Peng Bo | Robotics | Excellence in Scientific Innovation Award

Dr. Peng Bo | Robotics | Excellence in Scientific Innovation Award

Tsinghua University | China

Dr. Peng Bo is a researcher specializing in control systems, networked autonomous vehicles, and advanced filtering techniques, with a focus on H∞ filtering and event-based control methods for complex networked systems. His work integrates rigorous mathematical modeling, augmented Lyapunov functional approaches, and innovative algorithm design to enhance stability, performance, and reliability in mass-switching autonomous multi-vehicle systems. With a strong foundation in system dynamics and networked control, he has contributed to several high-impact publications, demonstrating a practical yet theoretically robust research approach. His research has influenced both academic developments and real-world applications in intelligent transportation and autonomous systems, reflecting measurable impact through citations and collaborative contributions in his field. Dr. Peng Bo continues to advance methodologies for robust control and optimization in interconnected, dynamic environments.

Citation Metrics (Scopus)

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15

10

5

0

Citations
10

Documents
5

h-index
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🟦 Citations   🟥 Documents   🟩 h-index


View Scopus Author Profile

Featured Publications

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

Ms. HAFSA ANAM | Engineering | Best Researcher Award

Ms. HAFSA ANAM | Engineering | Best Researcher Award

Macquarie University, Australia

Author Profile

Scopus

Orcid

Education 🎓

Hafsa completed her B.Sc. in Telecommunication Engineering in 2015 with a CGPA of 3.78/4.00, and later earned her M.Sc. in Telecommunication Engineering in 2017 with a CGPA of 3.79/4.00, both from the University of Engineering and Technology (UET), Taxila, Pakistan. Currently, she is pursuing her Ph.D. at Macquarie University, working on smart RFID sensor systems for IoT applications.

Professional Experience 💼

As part of her doctoral journey, Hafsa has worked as a Teaching Associate at Macquarie University, actively supporting undergraduate courses. Her role involved lectures, lab sessions, and student mentoring, enabling her to blend cutting-edge research with academic leadership. She also collaborates with interdisciplinary teams to design real-world applicable sensor systems.

Technical Skills 🛠️

Her core strengths lie in chipless RFID design, electromagnetic modeling, wireless communication systems, and flexible sensor fabrication. She is skilled in tools and techniques for antenna design, EM simulations, and printable electronics, with a focus on green, passive, and cost-effective RFID systems.

Teaching Experience👨‍🏫

Hafsa has contributed to several B.Sc. units as a Teaching Associate at Macquarie University. She has assisted in course delivery, lab experiments, and student project supervision, helping to bridge practical RFID development with academic theory.

Awards & Honors 🏅

Hafsa has been recognized with the Post Graduate Research Fund (PGRF) from Macquarie University in 2024 and is the recipient of a fully-funded Ph.D. scholarship (2022–present). Her research excellence earned her the Best Poster Presentation Award at the HDR Conference at Macquarie University in 2022, marking her as an emerging scholar in the RFID research community.

Research Interests 🔍

Her research is centered on chipless RFID tags, wireless communication, electromagnetics, and the Internet of Things (IoT). She is especially interested in developing multifunctional, battery-free RFID sensors that are capable of monitoring environmental parameters, with applications in recycling, smart infrastructure, retail, and industrial systems.

Publications Top Notes: 📝

Dual Sided Data Dense 25-bit Chipless RFID Tag

Authors: Hafsa Anam, Syed Muzahir Abbas, Subhas Mukhopadhyay, Iain Collings

Publication Year: 2023

Publication Type: Conference Paper


RFID Enabled Humidity Sensing and Traceability

Authors: Hafsa Anam, Syed Muzahir Abbas, Iain Collings, Subhas Mukhopadhyay

Publication Year: 2023


High-density Compact Chipless RFID Tag for Item-level Tagging

Authors: Ayesha Habib, Hafsa Anam, Yasar Amin, Hannu Tenhunen

Publication Year: 2018


 Internet-of-things Based Smart Tracking

Author: Hafsa Anam

Publication Year: 2017


Miniaturized Humidity and Temperature Sensing RFID Enabled Tags

Authors: Javeria Anum Satti, Ayesha Habib, Hafsa Anam, Sumra Zeb, Yasar Amin, Jonathan Loo, Hannu Tenhunen

Publication Year: 2018

Journal: International Journal of RF and Microwave Computer-Aided Engineering

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

Xiang Li | Computer Science | Best Researcher Award

Dr. Xiang Li | Computer Science | Best Researcher Award

Associate Researcher Qilu University of Technology (Shandong Academy of Sciences) China

Dr. Xiang Li is an accomplished Associate Researcher at the Qilu University of Technology (Shandong Academy of Sciences) in China, where he has been serving since 2019. With a strong academic foundation in computer science and a research focus spanning EEG-based emotion recognition, multimodal sentiment analysis, and contrastive learning, Dr. Li has published widely in high-impact journals and conferences. His work is recognized internationally, with over 1,700 citations on Google Scholar, reflecting his significant influence in the field of artificial intelligence and affective computing.

Profile

Google Scholar

Orcid

🎓 Education

Dr. Li earned his Ph.D. in Computer Science from the College of Intelligence and Computing at Tianjin University in 2019. He previously received his Master’s degree in Computer Science (2014) and a Bachelor’s degree in Network Engineering (2011), both from the School of Information Science and Technology at Shandong University of Science and Technology.

💼 Experience

Since 2019, Dr. Xiang Li has held the position of Associate Researcher at the Qilu University of Technology. In addition to his research role, he contributes significantly to teaching, instructing several undergraduate and graduate-level courses since 2020, including English for Computer Science, Information Retrieval, and Data Mining, Analysis, and Visualization. His multidisciplinary expertise allows him to merge theory with practice, especially in the intersection of artificial intelligence, neuroscience, and ocean data analytics.

🔬 Research Interests

Dr. Li’s research interests lie in EEG-based emotion recognition, multimodal deep learning, contrastive learning, and affective computing. He has also made substantial contributions to intelligent quality control in ocean observation, shipborne wind speed correction, and biomedical signal processing. His innovative approaches often employ supervised and self-supervised learning frameworks, with a focus on enhancing data-driven decision-making using limited or noisy data.

🏆 Awards

  • 🧠 ESI Highly Cited Paper for “EEG based emotion recognition: A tutorial and review” (2022)
  • 🏅 Recognized for over 1,700 citations on Google Scholar
  • 📈 Several publications with >100 citations, such as his works on quantum-inspired sentiment analysis and cross-subject EEG emotion recognition
  • 🧪 Multiple papers published in SCI Tier-1 journals and top CCF-ranked conferences

📚 Publications Top Notes:  

Below is a selection of Dr. Xiang Li’s publications, presented with hyperlinks, publication years, journals/conferences, and citation data (when available):

📘 2025: Multi-Affection Prompt Learning for Sentiment, Emotion and Sarcasm Joint Detection in Conversations – Tsinghua Science and Technology [SCI-1]

📘 2024: A Supervised Information Enhanced Multi-granularity Contrastive Learning Framework for EEG based Emotion Recognition – ICASSP 2024 [CCF-B]

📘 2024: Self-Supervised Pretraining-Enhanced Intelligent Quality Control for Ocean Observations – ICONIP 2024 [CCF-C]

📘 2024: An Adaptive Time-convolutional Network Online Prediction Method for Ocean Observation Data – SEKE 2024 [CCF-C]

📘 2024: Fusion of Time-Frequency Features in Contrastive Learning for Wind Speed Correction – Journal of Ocean University of China [SCI-3]

📘 2023: EEG-based Parkinson Detection through Supervised Contrastive Learning – BIBM 2023 [CCF-B]

📘 2022: EEG based Emotion Recognition: A Tutorial and Review – ACM Computing Surveys, 55(4) [SCI-1, IF=23.8, Cited by: 272]

📘 2021: Emotion Recognition via Dual-pipeline Graph Attention Network – BIBM 2021 [CCF-B]

📘 2020: Latent Factor Decoding of Multi-channel EEG through Neural Networks – Frontiers in Neuroscience, [SCI-2, Cited by: 81]

📘 2018: Exploring EEG Features in Cross-subject Emotion Recognition – Frontiers in Neuroscience, [SCI-2, Cited by: 369]

📘 2016: Emotion Recognition from Multi-channel EEG via CNN-RNN – BIBM 2016 [CCF-B, Cited by: 320]

📘 2015: EEG-based Emotion Identification Using Deep Feature Learning – ACM SIGIR NeuroIR Workshop [CCF-A Workshop, Cited by: 92]

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

Zhiyao Zhang | Engineering | Best Researcher Award

Prof. Zhiyao Zhang | Engineering | Best Researcher Award

Professor University of Electronic Science and Technology of China

Zhiyao Zhang is a Professor at the University of Electronic Science and Technology of China (UESTC), specializing in microwave photonics and high-speed optoelectronic devices. He earned his Ph.D. in Optical Engineering from UESTC in 2010. Currently, he serves in the School of Optoelectronic Science and Engineering and the Research Center for Microwave Photonics (RC-MWP). He was a Visiting Scholar at the University of Ottawa in 2017. His research contributions include opto-electronic oscillators, photonic analog-to-digital converters, and microwave photonic radars, with over 150 peer-reviewed journal papers published.

Profile

Research Gate

Scopus

🎓 Education

  • Ph.D. in Optical Engineering – University of Electronic Science and Technology of China (UESTC), 2010
  • Visiting Scholar – Microwave Photonics Research Laboratory, University of Ottawa, 2017

💼 Experience

  • Professor, School of Optoelectronic Science and Engineering, UESTC
  • Researcher, Research Center for Microwave Photonics (RC-MWP), UESTC
  • Visiting Scholar, Microwave Photonics Research Laboratory, University of Ottawa (2017)
  • Industry Collaboration, Partnered with Huawei Technologies Co. Ltd to develop next-generation broadband wireless base stations using Radio-over-Fiber (RoF) technology

🔬 Research Interests

  • Microwave Photonics
  • High-speed Optoelectronic Devices
  • Opto-electronic Oscillators (OEOs)
  • Photonic Analog-to-Digital Converters
  • Microwave Photonic Radars

🏆 Awards

  • Award Nomination: Best Researcher Award
  • Research Impact: Over 960 citations
  • Patents: 20 patents (published/under process)
  • Professional Membership: Chinese Society of Optical Engineering

📚 Publications Top Notes:

Zhang, Z., et al. (2023). “Ultra-wideband chaotic signal generation using nonlinear optoelectronic oscillators.” Journal of Lightwave Technology. 🔗 Link (Cited by 45 articles)

Zhang, Z., et al. (2022). “Photonic Analog-to-Digital Conversion with Enhanced Resolution.” Optics Express. 🔗 Link (Cited by 38 articles)

Zhang, Z., et al. (2021). “Externally-triggered ultra-wideband pulse generation in broadband nonlinear OEOs.” IEEE Transactions on Microwave Theory and Techniques. 🔗 Link (Cited by 50 articles)

Zhang, Z., et al. (2020). “Actively Mode-Locked Optoelectronic Oscillators for Short Microwave Pulse Generation.” Nature Communications. 🔗 Link (Cited by 72 articles)

Frequency Response Enhancement of Photonic Sampling Based on Cavity-Less Ultra-Short Optical Pulse Source

Self-referenced electro-optic response measurement of dual-parallel Mach-Zehnder modulators employing single-tone level control and low-frequency bias swing

Self-calibrated characterization of high-speed photodetectors based on slowly-varying-envelope photonic sampling

Linearization in the digital domain for photonic sampling analog-to-digital conversion

Externally-excited Short Pulse Train Generation in a Broadband Nonlinear Optoelectronic Oscillator

Optical Frequency Comb Generation Based on Single-chip Integrated LNOI Intensity and Phase Modulators

 

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”