Mr. Qiujie Yuan | Reservoir Computing | Best Researcher Award

Qiujie Yuan at Nanjing University of Posts and Telecommunications, China

Qiujie Yuan is a graduate researcher in Integrated Circuit Science and Engineering at Nanjing University of Posts and Telecommunications, with a strong foundation in applied physics. With hands-on experience in phase transition engineering and flexible 2D semiconductor device research, he demonstrates a rare blend of interdisciplinary R&D, system-level thinking, and international collaboration. His work focuses on electrochemically modulated MoS₂ transistors and bio-inspired temporal processing, contributing toward advancements in low-power, intelligent sensing systems.

🔹Professional Profile:

Scopus Profile

Orcid Profile 

🎓Education Background

Nanjing University of Posts and Telecommunications

• M.S. in Integrated Circuit Science and Engineering
  Sept 2023 – June 2026 (Expected)

• B.S. in Applied Physics
  June 2019 – June 2023

• Core Courses: Matrix Theory, CMOS Analog IC Design, Digital IC Analysis & Design, Power Devices & IC Design, Intelligent Sensors & Integrated Applications, Semiconductor Optoelectronics

💼 Professional Development

Graduate Researcher – National Key R&D Program
Focus: Flexible 2D Semiconductor Devices

• Designed MoS₂-based electrochemical transistor processes, achieving 7.8 cm²·V⁻¹·s⁻¹ mobility (23% improvement)

• Built a reservoir computing prototype with 92.4% classification accuracy using STDP optimization

• Established in situ electrochemical characterization protocols and multiphysics testbeds for over 160 parametric analyses

• Spearheaded interdisciplinary development from polymer electrolyte material synthesis (PVA/MXene) to system-level algorithm integration

Notable Project: “Reservoir Computing Enabled by Polymer Electrolyte-Gated MoS2 Transistors for Time-Series Processing”

• Introduced Li⁺-modulated phase transition for dynamic temporal processing

• Reduced system hardware complexity by 60% with scalable virtual node design

• Demonstrated successful material-to-system pipeline integration

🔬Research Focus

• Phase transition engineering and ionic modulation

• 2D semiconductors and electrochemical transistor design

• Reservoir computing and bio-inspired neuromorphic systems

• Integration of materials, device physics, and intelligent sensing algorithms

📈Author Metrics:

Qiujie Yuan is an emerging researcher with growing contributions in the fields of 2D semiconductors and neuromorphic computing. His recent work, “Reservoir Computing Enabled by Polymer Electrolyte-Gated MoS₂ Transistors for Time-Series Processing,” has been recognized for its innovation in integrating material synthesis with algorithmic intelligence. Although early in his publication career, his research demonstrates strong potential for high-impact citation, particularly in interdisciplinary domains such as flexible electronics, intelligent sensing systems, and electrochemical device engineering. His work has attracted attention in both academic and industrial circles for its engineering applicability and novel use of ionic modulation in dynamic systems. As he continues publishing, his author metrics are expected to grow rapidly, especially given his involvement in national key R&D programs and international collaborations.

🏆Awards and Honors:

• Second-Class Scholarship (Top 15%)

• Third-Class Scholarship

• Outstanding Graduate Cadre

• CET-6 Score: 586 | National Graduate Entrance English Score: 84

• Recognized for international technical collaboration across multilingual teams (Korea, Malaysia, Tunisia)

📝Publication Top Notes

Mr. Qiujie Yuan exemplifies a rare, high-potential interdisciplinary researcher who effectively bridges materials engineering, semiconductor device design, and AI-inspired computing architectures. His ability to integrate fundamental research with system-level applications and international collaboration marks him as a deserving candidate for a Best Researcher Award, especially in fields related to neuromorphic computing, flexible electronics, and intelligent sensing systems.

With continued publishing, diversified application trials, and increased visibility, Mr. Yuan is poised to become a key innovator in next-generation low-power AI hardware. He is not only suitable but highly recommended for recognition through this award.