations

  • A model validation and predicting the rental values of residential properties using logistic regression model
    2020
    2 citations

  • Information and Communication Technologies for construction services in South Africa: A PROCSA Scope
    2021
    1 citation

  • An Evaluation of Information and Communication Technology Application in South African Construction Industry
    2019
    1 citation

Jingyang Mao | Engineering | Best Researcher Award

Dr. Jingyang Mao | Engineering | Best Researcher Award

Lecturer Shanghai Institute of Technology China

🧑‍🏫 Dr. Jingyang Mao is a dedicated lecturer at the School of Electrical and Electronic Engineering, Faculty of Intelligence Technology, Shanghai Institute of Technology. With a Ph.D. in Control Science and Engineering from the University of Shanghai for Science and Technology (2022), he specializes in cutting-edge research on networked control systems and cyber-physical systems. His academic journey also includes a visiting scholar tenure at Louisiana State University, USA (2019–2021). Dr. Mao’s work bridges theoretical innovations with practical applications in modern engineering systems.

Profile

Orcid

Education

🎓 Ph.D. in Control Science and Engineering (2022)

  • University of Shanghai for Science and Technology, Shanghai, China

✈️ Visiting Scholar (2019–2021)

  • Department of Electrical and Computer Engineering, Louisiana State University, USA

Experience

👨‍💻 Lecturer (2022–Present)

  • School of Electrical and Electronic Engineering, Shanghai Institute of Technology
  • Focus: Cyber-physical systems, networked control, and adaptive filtering

Research Interests

🔍 Dr. Mao’s research interests lie in the fields of:

  • Cyber-physical systems 🌐
  • Multi-rate systems ⏱️
  • Joint recursive filtering 🔄
  • Unknown input estimation
  • Adaptive event-triggered mechanisms ⚙️

Awards

🏆 Award Nomination: Best Researcher Award
Recognized for groundbreaking contributions to the theory and application of cyber-physical systems.

Publications Top Notes:

📄 “Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms”

Event‐based reduced‐order H∞$H_{\infty }$ estimation for switched complex networks based on T‐S fuzzy model

Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

Event-Based Distributed Adaptive Kalman Filtering With Unknown Covariance of Process Noises