Shihao Zhang | Nanostructures | Best Researcher Award

Published on by Physicist Particle

Dr. Shihao Zhang | Nanostructures | Best Researcher Award

Specially Appointed Assistant Professor at Osaka University, Japan.

🎓 Dr. Shihao Zhang (born August 1993) is a Specially Appointed Assistant Professor at Osaka University, Japan, specializing in computational materials science. His research spans materials theory, mechanical properties, crystal defects, nanostructures, and machine learning applications. He earned his Ph.D. in Materials Science from Beihang University and has held prestigious research positions, including a JSPS Postdoctoral Fellowship. Dr. Zhang has contributed significantly to high-throughput materials simulations, publishing 34+ papers in leading journals like npj Computational Materials and Acta Materialia, accumulating 750+ citations (H-index: 13).

Professional Profile:

Scopus Profile

Suitability for Best Researcher Award – Dr. Shihao Zhang

Dr. Shihao Zhang stands out as a strong candidate for the Best Researcher Award due to his remarkable contributions to computational materials science. His expertise in materials theory, nanostructures, and machine learning-driven materials design has significantly advanced the field. His research has led to high-throughput materials simulations, fundamental discoveries in mechanical properties, and the development of innovative software tools.

Education & Experience

📚 Education:

  • 🎓 Ph.D. in Materials Science – Beihang University, 2021
  • 📊 B.S. in Materials Science & Engineering & Applied Mathematics – Dual degrees

🧑‍🏫 Experience:

  • 🔬 Specially Appointed Assistant Professor – Osaka University, Japan
  • 🏅 JSPS Postdoctoral Fellow – Osaka University
  • 💻 Researcher – IT4Innovations, Czech National Supercomputing Centre

Professional Development

🧪 Dr. Shihao Zhang has made significant contributions to computational materials science through advanced modeling, high-throughput simulations, and machine learning techniques. He has developed innovative software tools to enhance material design and prediction capabilities. 📈 His work bridges fundamental materials theory with practical applications, focusing on mechanical properties, plasticity, and nanostructures. 🔗 His research collaborations span multiple international institutions, fostering advancements in computational techniques and supercomputing applications. 🏆 With 34+ publications in prestigious journals and an H-index of 13, Dr. Zhang continues to drive impactful discoveries in materials science.

Research Focus

🛠️ Dr. Zhang’s research lies at the intersection of materials theory, mechanical properties, crystal defects, plasticity, nanostructures, and computational modeling. His expertise in machine learning-driven materials design enables the development of advanced materials with superior mechanical performance. 💡 His work utilizes high-throughput computational methods to predict material behavior at the atomic and nanoscale levels. 🔬 By integrating data-driven approaches with physics-based simulations, he enhances material discovery and optimization. 🌍 His research is essential for innovations in aerospace, electronics, and structural materials, pushing the boundaries of next-generation materials engineering.

Awards & Honors

🏅 JSPS Postdoctoral Fellowship – Japan Society for the Promotion of Science
📜 Multiple Research Grants – Supporting computational materials research
📖 34+ High-Impact Publications – npj Computational Materials, Acta Materialia, Physical Review B
📊 750+ Citations (H-index: 13) – Recognized research contributions
💡 Developed Software Tools – For high-throughput materials simulations
🌍 International Research Collaborations – Osaka University, IT4Innovations, and more

Publication Top Notes

  • Title: Temperature and loading-rate dependent critical stress intensity factor of dislocation nucleation from crack tip: Atomistic insights into cracking at slant twin boundaries in nano-twinned TiAl alloys

    • Authors: R. Fu, Rong; Z. Rui, Zhiyuan; J. Du, Junping; F. Meng, Fanshun; S. Ogata, Shigenobu
    • Year: 2025

  • Title: A dislocation perspective on heterointerfacial strengthening in nanostructured diamond and cubic boron nitride composites

    • Authors: H. Wei, Hanqing; H. Zhan, Haifei; D. Legut, Dominik; S. Zhang, Shihao
    • Year: 2025

  • Title: Dislocation plasticity in c-axis nanopillar compression of wurtzite ceramics: A study using neural network potentials

    • Authors: S. Zhang, Shihao; S. Ogata, Shigenobu
    • Year: 2025

Shahid Akbar | Computer Science | Best Researcher Award

Published on by Physicist Particle

Dr. Shahid Akbar | Computer Science | Best Researcher Award

Orcid Profile 

Scopus Profile

Educational Details

Postdoctoral Fellow
IFFS, University of Electronic Science and Technology of China
June 2023 – Present

Ph.D. in Computer Science
Abdul Wali Khan University Mardan, Pakistan
2017 – 2021
Dissertation Title: An Intelligent Computational Model for Identification of Anticancer Peptides

M.S. in Computer Science
Abdul Wali Khan University Mardan, Pakistan
2012 – 2016

Bachelor’s in Computer and Information Technology
Islamic University of Technology, Dhaka, Bangladesh
2008 – 2011

Professional Experience

Dr. Shahid Akbar currently serves as a Postdoctoral Fellow at the IFFS, University of Electronic Science and Technology of China, where he is engaged in advanced research in bioinformatics and artificial intelligence. Prior to this, he was a Lecturer in the Department of Computer Science at Abdul Wali Khan University Mardan, Pakistan, from August 2015 to June 2023, where he taught various undergraduate courses and contributed to the academic development of students in the field. Before that, he held a similar position at the Government College of Management Sciences in Swabi, Pakistan, from January 2012 to August 2015, where he began his academic career. Through these roles, Dr. Akbar has built a solid foundation in teaching and research, fostering a strong interest in the application of computational methods to solve complex scientific problems.

Research Interest

Dr. Shahid Akbar’s research interests lie at the intersection of bioinformatics and artificial intelligence. He specializes in machine learning, deep learning, pattern recognition, and neural networks, with a particular focus on developing intelligent computational models for identifying anticancer peptides.

Technical Skills

Dr. Akbar is proficient in various programming languages and tools, including Python, Keras, TensorFlow, SQL Server, R, MATLAB, Spark, and Hadoop. His expertise extends to data warehousing and advanced Java programming.

Awards and Distinctions

OIC Scholarship (3 years)

AWKUM Talented PhD Students Scholarship

Courses Taught

Dr. Akbar has taught a range of undergraduate courses, including:

Machine Learning

Data Structures and Algorithms

Introduction to Programming

Pattern Recognition

Object-Oriented Programming

Data Mining and Warehousing

Artificial Intelligence

Junior Project/Graduate Project

Top Notable Publications

Hybrid Residue Based Sequential Encoding Mechanism with XGBoost Improved Ensemble Model for Identifying 5-Hydroxymethylcytosine Modifications

Authors: Uddin, I., Awan, H.H., Khalid, M., Abdolrasol, M.G.M., Alghamdi, T.A.H.

Journal: Scientific Reports

Year: 2024

Volume: 14

Issue: 1

Article Number: 20819

Citations: 0

StackedEnC-AOP: Prediction of Antioxidant Proteins Using Transform Evolutionary and Sequential Features Based Multi-Scale Vector with Stacked Ensemble Learning

Authors: Rukh, G., Akbar, S., Rehman, G., Alarfaj, F.K., Zou, Q.

Journal: BMC Bioinformatics

Year: 2024

Volume: 25

Issue: 1

Article Number: 256

Citations: 0

Deepstacked-AVPs: Predicting Antiviral Peptides Using Tri-Segment Evolutionary Profile and Word Embedding Based Multi-Perspective Features with Deep Stacking Model

Authors: Akbar, S., Raza, A., Zou, Q.

Journal: BMC Bioinformatics

Year: 2024

Volume: 25

Issue: 1

Article Number: 102

Citations: 17

AIPs-DeepEnC-GA: Predicting Anti-Inflammatory Peptides Using Embedded Evolutionary and Sequential Feature Integration with Genetic Algorithm Based Deep Ensemble Model

Authors: Raza, A., Uddin, J., Zou, Q., Alghamdi, W., Liu, R.

Journal: Chemometrics and Intelligent Laboratory Systems

Year: 2024

Volume: 254

Article Number: 105239

Citations: 0

Comprehensive Analysis of Computational Methods for Predicting Anti-Inflammatory Peptides

Authors: Raza, A., Uddin, J., Akbar, S., Zou, Q., Ahmad, A.

Journal: Archives of Computational Methods in Engineering

Year: 2024

Volume: 31

Issue: 6

Pages: 3211–3229

Citations: 3

DeepAVP-TPPred: Identification of Antiviral Peptides Using Transformed Image-Based Localized Descriptors and Binary Tree Growth Algorithm

Authors: Ullah, M., Akbar, S., Raza, A., Zou, Q.

Journal: Bioinformatics

Year: 2024

Volume: 40

Issue: 5

Article Number: btae305

Citations: 9

iAFPs-Mv-BiTCN: Predicting Antifungal Peptides Using Self-Attention Transformer Embedding and Transform Evolutionary Based Multi-View Features with Bidirectional Temporal Convolutional Networks

Authors: Akbar, S., Zou, Q., Raza, A., Alarfaj, F.K.

Journal: Artificial Intelligence in Medicine

Year: 2024

Volume: 151

Article Number: 102860

Citations: 18

Blockchain-Based Logging to Defeat Malicious Insiders: The Case of Remote Health Monitoring Systems

Authors: Javed, H., Abaid, Z., Akbar, S., Alkahtani, H.K., Raza, A.

Journal: IEEE Access

Year: 2024

Volume: 12

Pages: 12062–12079

Citations: 2

Conclusion

In summary, Dr. Shahid Akbar’s diverse research interests, significant contributions to bioinformatics, robust technical skills, extensive educational background, and active participation in academia and professional development make him an exceptional candidate for the Best Researcher Award. His work not only advances the field of computer science but also contributes to addressing critical challenges in healthcare, particularly in cancer research.