Bo Yao | Neuromorphic Devices | Best Researcher Award

Prof. Bo Yao | Neuromorphic Devices | Best Researcher Award

Deputy Director at Shaoxing University | China

Prof. Bo Yao is an Associate Professor at Shaoxing University, China, specializing in semiconductor devices and optoelectronic materials. He earned his Ph.D. from Lanzhou University, focusing on semiconductor physics and advanced electronic devices. His research explores III-V-based MOSFETs, flexible photodetectors, phototransistors, and organic photoelectric functional films. Prof. Yao has published over 21 papers in prestigious SCI and EI indexed journals, including Applied Physics Letters, Journal of Materials Chemistry C, and IEEE Transactions on Electron Devices. He holds 15 national invention patents, with 8 already authorized. Recognized for his contributions, he has been selected as a “Young Outstanding Talent” under the Zhejiang Province University Leading Talent Cultivation Program and a “Young Top-notch Talent” under Shaoxing City’s “Hometown of Scholars” Special Support Program.

Professional Profile

Scopus Profile

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Education

Prof. Bo Yao received his Ph.D. degree from Lanzhou University, China, specializing in semiconductor physics and electronic devices. His doctoral research laid a strong foundation in the design, preparation, and performance analysis of advanced optoelectronic and semiconductor materials, which continues to guide his academic and professional career in the field of flexible photodetectors, MOSFETs, and organic optoelectronic functional films.

Experience

Prof. Bo Yao has extensive academic and research experience in the field of optoelectronics and semiconductor devices. After completing his Ph.D. at Lanzhou University, he joined Shaoxing University, where he has been actively engaged in teaching and research. He has been serving as an Associate Professor, focusing on the study of organic photoelectric functional films, semiconductor photodetectors, and III–V-based MOSFETs. His expertise also includes the design and fabrication of flexible photodetectors and phototransistors, contributing to the advancement of next-generation optoelectronic technologies. Alongside his teaching responsibilities, he has guided students in research projects, published widely in leading journals, and secured multiple patents, demonstrating his strong academic leadership and innovative research contributions.

Research Interests

Prof. Bo Yao’s research interests lie at the intersection of advanced semiconductor devices and optoelectronic materials. His work primarily focuses on III-V-based MOSFETs, where he explores innovative design and fabrication methods to enhance device performance for next-generation electronics. He is also engaged in the development of flexible photodetectors and phototransistors, emphasizing high sensitivity, stability, and adaptability for wearable and bendable technologies. In addition, Prof. Yao has made significant contributions to the preparation and performance optimization of organic photoelectric functional films and semiconductor photodetectors, advancing their applications in optical signal detection and optoelectronic integration. Through his research, he aims to bridge materials science with practical device engineering, contributing to the evolution of efficient, reliable, and multifunctional electronic and optoelectronic systems.

Publications

Dual-functional organic/perovskite heterojunction phototransistors enabling wide-spectrum detection and synaptic plasticity emulation

Ultra-low dark current and high sensitivity lead-free perovskite–like photodetector realized by anti-solvent optimization Cs3Bi2I9 amorphous film

High-Performance UV–Visible Broad Spectral Phototransistors Based on CuPc/Cs3Bi2I9 Heterojunction

High-Performance Flexible Near-Infrared-II Phototransistor Realized by Combining the Optimized Charge-Transfer-Complex/Organic Heterojunction Active Layer and Gold Nanoparticle Modification

Conclusion

Prof. Bo Yao is a highly suitable candidate for the Research for Best Researcher Award. His strong record of publications, patents, and funded recognition programs highlights both academic excellence and innovation. With his continued growth in international outreach and collaborative impact, he is well-positioned to emerge as a leading figure in semiconductor device research and optoelectronic technologies.

Ms. Shakila Rahman | Computer Engineering | Best Researcher Award

Ms. Shakila Rahman | Computer Engineering | Best Researcher Award

Ms. Shakila Rahman , American International University – Bangladesh (AIUB)

Shakila Rahman 🇧🇩 is a Lecturer at the Department of Computer Science, AIUB 🏫. She earned her M.Sc. in AI & Computer Engineering 🤖 from the University of Ulsan, South Korea 🇰🇷, with a CGPA of 4.00/4.50 📚. Her research spans UAV networking 🚁, wireless sensor networks 🌐, and machine learning 🧠. She actively supervises undergraduate projects 👩‍💻 and has published in reputed journals 📖. With experience in academia and applied computing, she contributes passionately to AI and emerging technologies 💡. She is also active on ResearchGate, ORCID, and LinkedIn 🌍.

Professional Profile:

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🔹 Education & Experience 

Shakila Rahman completed her M.Sc. in AI & Computer Engineering 🎓 from the University of Ulsan, South Korea 🇰🇷, and her B.Sc. in Computer Science & Engineering from IIUC 🇧🇩. Currently, she serves as a Lecturer 👩‍🏫 at American International University-Bangladesh (AIUB), where she teaches core computing subjects 💻. She previously worked as a Graduate Research Assistant in South Korea 🔬 and as an Undergraduate Teaching Assistant at IIUC 👩‍🔬. Her experience blends international research, teaching, and real-world project supervision 🌐. She is skilled in Python, Java, and C++ 🧑‍💻, and fosters student innovation through hands-on learning 🧪.

🔹 Professional Development

Shakila has enhanced her technical skillset through multiple workshops and training programs 🛠️. She completed web development 💻 at BASIS BITM, mobile game/app development 🎮 with Bangladesh ICT Division, and Android app development 🤖 with Affable Technology. As a competitive programmer, she participated in ICPC, NGPC, and UVA online judges 🏆. During her B.Sc., she joined industrial events like the Tech Summit by LEADS Corporation 👩‍💼. These initiatives equipped her with a dynamic understanding of both academic theory and industry practices 🌐. She is also an IELTS-certified English communicator with a score of 6.0 🇬🇧🗣️.

🔹 Research Focus

Shakila Rahman’s research lies at the intersection of AI and networking technologies 🤖🌐. Her main focus includes UAV Networking 🚁, Wireless Sensor Networks 🛰️, Network Systems 🖧, and Optimization Algorithms 🔁. She also works with Machine Learning 🧠, Deep Learning 🧬, Image Processing 🖼️, and AR/VR applications in AI 🥽. Her work emphasizes solving real-world challenges like obstacle detection, fire/smoke recognition 🔥🚨, and human activity classification 🚶‍♂️🚨. She publishes in SCIE and SCOPUS-indexed journals 📚, contributing to the academic community with innovations in intelligent systems and computer vision 👁️‍🗨️.

🔹 Awards & Honors 

Shakila Rahman has received prestigious academic honors 🏅, including the Brain Korea Scholarship (BK21) 💰 during her M.Sc. at the University of Ulsan 🇰🇷. She was also awarded the fully funded AF1 Scholarship worth approx. $21,000 USD 🎓💵. Her research was supported by the National Research Foundation of Korea (NRF) 🇰🇷 for multiple publications 📑. These recognitions highlight her academic excellence 🌟, research potential 🔬, and commitment to global scientific collaboration 🌍. Her accolades stand as a testament to her dedication and passion in the field of Artificial Intelligence and networked systems 🚀📡.

Publication Top Notes:

🧠 Bilingual Sign Language Recognition: A YOLOv11-Based Model for Bangla and English Alphabets

  • Journal: Journal of Imaging

  • Year: 2025

  • Citations: 0

  • Summary: This study presents a YOLOv11-based model designed for real-time recognition of Bangla and English sign language alphabets. The model aims to bridge communication gaps for the hearing-impaired by accurately detecting and classifying sign language gestures.


🏙️ Towards Safer Cities: AI-Powered Infrastructure Fault Detection Based on YOLOv11

  • Journal: Future Internet

  • Year: 2025

  • Citations: 0

  • Summary: This research introduces an AI-driven approach utilizing YOLOv11 for detecting infrastructure faults in urban environments. The model enhances city safety by enabling prompt identification and maintenance of structural issues.


🧴 A Hybrid CNN Framework DLI-Net for Acne Detection with XAI

  • Journal: Journal of Imaging

  • Year: 2025

  • Citations: 0

  • Summary: The study proposes DLI-Net, a hybrid CNN framework combining DeepLabV3 for segmentation and InceptionV3 for classification, to detect and classify acne lesions. Achieving a 97% accuracy rate, the model incorporates Grad-CAM for explainable AI, enhancing transparency in dermatological diagnostics.


🚁 A Deep Q-Learning Based UAV Detouring Algorithm in a Constrained Wireless Sensor Network Environment

  • Journal: Electronics

  • Year: 2025

  • Citations: 0

  • Summary: This paper presents a Deep Q-Learning algorithm for unmanned aerial vehicles (UAVs) to navigate efficiently within constrained wireless sensor networks. The approach optimizes detouring strategies, enhancing UAV performance in complex environments.


🛡️ A Deep Learning Model for YOLOv9-based Human Abnormal Activity Detection: Violence and Non-Violence Classification

  • Journal: Iranian Journal of Electrical and Electronic Engineering

  • Year: 2024

  • Citations: 0

  • Summary: The research develops a YOLOv9-based deep learning model to classify human activities as violent or non-violent. Aimed at enhancing surveillance systems, the model contributes to improved public safety through accurate activity detection.

✅ Conclusion

Shakila Rahman is a highly suitable candidate for the Best Researcher Award due to her blend of academic excellence, innovative research, international exposure, and impactful contributions to AI and networking fields. Her work not only advances fundamental knowledge but also targets practical challenges, demonstrating a research trajectory with strong future promise. Recognizing her with this award would celebrate her achievements and encourage continued excellence in emerging technology domains. 🚀🤖📡