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

Jamal Alotaibi | Engineering | Best Researcher Award

Assist. Prof. Dr. Jamal Alotaibi | Engineering | Best Researcher Award

Department of Computer Engineering, College of Computer, Qassim University, Buraydah, Saudi Arabia.

Dr. Jamal Alotaibi is an accomplished researcher and educator in the field of Computer Engineering. With expertise in IoT, AI, and security, he has contributed significantly to the advancement of Smart Transportation and Vehicle-to-Vehicle (V2V) communication. Currently serving as the Head of the Computer Engineering Department at Qassim University, his work focuses on secure and efficient computing frameworks for the Internet of Vehicles (IoV).

Profile

Google Scholar

Education 🎓

  • Ph.D. in Computer Engineering (2018 – 2022) – Wayne State University, USA

  • M.Sc. in Electrical and Computer Engineering (2016 – 2017) – Wayne State University, USA

  • B.Sc. in Computer Engineering (2008 – 2013) – Qassim University, KSA

Experience 👨‍🏫

  • Qassim University (2022 – Present) – Assistant Professor, now Head of the Computer Engineering Department (2024–Present)

  • Wayne State University (2016 – 2022) – Research Assistant in IoT and Security Labs

  • STC Company (2013) – Network Engineer

  • Consultations:

    • Ford Motor Company (2020 – 2022) – Embedded Systems Consultant for Electric Vehicles

    • Verizon Company (2021–2022) – V2V Infrastructure Consultant

    • City of Detroit (2021–2023) – IoV Consultant

Research Interests 🔬

  • Internet of Vehicles (IoV) and Fog Computing

  • Software-Defined Networking (SDN) for Smart Transportation

  • Blockchain-based Security Solutions

  • Machine Learning for Secure Communication Systems

Awards 🏆

  • Head of IoT Research Lab – Wayne State University

  • Head of Research Committee – Qassim University (2023 – Present)

Publications Top Notes: 📚

SAFIoV: A Secure and Fast Communication in Fog-Based IoV Using SDN and Blockchain

IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2021

Read Here

A Lightweight and Fog-Based Authentication Scheme for Internet-of-Vehicles

IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEM-CON), 2021

Read Here

PPIoV: A Privacy-Preserving Framework for IoV-Fog Using Federated Learning and Blockchain

IEEE World AI IoT Congress, 2022

Read Here

Insight into IoT Applications and Common Practice Challenges

Insight Journal, 2022

Read Here

A hybrid software-defined networking approach for enhancing IoT cybersecurity with deep learning and blockchain in smart cities

SDN-Enabled Efficient Resource Utilization in a Secure, Trustworthy and Privacy Preserving IOV-Fog Environment

Jebin Samuvel T | Engineering | Global Impact in Research Award

Mr. Jebin Samuvel T | Engineering | Global Impact in Research Award

Research Scholar Indian Institute of Technology Madras India

Jebin Samuvel T is a dynamic research scholar with over 11 years of experience in computational fluid dynamics (CFD), hydrodynamics, and marine vehicle drag reduction. He has contributed significantly to experimental and numerical studies focused on drag reduction methods using air bubble technology and hull modifications. With a strong academic foundation and hands-on industry-oriented research, he blends theoretical expertise with practical implementation. Currently pursuing a Ph.D. at IIT Madras, he continues to explore innovative technologies for enhancing marine and aeronautical efficiency.

Profile

Scopus

Google Scholar

Orcid

🎓 Education

Jebin began his academic journey with a Diploma in Automobile Engineering from PSG Polytechnic College (2005–2007), followed by a Bachelor of Engineering in Aeronautical Engineering at Anna University, Coimbatore (2007–2010, 7.6 CGPA). He then completed a Master’s in Aeronautical Engineering at Park College of Engineering and Technology (2010–2012, 7.9 CGPA). Presently, he is pursuing his Doctorate in Ocean Engineering at IIT Madras (2018–Present, 7.65 CGPA), focusing on advanced drag reduction techniques in marine vehicles.

💼 Experience

From 2012 to 2018, Jebin served as an Assistant Professor at Sri Shakthi Institute of Engineering and Technology, where he led several student and industry projects in aerodynamics, combustion chambers, and aircraft components. Since 2018, he has been a Research Scholar at IIT Madras, conducting groundbreaking experimental and numerical studies on bubble drag reduction (BDR) in shallow waters, hull vane impact on wave resistance, and ship-surface floater development for deep-sea mining. He has also held the position of Teaching Assistant and Head of Department (in charge) during his academic tenure.

🔬 Research Interests

Jebin’s research primarily focuses on:

  • 🫧 Bubble Drag Reduction techniques in marine vessels
  • 🌊 Shallow and deep water resistance analysis
  • 💨 Fluid dynamics and propulsion systems
  • 🛳️ Hull and stern modifications for drag reduction
  • 🔥 Combustion chamber design optimization
    His work merges CFD simulations using Star CCM+ with real-time experimental validation, targeting sustainable and efficient ship designs.

🏆 Awards & Achievements

  • 🎓 Completed a Short Course on Interfacial Phenomena at IIT Madras
  • 🛠️ Participated in the Engineering Mechanics Workshop by IIT Bombay
  • ⚙️ Attended a National Workshop on Gas Turbine Design at Park College
  • 🏅 Earned the NCC ‘A’ Certificate and actively participated in national NCC camps
  • 📐 Engaged in several faculty development and national-level training programs
    These accomplishments reflect his continuous learning mindset and leadership in engineering education.

📚 Publications Top Notes: 

Samuvel, J. T., Gokulakrishnan, M., Kumar, A., & Ramamurthy, V. (2022). Numerical Estimation of Frictional Drag on Flat Plate In Shallow Water with & without BDR. OCEANS 2022 – Chennai. Cited by: 3

Gokulakrishnan, M., Samuvel, J. T., Kumar, A., & Ramamurthy, V. (2022). Numerical prediction of hydrodynamic forces and moments of KCS in shallow water. OCEANS 2022 – Chennai. Cited by: 2

Impact of Water Depth on the Resistance of a Mini-Bulk Carrier: An Experimental and Numerical Study

Lilian Huang | Engineering | Best Researcher Award

Prof. Lilian Huang | Engineering | Best Researcher Award

Professor Harbin Engineering University China

Lilian Huang is a professor at the School of Information and Communication Engineering, Harbin Engineering University. With a strong background in navigation, guidance, and control, she has made significant contributions to fractional-order chaotic systems, nonlinear dynamics, and chaos-based encryption. Her research has been widely published in high-impact journals, and she holds multiple patents related to chaotic system control and encryption techniques.

Profile

Scopus

🎓 Education

Lilian Huang earned her Ph.D. (2005) and Master’s (2002) in Navigation, Guidance, and Control from Harbin Institute of Technology. She completed her Bachelor’s in Automation from Zhongyuan University of Technology in 1996. Her academic journey laid a strong foundation for her expertise in control systems and nonlinear dynamics.

💼 Experience

Currently serving as a professor at Harbin Engineering University since 2012, Lilian Huang has also worked as an associate professor (2005-2012) and postdoctoral researcher (2005-2008) at the same institution. She was a visiting scholar at the University of Delaware in 2016-2017. Before joining academia, she worked as an assistant engineer at Harbin Dong’an Engine Manufacturing Co., Ltd. (1996-2000), gaining industry experience.

🔬 Research Interests

Lilian Huang’s research focuses on fractional-order chaotic systems, nonlinear dynamics, and chaos control. She explores their applications in encryption, secure communication, and dynamic system analysis. Her work contributes to developing novel chaotic systems with enhanced security features for information processing.

🏆 Awards & Recognitions

She has led several prestigious research projects funded by the National Natural Science Foundation of China and Heilongjiang Province. Her innovations in chaos-based encryption and nonlinear control have been recognized through numerous patents and high-impact publications.

📚 Publications Top Notes: 

Multi-Image Encryption Algorithm Based on Novel Spatiotemporal Chaotic System and Fractal GeometryIEEE Transactions on Circuits and Systems I, 2024. Read here

Design and Implementation of Grid-Wing Hidden Chaotic Attractors with Only Stable EquilibriaIEEE Transactions on Circuits and Systems I, 2023. Read here

Generating Multiwing Hidden Chaotic Attractors with Only Stable Node-FociIEEE Transactions on Industrial Electronics, 2024. Read here

A Construction Method of N-Dimensional Non-Degenerate Discrete Memristive Hyperchaotic MapChaos, Solitons & Fractals, 2022. Read here

A Novel 3D Non-Degenerate Hyperchaotic Map with Ultra-Wide Parameter Range and Coexisting AttractorsNonlinear Dynamics, 2023. Read here

huayu qi | Engineering | Best Researcher Award

Mr. huayu qi | Engineering | Best Researcher Award

Shandong University of Technology China

Qi Huayu is a dedicated researcher and master’s student at Shandong University of Technology. With a strong focus on particle morphology quantification, Qi has contributed significantly to developing innovative methods for characterizing particle structures. Through rigorous research, Qi aims to advance scientific understanding and practical applications in the field of particle analysis.

Profile

Scopus

Orcid

Education 🎓

  • Master’s Degree | Shandong University of Technology

Experience 👨‍🔬

  • Engaged in research on particle morphology quantification and regeneration.
  • Published multiple papers in high-impact scientific journals.
  • Developed quantitative analysis methods for particle characterization.

Research Interests 🔬

  • Particle Morphology Quantification
  • Triangle Side Ratio Method for Angularity Characterization
  • Multi-scale Particle Morphological Analysis
  • Application of Morphology Analysis in Engineering and Material Science

Awards 🏆

  • Best Researcher Award (Nominee, 2025)
  • Recognition for innovative contributions in particle morphology quantification.

Publications Top Notes: 📚

“Particle morphology quantification and regeneration based on triangle side ratio”

Granular Matter (2025)

DOI: 10.1007/s40571-025-00919-y

Cited by: Pending citation data

“Triangle Side Ratio Method for Particle Angularity Characterization: From Quantitative Assessment to Classification Applications”

Granular Matter (2024)

DOI: 10.1007/s10035-024-01449-9

Cited by: Pending citation data

“Multi-scale morphological quantification of particle based on altitude-to-chord ratio”

 

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

ABDUL SAMI | Engineering | Young Scientist Award

Mr. ABDUL SAMI | Engineering | Young Scientist Award

Lecturer Numl University Hyderabad Pakistan

Engr. Abdul Sami Shaikh is a seasoned software engineering professional with a diverse portfolio in academia, research, and freelancing. His career is marked by significant contributions to IT education, cutting-edge research, and innovative development practices. Based in Hyderabad, Sindh, Abdul Sami is driven by a passion for leveraging technology to address real-world challenges and enhance learning.

Profile

Orcid

Education 🎓

Abdul Sami Shaikh has a strong academic foundation with a Master of Engineering in Information and Communication Engineering from Harbin Engineering University, China (2013-2016), achieving an impressive 3.77 CGPA. His undergraduate degree in Computer System Engineering from Mehran University of Engineering and Technology, Jamshoro (2005-2009), laid the groundwork for his technical expertise. Earlier, he pursued Pre-Engineering at Govt. Boys Degree College, Qasimabad, Hyderabad, and completed his schooling at the Model School of Sindh University.

Experience 💼

Abdul Sami has an extensive teaching and research background, having served as a lecturer at Isra University, National University of Modern Languages (NUML), and other prestigious institutions. His professional journey includes roles such as Research Associate at Mehran UET, Program Coordinator for the National Freelance Training Program, and editorial assistant for the Mehran UET Research Journal. He also gained valuable industrial experience through internships with organizations like Sui Southern Gas Company and Microsoft.

Research Interests 🔬

His research focuses on machine learning, data visualization, deep learning, and their applications in healthcare and cybersecurity. He has explored innovative solutions in image analysis, mobile app automation for Industry 4.0, and advanced threat detection systems. Abdul Sami also delves into challenges in spatial crowdsourcing and IoT-based systems.

Awards and Recognitions 🏆

While Abdul Sami has not listed specific awards, his academic and professional milestones, coupled with his impactful publications, position him as a strong candidate for recognition in research and innovation.

Publications Top Notes: 📚

Acoustic Propagation and Transmission Loss Analysis in Shallow Water

Automated Classification of Pneumonia from Chest X-Ray Images using EfficientNet-B0