Manar Hamza | Computer Science Data mining | Best Researcher Award

Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor at  Prince Sattam bin Abd El Aziz University, China

👩‍🏫 Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. 💻 Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. 🌍 Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education 🎓

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018–2021). 🎓 Master’s Degree in Computer Science from Sudan University of Science and Technology (2003–2005). 🎓 B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995–1999). 📚 Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience 🖥️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). 👩‍💼 Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). 🇸🇩 Lecturer at Omdurman Islamic University, Sudan (2005–2012). 👩‍🔬 E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors 🏆

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. 🙌 Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ⭐ Esteemed arbitrator in scientific and innovation conferences. 📜 Active contributor to enhancing the learning environment with innovative solutions.

Research Focus 🔍

Data mining, text mining, and information security are core research areas. 📊 Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. 🛡️ Exploring cybersecurity methods and their application in education and industry.

✍️Publications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889–1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176–186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486–15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98–114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153–168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258–267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147–11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidate’s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.

Long Chen | Carbon Fiber Reinforced Plastic Laser drilling | Best Researcher Award

Dr. Long Chen | Carbon Fiber Reinforced Plastic Laser drilling | Best Researcher Award

Research Associate at  Huazhong University of Science and Technology, China

🎓 Long Chen is a Research Associate at Huazhong University of Science and Technology and Deputy Director of the R&D Center at Zhejiang Huagong Guanggrun Intelligent Equipment Technology Co., Ltd. (since 2021). 🔬 His research focuses on laser processing technology for carbon fiber composite materials (CFRP). 💡 Long has developed advanced laser processing equipment used in critical aerospace components like satellite antenna covers, engine casings, and missile shells. 📚 He has authored numerous SCI-indexed papers and holds five authorized patents among 14 applications. 🌟 Long actively participates in national and provincial research projects, making significant contributions to the field of intelligent manufacturing.

Professional Profiles:

Education  🎓

PhD in Engineering, Huazhong University of Science and Technology, 2019–2024. 🎓 Bachelor’s Degree in Mechanical Engineering, Top-tier Chinese Institution (Year N/A). 📜 Successfully defended doctoral thesis in 2024 on CFRP laser processing technology. 📚 Academic expertise covers mechanisms of laser interaction with advanced materials, intelligent equipment design, and status monitoring.

Experience  💼

Deputy Director, Zhejiang Huagong Guanggrun R&D Center (2021–present). 💡 Spearheaded innovation funds for CFRP laser processing. 📊 Led 12 enterprise technology development projects. 🌐 Participated in R&D for significant aerospace engineering equipment, contributing to an award-winning project.

Awards and Honors  🏆

First Prize for Science and Technology Progress, Hubei Province, for contributions to aerospace engineering. 🌟 Recognition for advancements in CFRP high-performance manufacturing. 📜 Active member of the China Mechanical Engineering Society and China Society for Composite Materials.

Research Focus  🔬

Exploring acoustic emission signals in CFRP laser cutting, unveiling mechanisms of thermal ablation and mechanical denudation. 📈 Developed RIPL scanning, improving cutting efficiency by up to 33.9%. 🚀 Applications in aerospace and high-performance manufacturing.

 

✍️Publications Top Note :

Alpinetin ameliorates bleomycin-induced pulmonary fibrosisBiomedicine and Pharmacotherapy (2024): 2 citations.

🫁 Associations of prior pulmonary tuberculosis with incident COPDTherapeutic Advances in Respiratory Disease (2024): 0 citations.

🌍 The incidence of tuberculous pleurisy in mainland ChinaFrontiers in Public Health (2023): 4 citations.

📊 Global trends of NAFLD in 204 countriesJMIR Public Health and Surveillance (2022): 22 citations.

🏥 12-month systemic consequences of COVID-19 in discharged patientsClinical Infectious Diseases (2022): 47 citations.

🏥 Global burden of infective endocarditis (1990–2019)Frontiers in Medicine (2022): 69 citations.

🔬 Global burden of urinary tract infections (1990–2019)World Journal of Urology (2022): 73 citations.

🌍 Global trends of maternal infections (1990–2019)BMC Infectious Diseases (2021): 20 citations.

🧮 CAPRL Scoring System for COVID-19 mortality predictionInfectious Diseases and Immunity (2021): 0 citations.

🧪 Immunological characteristics in Type 2 diabetes among COVID-19 patientsFrontiers in Endocrinology (2021): 30 citations.

Conclusion

Long Chen demonstrates an exceptional track record in innovative research, industrial applications, and scholarly contributions to the field of CFRP laser processing. His unique ability to translate research into practical solutions for high-performance manufacturing makes him a strong contender for the Best Researcher Award. Addressing the areas for improvement, particularly in global collaborations and public outreach, could further solidify his candidacy as a leader in advanced manufacturing research.

Atsushi Kakogawa | Robotics and Mechatronics | Best Researcher Award

Assoc. Prof. Dr Atsushi Kakogawa |  Robotics and Mechatronics | Best Researcher Award

Associate Professor at Ritsumeikan University, Japan

🌟 Atsushi Kakogawa, Ph.D., is an Associate Professor in Robotics at Ritsumeikan University, Japan. A pioneer in robotics, he excels in mobile robot design, mechanical systems, and embedded systems. Proficient in programming languages like C++, Python, and more, Dr. Kakogawa has a prolific career marked by teaching, research, and leadership in international robotics conferences.

Profile

scholar

Education🎓 

Doctor of Engineering, Ritsumeikan University, Japan, 2015.  Master of Engineering, Ritsumeikan University, Japan, 2012.  Bachelor of Engineering, Department of Robotics, Ritsumeikan University, Japan, 2010.

Experience💼

Associate Professor, Ritsumeikan University (2023–Present).  Lecturer and Visiting Assistant Professor at University of Waterloo (2017). Assistant Professor, Ritsumeikan University (2015–2019).

Awards and Honors🏆

KAKENHI Grants from Japan Society for the Promotion of Science. Shiga Prefecture Technology Promotion Subsidy (2022). Organizer and Editor roles in top IEEE conferences, including IROS and ICRA.

Research Focus🤖

Robotics: Mobile robot design and mechanical system applications.  Embedded systems and advanced Internet communication technologies.  Multidisciplinary programming in C++, Python, and SQL for robotics innovation.

Publication  Top Notes

Design of a Multilink-Articulated Wheeled Pipeline Inspection Robot Using Only Passive Elastic Joints

Journal: Advanced Robotics, 2018

Citations: 73

Highlights: Introduces a pipeline robot leveraging passive elastic joints for adaptability in complex pipeline systems.

Mobility of an In-Pipe Robot with Screw Drive Mechanism Inside Curved Pipes

Conference: IEEE International Conference on Robotics and Biomimetics, 2010

Citations: 72

Highlights: Explores screw drive mechanisms for pipeline robots navigating curved environments.

Stiffness Design of Springs for a Screw Drive In-Pipe Robot to Pass Through Curved and Vertical Pipes

Journal: Advanced Robotics, 2012

Citations: 55

Highlights: Focuses on optimizing spring stiffness to enhance robot mobility in diverse pipe geometries.

Designing Arm Length of a Screw Drive In-Pipe Robot for Climbing Vertically Positioned Bent Pipes

Journal: Robotica, 2016

Citations: 50

Highlights: Discusses arm length designs crucial for overcoming vertical bends in pipelines.

An In-Pipe Robot with Underactuated Parallelogram Crawler Modules

Conference: IEEE International Conference on Robotics and Automation, 2014

Citations: 48

Highlights: Presents a robot with a novel crawler module enhancing adaptability and efficiency.

Design of a Multilink-Articulated Wheeled Inspection Robot for Winding Pipelines: AIRo-II

Conference: IEEE/RSJ Intelligent Robots and Systems, 2016

Citations: 46

Highlights: Develops AIRo-II, a wheeled robot optimized for winding and complex pipelines.

Pathway Selection Mechanism of a Screw Drive In-Pipe Robot in T-Branches

Conference: IEEE International Conference on Automation Science and Engineering, 2012

Citations: 42

Highlights: Proposes mechanisms for robots to autonomously navigate pipeline branches.

Development of a Screw Drive In-Pipe Robot for Passing Through Bent and Branch Pipes

Conference: IEEE ISR, 2013

Citations: 41

Highlights: Focuses on screw drive robots overcoming pipeline bends and branches.

Underactuated Modular Finger with Pull-In Mechanism for a Robotic Gripper

Conference: IEEE Robotics and Biomimetics, 2016

Citations: 40

Highlights: Introduces a robotic gripper using an underactuated mechanism for enhanced grasping.

Stiffness Design of a Resonance-Based Planar Snake Robot with Parallel Elastic Actuators

Journal: IEEE Robotics and Automation Letters, 2018

Citations: 39

Highlights: Examines stiffness optimization for snake robots in planar environments.

Conclusion

Dr. Atsushi Kakogawa is a highly accomplished researcher whose contributions to robotics and mechatronics make him a strong contender for the Best Researcher Award. His academic rigor, leadership in the robotics community, and innovation in mobile and embedded systems distinguish him as a trailblazer in his field. By addressing areas such as industrial collaboration and broader global recognition, he could solidify his position as a preeminent figure in robotics research.

Atsushi Kakogawa | Robotics and Mechatronics | Best Researcher Award Ritsumeikan University

Assoc. Prof. Dr Atsushi Kakogawa |  Robotics and Mechatronics | Best Researcher Award

Associate Professor at Ritsumeikan University, Japan

🌟 Atsushi Kakogawa, Ph.D., is an Associate Professor in Robotics at Ritsumeikan University, Japan. A pioneer in robotics, he excels in mobile robot design, mechanical systems, and embedded systems. Proficient in programming languages like C++, Python, and more, Dr. Kakogawa has a prolific career marked by teaching, research, and leadership in international robotics conferences.

Profile

scholar

Education🎓 

Doctor of Engineering, Ritsumeikan University, Japan, 2015.  Master of Engineering, Ritsumeikan University, Japan, 2012.  Bachelor of Engineering, Department of Robotics, Ritsumeikan University, Japan, 2010.

Experience💼

Associate Professor, Ritsumeikan University (2023–Present).  Lecturer and Visiting Assistant Professor at University of Waterloo (2017). Assistant Professor, Ritsumeikan University (2015–2019).

Awards and Honors🏆

KAKENHI Grants from Japan Society for the Promotion of Science. Shiga Prefecture Technology Promotion Subsidy (2022). Organizer and Editor roles in top IEEE conferences, including IROS and ICRA.

Research Focus🤖

Robotics: Mobile robot design and mechanical system applications.  Embedded systems and advanced Internet communication technologies.  Multidisciplinary programming in C++, Python, and SQL for robotics innovation.

Publication  Top Notes

Design of a Multilink-Articulated Wheeled Pipeline Inspection Robot Using Only Passive Elastic Joints

Journal: Advanced Robotics, 2018

Citations: 73

Highlights: Introduces a pipeline robot leveraging passive elastic joints for adaptability in complex pipeline systems.

Mobility of an In-Pipe Robot with Screw Drive Mechanism Inside Curved Pipes

Conference: IEEE International Conference on Robotics and Biomimetics, 2010

Citations: 72

Highlights: Explores screw drive mechanisms for pipeline robots navigating curved environments.

Stiffness Design of Springs for a Screw Drive In-Pipe Robot to Pass Through Curved and Vertical Pipes

Journal: Advanced Robotics, 2012

Citations: 55

Highlights: Focuses on optimizing spring stiffness to enhance robot mobility in diverse pipe geometries.

Designing Arm Length of a Screw Drive In-Pipe Robot for Climbing Vertically Positioned Bent Pipes

Journal: Robotica, 2016

Citations: 50

Highlights: Discusses arm length designs crucial for overcoming vertical bends in pipelines.

An In-Pipe Robot with Underactuated Parallelogram Crawler Modules

Conference: IEEE International Conference on Robotics and Automation, 2014

Citations: 48

Highlights: Presents a robot with a novel crawler module enhancing adaptability and efficiency.

Design of a Multilink-Articulated Wheeled Inspection Robot for Winding Pipelines: AIRo-II

Conference: IEEE/RSJ Intelligent Robots and Systems, 2016

Citations: 46

Highlights: Develops AIRo-II, a wheeled robot optimized for winding and complex pipelines.

Pathway Selection Mechanism of a Screw Drive In-Pipe Robot in T-Branches

Conference: IEEE International Conference on Automation Science and Engineering, 2012

Citations: 42

Highlights: Proposes mechanisms for robots to autonomously navigate pipeline branches.

Development of a Screw Drive In-Pipe Robot for Passing Through Bent and Branch Pipes

Conference: IEEE ISR, 2013

Citations: 41

Highlights: Focuses on screw drive robots overcoming pipeline bends and branches.

Underactuated Modular Finger with Pull-In Mechanism for a Robotic Gripper

Conference: IEEE Robotics and Biomimetics, 2016

Citations: 40

Highlights: Introduces a robotic gripper using an underactuated mechanism for enhanced grasping.

Stiffness Design of a Resonance-Based Planar Snake Robot with Parallel Elastic Actuators

Journal: IEEE Robotics and Automation Letters, 2018

Citations: 39

Highlights: Examines stiffness optimization for snake robots in planar environments.

Conclusion

Dr. Atsushi Kakogawa is a highly accomplished researcher whose contributions to robotics and mechatronics make him a strong contender for the Best Researcher Award. His academic rigor, leadership in the robotics community, and innovation in mobile and embedded systems distinguish him as a trailblazer in his field. By addressing areas such as industrial collaboration and broader global recognition, he could solidify his position as a preeminent figure in robotics research.

Hugo Bildstein | Sensor-based Control | Best Researcher Award

Dr. Hugo Bildstein | Sensor-based Control | Best Researcher Award

Dr. LAAS-CNRS, France

Hugo Bildstein is a PhD candidate and Temporary Teaching and Research Assistant at the University of Toulouse 3 – Paul Sabatier, affiliated with the RAP team at LAAS-CNRS. His academic background includes a Master’s degree in Robotics from Toulouse and a previous engineering degree in Mechatronics from ENS Rennes. Hugo’s research focuses on visual predictive control for mobile manipulators, with notable publications in leading journals and conferences, including Robotics and Autonomous Systems (RAS) and IEEE/ASME AIM. His work explores strategies for improving visibility, manipulability, and stability in robotic systems.

Professional Profiles:

scopus

Academic Background 🎓:

Hugo Bildstein is currently a Temporary Teaching and Research Assistant at the University of Toulouse 3 – Paul Sabatier, working within the RAP team at LAAS-CNRS, Toulouse. His academic journey includes a PhD at the same university from 2020-2024, following a Master’s degree in Robotics: Decision and Control (RODECO) at the University of Toulouse 3 – Paul Sabatier. Hugo also holds a Master’s degree in Mechatronics from ENS Rennes and ranked 11th in the Agrégation in Industrial Engineering Sciences, Electrical Engineering option in 2019.

Research Activities and  📚:

Hugo’s research focuses on enhancing visual predictive control for mobile manipulators. His work includes:“Visual Predictive Control for Mobile Manipulators: Visibility, Manipulability, and Stability” – to be published in Robotics and Autonomous Systems (RAS) in 2024.“Enhanced Visual Predictive Control Scheme for Mobile Manipulators” – presented at the 2023 European Conference on Mobile Robots (ECMR) in Coimbra, Portugal.“Multi-camera Visual Predictive Control Strategy for Mobile Manipulators” – showcased at the 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) in Seattle, USA.“Visual Predictive Control Strategy for Mobile Manipulators” – discussed at the 2022 European Control Conference (ECC) in London, United Kingdom.

Research Analysis for Hugo Bildstein

Strengths for the Award:

  1. Innovative Contributions: Hugo Bildstein’s research focuses on cutting-edge topics in robotics, particularly visual predictive control for mobile manipulators. His work on enhancing control schemes through multi-camera strategies and visual feedback systems is highly relevant and forward-thinking in the field of robotics and autonomous systems.
  2. Diverse Research Outputs: Bildstein has published several papers in prestigious journals and conferences, demonstrating a consistent and impactful research output. His papers, such as those presented at the European Conference on Mobile Robots (ECMR) and the IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), highlight significant contributions to the field.
  3. Academic Excellence: His strong academic background, including a PhD in Robotics and a Master’s degree in Robotics and Control, coupled with high rankings in competitive exams like the Agrégation in Industrial Engineering Sciences, underscores his deep expertise and commitment to the field.
  4. Teaching and Research Experience: As a Teaching and Research Assistant at the University of Toulouse 3 – Paul Sabatier, Bildstein not only engages in advanced research but also contributes to academic teaching, showcasing his ability to bridge research and education effectively.

Areas for Improvement:

  1. Citation Impact: While Bildstein has several publications, some of his recent papers have yet to accumulate significant citations. Increasing the visibility and impact of his work through broader dissemination and collaboration could enhance his academic profile.
  2. Interdisciplinary Applications: Expanding research to explore interdisciplinary applications of his work could provide broader impact and open new avenues for practical implementation of his findings.
  3. Research Collaboration: Engaging in collaborative research with industry partners or other academic institutions could provide additional resources and perspectives, potentially leading to more comprehensive studies and real-world applications.

Conclusion:

Hugo Bildstein is a promising candidate for the Best Researcher Award due to his innovative contributions to the field of robotics, particularly in visual predictive control for mobile manipulators. His strong academic background, diverse research outputs, and active role in teaching and research highlight his potential and dedication. Addressing areas such as citation impact and interdisciplinary applications could further enhance his standing in the research community.

✍️Publications Top Note :

1. Enhanced Visual Predictive Control Scheme for Mobile Manipulators

Authors: Hugo Bildstein, A. Durand-Petiteville, V. Cadenat

Citations: 0

2. Multi-camera Visual Predictive Control Strategy for Mobile Manipulators

Authors: Hugo Bildstein, A. Durand-Petiteville, V. Cadenat

3. Visual Predictive Control Strategy for Mobile Manipulators

Authors: Hugo Bildstein, A. Durand-Petiteville
Citations: 2
Access: Open access

Prof Philip F. Yuan | Robotic Fabrication | Best Researcher Award

Prof Philip F. Yuan | Robotic Fabrication | Best Researcher Award

Prof Philip F. Yuan , CAUP, Tongji University, China

Prof Philip F. Yuan is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

 

Professional Profiles:

Scopus

Yuan, Philip F.

Info:

Tongji University, Shanghai, China
56057067100

📖 Publications Top Note :

Agent-Based Principal Strips Modeling for Freeform Surfaces in Architecture
Chai, H., Orozco, L., Kannenberg, F., Menges, A., Yuan, P.F.
Nexus Network Journal, 2024, 26(2), pp. 369–396
Explores innovative modeling techniques in architecture utilizing agent-based methods.

Bioinspired Sensors and Applications in Intelligent Robots: A Review
Zhou, Y., Yan, Z., Yang, Y., Yuan, P.F., He, B.
Robotic Intelligence and Automation, 2024, 44(2), pp. 215–228
A comprehensive review of bioinspired sensor technologies and their applications in robotics.

FloatArch: A Cable-Supported, Unreinforced, and Re-Assemblable 3D-Printed Concrete Structure Designed Using Multi-Material Topology Optimization
Li, Y., Wu, H., Xie, X., Yuan, P.F., Xie, Y.M.
Additive Manufacturing, 2024, 81, 104012
Presents a pioneering design in 3D-printed concrete structures optimized for reusability and sustainability.

Structural Performance-Based 3D Concrete Printing for an Efficient Concrete Beam
Wu, H., Li, Y., Xie, X., Gao, X., Yuan, P.F.
Sustainable Development Goals Series, 2024, Part F2790, pp. 343–354
Discusses advancements in 3D printing for creating efficient concrete beams.

Research on 3D Printing Craft for Flexible Mass Customization: The Case of Chengdu Agricultural Expo Center
Gao, T., Gu, S., Zhang, L., Yuan, P.F.
Sustainable Development Goals Series, 2024, Part F2790, pp. 465–480
Examines flexible customization in 3D printing through a case study of an agricultural expo center.

Preface
Yan, C., Chai, H., Sun, T., Yuan, P.F.
Computational Design and Robotic Fabrication, 2024, Part F2072
Introduction to the latest volume focusing on computational design and robotic fabrication.

The Use of Normative Energy Calculation for Natural Ventilation Performance-Driven Urban Block Morphology Generation
Li, W., Xu, X., Makvandi, M., Sun, Z., Yuan, P.F.
Computational Design and Robotic Fabrication, 2024, Part F2072, pp. 315–328
Investigates energy-efficient urban design through computational methods.

A Parametric Approach Towards Carbon Net Zero in Agricultural Planning
Yueyang, W., Yuan, P.F.
Computational Design and Robotic Fabrication, 2024, Part F2072, pp. 305–314
Focuses on achieving carbon neutrality in agricultural planning using parametric design techniques.

ISOMORPHISM: Stylized Translations of 2D Prototype in Additive Clay Printing
Gong, L., Yuan, P.F.
Computational Design and Robotic Fabrication, 2024, Part F2072, pp. 515–525
Explores the translation of 2D designs into 3D printed clay structures.

Practical Application of Multi-Material Topology Optimization to Performance-Based Architectural Design of an Iconic Building
Li, Y., Ding, J., Zhang, Z., Yuan, P.F., Xie, Y.M.
Composite Structures, 2023, 325, 117603
Applies multi-material optimization in creating high-performance architectural designs.