Dr. Chengjun Zeng | Polymer composites | Best Researcher Award

Assoc. Prof. Dr. Chengjun Zeng , Harbin Institute of Technology , China.

Dr. Chengjun Zeng is an Associate Professor at Harbin Institute of Technology, specializing in shape memory polymer composites, 4D printing, and mechanical metamaterials. He earned his Ph.D. in Mechanics from Harbin Institute of Technology (2022) and a Bachelor’s in Naval Architecture and Ocean Engineering from Harbin Engineering University (2017). Previously, he served as an Assistant Professor and Postdoctoral researcher under Prof. Jinsong Leng. Dr. Zeng has published impactful research in Advanced Functional Materials, International Journal of Plasticity, and Composites Science and Technology. His work pushes boundaries in composite mechanics and programmable materials.

Publication Profile

Scopus

Orcid

Google Scholar

Education & Experience

Education

Ph.D. in Mechanics – Harbin Institute of Technology (2017-2022)
B.Sc. in Naval Architecture and Ocean Engineering – Harbin Engineering University (2013-2017)

Experience

Associate Professor & Master’s Supervisor – Harbin Institute of Technology (2025-Present)
Assistant Professor & Master’s Supervisor – Harbin Institute of Technology (2023-2025)
Postdoctoral Researcher (Co-supervised by Prof. Jinsong Leng) – Harbin Institute of Technology (2023-2025)

Suitability Summary

Dr. Chengjun Zeng, Associate Professor at Harbin Institute of Technology, is a leading expert in shape memory polymer composites, 4D printing, mechanical metamaterials, and composite mechanics. His outstanding research contributions, high-impact publications, and pioneering advancements in smart materials position him as a deserving recipient of the Best Researcher Award.

Professional Development

Dr. Chengjun Zeng is a rising expert in advanced materials science and mechanical engineering, with significant contributions to 4D printing, smart composites, and mechanical metamaterials. His research integrates viscoelasticity, anisotropic behaviors, and phase transitions, driving innovations in programmable structures and bio-inspired designs. His publications in top-tier journals reflect his dedication to high-impact research. As a Master’s supervisor, he mentors students in cutting-edge polymer mechanics. His collaborations with leading scholars and institutions further solidify his role in transforming next-gen material science.

Research Focus

Dr. Chengjun Zeng’s research revolves around advanced polymer composites, focusing on shape memory effects, smart materials, and bio-inspired mechanics. His work explores programmable deformation, high-stretchability structures, and sustainable composite applications. Leveraging 4D printing, he pioneers reconfigurable materials for aerospace, biomedical, and mechanical applications. His models integrate finite deformation mechanics, viscoelasticity, and phase transitions, bridging theoretical advancements with real-world implementations. His contributions are shaping the future of adaptive materials, mechanical metamaterials, and intelligent composite structures, making strides toward functional and responsive engineering solutions.

Awards & Honors

Published in Top-Tier SCI Journals – Advanced Functional Materials, International Journal of Plasticity, Composites Science and Technology
Ph.D. Advisor & Research Mentor – Supervising graduate students in cutting-edge polymer mechanics
High-Impact Publications – Featured in journals with Impact Factors 18.5, 9.4, and 8.3
Recognized for Innovations in 4D Printing & Composite Mechanics

Publication Top Notes

Construction of Mechanical Metamaterials and Their Extraordinary Functions – Composite Structures, 2025-02, DOI: 10.1016/j.compstruct.2025.118872

4D Printed Mortise-Tenon Mechanical-Electromagnetic Multifunctional Pixel Metamaterials – Chemical Engineering Journal, 2025-01, DOI: 10.1016/j.cej.2024.158784

Bamboo-Inspired 3D Printed Continuous Fiber-Reinforced Vascular Composites – Composites Communications, 2025-01, DOI: 10.1016/j.coco.2024.102219

Mechanical Properties of Diamond-Type Triply Periodic Minimal Surface Structures Fabricated by Photo-Curing 3D Printing – Composite Structures, 2025-01, DOI: 10.1016/j.compstruct.2024.118695

Theoretical Model Combined Finite Element Approach for Studying Mechanical Behavior of Shape Memory Hydrogel Ribbed Sheet with Stretch-Triggered Bend Effect – Composite Structures, 2025-01, DOI: 10.1016/j.compstruct.2024.118783

Conclusion

Dr. Chengjun Zeng’s groundbreaking work and transformative contributions tosmart materials and mechanical metamaterials make him an ideal candidate for the Best Researcher Award. His research not only advances fundamental knowledge but also drives real-world applications in aerospace, robotics, and biomedical engineering, solidifying his global impact in material science and engineering.

Rashik Shahriar Akash | Composite Modeling | Best Researcher Award

Mr. Rashik Shahriar Akash, Health Informatics Research Lab, Bangladesh.

Rashik Shahriar Akash is a motivated Computer Science student from Dhaka, Bangladesh, specializing in Artificial Intelligence (AI) and Machine Learning (ML). He currently serves as a Research Assistant at the Health Informatics Research Lab, focusing on Computer Vision, particularly in medical imaging. With a strong academic background and a passion for technology, Rashik is committed to developing cutting-edge AI solutions for real-world problems. He has contributed to multiple high-impact research papers in the fields of medical imaging, deep learning, and AI. Outside of academics, Rashik is actively involved in extracurricular activities and mentoring fellow students.

Experience

Research Assistant, Computer Vision, Health Informatics Research Lab, Dhaka (Jul 2024 – Present) 🧑‍💻

Research Assistant, Computer Vision, Apurba-DIU Research and Development LAB, Dhaka (Apr 2023 – Jun 2024)

Trainer, Advance Machine Learning and Deep Learning Bootcamp, DIU NLP & ML Research Lab, Dhaka (May 2023 – Dec 2023)

Lab Prefect, Computer Science and Engineering, Daffodil International University (May 2022 – Dec 2022)

Suitability For The Award

Mr. Rashik Shahriar Akash is an exceptional candidate for the Best Researcher Award based on his strong academic background, extensive research experience, and demonstrated commitment to advancing the field of Artificial Intelligence (AI) and Machine Learning (ML). As a research assistant in the fields of Computer Vision and Health Informatics, he has contributed significantly to cutting-edge research projects, particularly in medical imaging and disease prediction.

Professional Development

Rashik Shahriar Akash has actively pursued opportunities for professional development throughout his academic journey. As a Trainer for the Advance Machine Learning and Deep Learning Bootcamp, he mentored students and enhanced his skills in machine learning frameworks such as TensorFlow and PyTorch. He has also collaborated on several cutting-edge research projects, published impactful papers, and has a strong focus on AI and computer vision in healthcare. His passion for learning and teaching has enabled him to refine his skills in AI and machine learning, particularly in medical applications.

Research Focus

Rashik’s research primarily focuses on the application of Artificial Intelligence and Machine Learning in the fields of medical imaging and computer vision. He has worked on innovative AI models, such as deep learning algorithms for medical diagnoses, including brain tumor detection and breast cancer prediction. His other areas of interest include computer vision-based solutions for polyp segmentation, cervical cell abnormalities, and taxonomic classification using DNA analysis. Through his work, Rashik aims to enhance the efficiency and accuracy of AI applications in healthcare, contributing to meaningful advancements in the field.

Awards and Honors

Level 2 (FE) passer of Information Technology Engineers Examination 2023
Performance-based scholarship at Daffodil International University (2020–2024)
Government scholarship in Junior School Certificate Examination 2013
Government scholarship for High School Entrance

Publications

A Comprehensive Review on Family Budget Management (2023) – International Conference on Intelligent Computing & Optimization, 379-391 (Cited by 1)
SAMU-Net: A Dual-Stage Polyp Segmentation Network with a custom attention-based U-Net and Segment anything Model for Enhanced Mask Prediction (2024) – Array, 100370 (Cited by 0)
CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities (2024) – Digital Health, 10, 20552076241295440 (Cited by 0)
A Review on the Impacts of Social Media on the Mental Health (2023) – International Conference on Intelligent Computing & Optimization, 181-195 (Cited by 0)