Assoc. Prof. Dr. Alireza Zirak | Robotics & Automation | Best Researcher Award

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Assoc. Prof. Dr. Alireza Zirak | Robotics & Automation | Best Researcher Award

Assoc. Prof. Dr. Alireza Zirak | Nuclear Science and Technology Research Institute | Iran

Prof. Alireza Zirak is an Associate Professor at the Laser and Optics Research School, specializing in electronics, telecommunications, and advanced photonics. His research focuses on tomography and radiotherapy systems, quantum technology, digital signal and image processing, laser applications, IoT, embedded systems, and stochastic modeling. He has received multiple national honors, including top rankings in Iran’s University Entrance Examination and Mathematics Olympiad, the National Science Festival design prize, and recognition at the National Engineer’s Day festival. Prof. Zirak has also contributed as a scientific committee member for major conferences and received acknowledgments from institutions such as the Vice Presidency for Science and Technology. With expertise in optimization, microcontroller programming, and photonics system design, he has played a significant role in advancing interdisciplinary applications of electronics and optics. His academic influence is reflected in 174 citations from 139 documents, 20 publications, and an h-index of 8, demonstrating both his productivity and impact in modern engineering and photonics research.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Nankali, S., Worm, E. S., Weber, B., Høyer, M., Zirak, A., Poulsen, P. R. (2018). Geometric and dosimetric comparison of four intrafraction motion adaptation strategies for stereotactic liver radiotherapy. Physics in Medicine & Biology, 63(14), 145010.

  • Khezerloo, D., Nedaie, H. A., Zirak, A., Farhood, B., Banaee, N., Alidokht, E. (2018). Dosimetric properties of new formulation of PRESAGE® with tin organometal catalyst: Development of sensitivity and stability to megavoltage energy. Journal of Cancer Research and Therapeutics, 14(2), 308–315.

  • Rajabi, H., & Zirak, A. (2016). Speckle noise reduction and motion artifact correction based on modified statistical parameters estimation in OCT images. Biomedical Physics & Engineering Express, 2(3), 035012.

  • Zirak, A. R., & Khademi, M. (2007). An efficient method for model refinement in diffuse optical tomography. Optics Communications, 279(2), 273–284.

  • Zirak, A. R., & Roshani, S. (2016). A reduced switch voltage stress class E power amplifier using harmonic control networks. International Journal of Advanced Computer Science and Applications, 7, 38–42.

Mr. Haochen Wang | Robotics | Best Researcher Award

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Mr. Haochen Wang | Robotics | Best Researcher Award

Mr. Haochen Wang , Shandong University , China.

Mr. Wang Haochen 🎓, is a Ph.D. candidate in Computer Science and Technology at Shandong University 🏫. With a strong foundation in Artificial Intelligence 🤖, he has led and contributed to numerous cutting-edge projects in reinforcement learning, robotic vision, and intelligent control systems 🤝. His research has been applied to real-world systems such as badminton robots 🏸, fascia removal machines 🥩, and defect detection in manufacturing 🏭. Wang has published multiple academic papers 📄 and co-authored a national patent 📑. Passionate about AI-driven innovation, he is proficient in Python, C++, PyTorch, and reinforcement learning frameworks 💻.

Professional Profile

Scopus
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Education & Experience 

📘 Education

  • 🎓 2018.09–2022.06: B.Sc. in Artificial Intelligence, Shandong University

  • 🎓 2022.09–Present: Direct Ph.D. in Computer Science & Technology, Shandong University

🔧 Project Experience

  • 🏸 ICRA 2025: Physical Knowledge-Aided Reinforcement Learning for Badminton Robots

  • 🦾 2024: Transformer-based Sequential Decision Models for Robotic Grasping

  • 🥩 2022–2023: 3D Vision & Path Planning for Fascia Removal Robot

  • 🧠 2022: Defect Detection with Attention Mechanisms (ICCPS 2023)

  • 🎥 2020: Multifunctional Dance & Social App “Qingying” – National Competition Winner

🧑‍💼 Internship

  • 🤖 2022: DeepCool Robotics – Defect Detection Algorithm Development

Summary Suitability

Mr. Wang Haochen, a direct Ph.D. candidate in Computer Science and Technology at Shandong University, is a highly qualified nominee for the 🏆 Best Researcher Award. His research trajectory showcases exceptional dedication to integrating cutting-edge artificial intelligence with real-world robotic systems, demonstrating both academic excellence and practical impact. His interdisciplinary contributions span reinforcement learning, computer vision, robotics, and healthcare AI—making him a strong contender for this prestigious recognition.

Professional Development 

Mr. Wang Haochen has developed professionally through diverse hands-on experiences in academia and industry 🔬. From building AI-driven decision-making systems 🤖 to deploying real-world robotics solutions 🦿, he has cultivated a deep understanding of reinforcement learning, computer vision, and human-robot interaction 🤝. His work spans both innovative research and applied technology, demonstrated by successful collaboration with companies and high-impact publications 📚. He is fluent in major programming languages 💻 and adept in PyTorch, TensorFlow, and multiple RL toolkits ⚙️. His capability to bridge theory and practice makes him a promising researcher and developer in intelligent systems 🌐.

Research Focus 

Mr. Wang Haochen’s research focuses on reinforcement learning (RL) 🔁, robotics 🤖, and AI-driven automation ⚙️. He explores the intersection of physical modeling and machine learning to enhance decision-making in real-world environments 🌍. His contributions include hybrid learning systems, offline RL with physics-based priors, and Transformer-based policies for robot control 🧠. With projects ranging from robotic grasping 🤲 to intelligent defect detection 🏭, his work aims to make robotic systems smarter, more adaptive, and deployable in practical settings. His integration of AI algorithms with physical systems bridges the gap between simulation and deployment 🚀.

Awards & Honors

🏆 14th National College Software Innovation Competition

  • 🥇 National First Prize

  • 💡 Most Entrepreneurial Potential Award

📄 Academic Recognition

  • 📘 First Author – ICRA 2025 & ICCPS 2025

  • 📗 Fourth Author – Information Fusion Publication

  • 📝 National Invention Patent – Second Author

Publication Top Notes

  • Title: Integrating Learning-Based Manipulation and Physics-Based Locomotion for Whole-Body Badminton Robot Control
    Authors: Wang Haochen, et al.
    Conference: IEEE International Conference on Robotics and Automation (ICRA), 2025
    Status: Accepted (In Press)

  • Title: Autonomous and Cost-effective Defect Detection System for Molded Pulp Products
    Authors: Wang Haochen, et al.
    Conference: ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2025
    DOI: [To be updated if available]
    Status: Published

  • Title: MV-BMR: Motion and Vision Sensing Integration Based Agile Badminton Robot
    Authors: [First three authors], Wang Haochen
    Journal: Information Fusion
    Status: Published
    DOI: [To be provided]

  • Title: The association of pain phenotype and providing caregiving with depressive symptom trajectory for older adults: a longitudinal analysis using the health and retirement study
    Authors: [Not provided]
    Journal/Conference: [Not specified]
    Note: This appears unrelated to robotics/AI. If Wang Haochen is an author, clarify authorship and publication source.

Conclusion

Mr. Wang Haochen’s innovative work across academic research, real-world robotics deployment, and industrial application makes him a compelling recipient of the Best Researcher Award. His ability to transform complex AI algorithms into deployable systems has resulted in impactful contributions to sports robotics, intelligent manufacturing, and healthcare analytics. With a blend of deep technical skills, research leadership, and cross-sector collaboration, he stands out as a rising star in intelligent systems. He not only meets the criteria for this honor—but redefines them.