Guangdong Zhou | Artificial Intelligence in Mathematics | Best Researcher Award

Posted on by Math Scientist

Prof. Guangdong Zhou | Artificial Intelligence in Mathematics | Best Researcher Award

Professor at Southwest university, China

Prof. Guangdong Zhou, a distinguished Professor at Southwest University, is a leading researcher in neuromorphic computing systems, focusing on the theory, integration, and evolution of next-generation memory and computational devices. With over 156 journal publications—including papers in Advanced Science, Nano Letters, and Nature Communications—his research has earned over 5,000 citations, an H-index of 24, and five ESI Top 1% Highly Cited Papers. Prof. Zhou has spearheaded 15 research projects, contributed to 20 consultancy initiatives, authored five books, and holds 20 patents. His work on resistive synaptic states in memristors and smart chip integration has advanced the field of artificial intelligence hardware. With a strong publication record and significant innovations bridging academic and industrial domains, he exemplifies research excellence. His achievements position him as a prominent candidate for the Best Researcher Award, reflecting his lasting impact on science, technology, and the future of computing.

Professional Profile

Google Scholar
Scopus Profile

🎓 Education

Prof. Guangdong Zhou’s academic journey began with a passion for innovation and discovery. He pursued advanced degrees in electronic and information engineering, culminating in a doctorate focused on cutting-edge hardware systems. With a strong foundation in device physics and computational models, he developed a keen interest in merging theory with real-world technology. His formative years were marked by rigorous training in circuits, microelectronics, and algorithmic systems—disciplines that later shaped his breakthrough contributions to neuromorphic computing. Prof. Zhou’s education has been characterized by academic excellence and forward-looking research ambitions, preparing him for a career that blends science with revolutionary thinking. 📘💡

💼 Professional Experience

With a prolific career as a Professor at Southwest University, Prof. Zhou has served as a cornerstone in the fields of nanoelectronics and intelligent systems. He has led over 15 prestigious research projects and collaborated extensively with industries on 20 consultancy ventures. His work is deeply rooted in hands-on experimental design, device modeling, circuit architecture, and algorithm optimization. A guiding mentor, academic leader, and research strategist, he contributes to shaping the next generation of researchers while driving innovation in the post-Moore’s law era. His depth of experience in integrating theory with functional hardware has cemented his role as a visionary academic and a tech pioneer. 🧠🔬

🔍 Research Interest

Prof. Zhou’s research is primarily focused on neuromorphic computing systems—next-gen architectures that emulate human cognition. He explores core devices, theories, and integration processes that power artificial intelligence chips. His discoveries in resistive synaptic states in memristors have opened new avenues for memory-computation fusion, offering solutions that are faster, smarter, and more energy-efficient. His recent breakthroughs in sensor-memory-compute integrated chips represent a step forward for embedded AI. Prof. Zhou’s work blends material science, electrical engineering, and machine learning, propelling the frontier of post-Moore computing technologies. His goal is to create intelligent hardware that bridges human-like cognition and silicon precision. 🤖⚡

🏅 Awards and Honors

Prof. Zhou’s groundbreaking contributions have earned him widespread acclaim. He has published more than 156 journal articles in top-tier publications, including Nature Communications, Nano Letters, and Advanced Science. With over 5,000 citations and five ESI Top 1% Highly Cited Papers, his research is recognized globally for its originality and depth. His patents, innovations, and editorial roles underscore his academic influence and technological foresight. As an author of five published books and holder of 20 patents, Prof. Zhou is widely respected across the academic and industrial spheres. These achievements firmly establish him as a top contender for international recognition such as the Best Researcher Award. 🥇📚

📝 Conclusion

Prof. Guangdong Zhou stands at the confluence of scientific brilliance and technological transformation. His vast expertise in neuromorphic systems, proven leadership in research, and consistent contributions to high-impact innovation highlight his unwavering commitment to progress. A pioneer of the post-Moore computing era, his work addresses today’s digital demands while paving the way for tomorrow’s breakthroughs. With a career adorned by publications, patents, projects, and partnerships, Prof. Zhou exemplifies the essence of a modern research trailblazer. His remarkable journey is not only an inspiration for aspiring scholars but also a beacon for the global research community. 🌐🚀

Publications Top Notes

📘 1. Evolution from CRS to SRS in a Multifunctional Ag/TiO₂@MoO₃/Ti Memristor for Emotional Perception Application

  • 🧑‍🔬 Authors: Jiajia Qin, Bai Sun, Shuangsuo Mao, Yulong Yang, Yong Zhao

  • 📅 Year: 2025

  • 📊 Citations: 0

  • 📰 Source: Applied Materials Today

  • 💡 Theme: Emotional computing with multifunctional memristors 💖

🌟 2. Photoelectric Reservoir Computing Based on TiOx Memristor for Analog Signal Processing

  • 🧑‍🔬 Authors: Zimu Li, Dengshun Gu, Xuesen Xie, Shukai Duan, Guangdong Zhou

  • 📅 Year: 2025

  • 📊 Citations: 0

  • 📰 Source: ACS Applied Nano Materials

  • 💡 Theme: Memristive analog signal computing powered by light 💡🔁

🌱 3. An Organic Artificial Synaptic Memristor for Neuromorphic Computing

  • 🧑‍🔬 Authors: Kaikai Gao, Bai Sun, Bo Yang, Xiaoliang Chen, Jinyou Shao

  • 📅 Year: 2025

  • 📊 Citations: 0

  • 📰 Source: Applied Materials Today

  • 💡 Theme: Bio-inspired computing using organic materials 🧠🌿

🧠 4. Self-Rectifying Switching Memory Based on HfOx/FeOx Semiconductor Heterostructure for Neuromorphic Computing

  • 🧑‍🔬 Authors: Haofeng Ran, Zhijun Ren, Jie Li, Shukai Duan, Guangdong Zhou

  • 📅 Year: 2025

  • 📊 Citations: 1

  • 📰 Source: Advanced Functional Materials

  • 💡 Theme: Efficient and selective memory switching for AI 🧠⚡

💡 5. Polymer Optoelectronic Synapse with Tunable Negative Photoconductance Memory for Sequential Signal Processing

  • 🧑‍🔬 Authors: Zhaohui Yang, Dengshun Gu, Bochang Zhang, Shukai Duan, Guangdong Zhou

  • 📅 Year: 2025

  • 📊 Citations: 0

  • 📰 Source: ACS Applied Electronic Materials

  • 💡 Theme: Light-controllable memory synapses for AI logic 📲🔦

❤️‍🩹 6. TiOx-Based Implantable Memristor for Biomedical Engineering

  • 🧑‍🔬 Authors: Chuan Yang, Hongyan Wang, Zelin Cao, Yong Zhao, Bai Sun

  • 📅 Year: 2025

  • 📊 Citations: 0

  • 📰 Source: ACS Applied Materials and Interfaces

  • 💡 Theme: Future-ready implantables for bio-interfacing tech 🧬🩺

🫁 7. A High-Stability Pressure-Sensitive Implantable Memristor for Pulmonary Hypertension Monitoring

  • 🧑‍🔬 Authors: Zelin Cao, Yiwei Liu, Bai Sun, Jinyou Shao, Sida Qin

  • 📅 Year: 2025

  • 📊 Citations: 5

  • 📰 Source: Advanced Materials

  • 💡 Theme: Real-time pressure detection for advanced health monitoring 🌡️🫁

🧪 8. Investigation of the TaOx Unipolar Switching Memory on High-Efficiency Computing

  • 🧑‍🔬 Authors: Chunrong Du, Xiaoyue Ji, Zhekang Dong, Shukai Duan, Guangdong Zhou

  • 📅 Year: 2025

  • 📊 Citations: 0

  • 📰 Source: Journal of Alloys and Compounds

  • 💡 Theme: Accelerating computing with advanced memory systems 💻⚙️

🔊 9. Flexible Artificial Vision Computing System Based on FeOx Optomemristor for Speech Recognition

  • 🧑‍🔬 Authors: Jie Li, Yue Xin, Bai Sun, Shukai Duan, Guangdong Zhou

  • 📅 Year: 2025

  • 📊 Citations: 1

  • 📰 Source: Journal of Semiconductors

  • 💡 Theme: Bridging vision and sound through flexible AI tech 🎤👁️

 

Miljana Milic | Artificial Intelligence in Mathematics | Best Academic Researcher Award

Posted on by Math Scientist

Prof. Dr. Miljana Milic | Artificial Intelligence in Mathematics | Best Academic Researcher Award

University Full Professor at University of Nis, Faculty of Electronic Engineering, Serbia

Prof. Dr. Miljana Milic is a distinguished full professor at the University of Niš, specializing in applied mathematics, artificial intelligence, and electronic circuit design. With an extensive academic background, she holds MSc and PhD degrees in Electrical Engineering and has made significant contributions to neural networks, forecasting algorithms, and VLSI circuit design. Her research focuses on improving forecasting accuracy and system performance, with notable publications in high-impact journals such as Mathematics and Microelectronics Reliability. Prof. Milic’s work spans across numerous international collaborations, particularly in Southeast Europe and with renowned universities in Germany, the UK, and Greece. She has also contributed to multiple innovation projects and holds several patents. As a mentor, she has shaped the careers of emerging researchers while continuing her own impactful work in artificial intelligence and electronic systems. Prof. Milic’s research is recognized for its practical applications in energy systems, communications, and predictive modeling.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education

Prof. Dr. Miljana Milic holds both MSc and PhD degrees in Electrical Engineering, reflecting her strong academic foundation. Her education has equipped her with deep expertise in applied mathematics, artificial intelligence, and electronic circuit design, providing a solid base for her pioneering research in forecasting methods and complex system modeling. Over the years, her academic journey has been complemented by her continuous pursuit of knowledge through collaborations with prestigious institutions globally. Her educational background has not only formed the foundation of her research but also contributed to her leadership in shaping future engineers and researchers, further enhancing her impact on both the academic and professional communities.

Professional Experience

Prof. Dr. Miljana Milic is a full professor at the University of Niš, Faculty of Electronic Engineering, where she has significantly influenced both research and education. She has led several research projects funded by government agencies and collaborated internationally on various technical solutions related to electronic systems, artificial intelligence, and forecasting. With a focus on bridging theoretical advancements and practical applications, her career has seen her at the forefront of developments in areas such as VLSI circuits, predictive modeling, and energy systems. Prof. Milic’s teaching and mentorship have further cemented her reputation as a respected figure in academia.

Research Interest

Prof. Dr. Milic’s research spans applied mathematics, artificial intelligence, and electronic circuit design. Her primary focus lies in developing advanced forecasting methods, particularly using neural networks to improve prediction accuracy in time series modeling. Additionally, her work explores VLSI circuit design, specifically in the areas of delay estimation and integrated circuit testing. Prof. Milic is also dedicated to exploring the intersection of AI and electronic systems, applying predictive models to various sectors such as energy management, wireless communication, and healthcare. Her interdisciplinary approach aims to narrow the gap between theoretical research and real-world applications, particularly in the context of modern technological challenges.

Awards and Honors

Prof. Dr. Miljana Milic has received numerous accolades for her contributions to research and academia. Her work has been recognized internationally, with her publications cited widely across the academic community. She has received funding for numerous research projects, including those from the Ministry of Education, Science, and Technological Development in Serbia, highlighting her role in advancing scientific innovation. As a mentor and leader, Prof. Milic has also earned recognition for her dedication to education and academic development, playing a pivotal role in shaping the next generation of researchers in her field. Her ongoing contributions to academic journals and international collaborations further solidify her standing in the global research community.

Conclusion

Prof. Dr. Miljana Milic is an accomplished academic whose research has made a significant impact in the fields of artificial intelligence, neural networks, and electronic circuit design. With a strong academic background and extensive professional experience, she has contributed to numerous international projects and innovations that bridge theory with real-world applications. Her work in predictive modeling, particularly in energy systems and communication technologies, showcases her interdisciplinary approach and commitment to advancing modern science and engineering. Through her dedication to research, teaching, and mentorship, Prof. Milic continues to inspire and shape the future of engineering, making her a highly deserving candidate for the Best Academic Researcher Award.

Publications Top Notes

  • Title: Decimation Filter Design
    Authors: M. Sokolovic, B. Jovanovic, M. Damnjanovic
    Year: 2004
    Citation: 21
    Source: 24th International Conference on Microelectronics (IEEE Cat. No …)

  • Title: Modular Design of Fast Leading Zeros Counting Circuit
    Authors: N.Z. Milenkovic, V.V. Stankovic, M.L. Milic
    Year: 2015
    Citation: 19
    Source: Journal of Electrical Engineering 66 (6), 329

  • Title: Oscillation-Based Analog Diagnosis Using Artificial Neural Networks Based Inference Mechanism
    Authors: M.A. Stošović, M. Milić, M. Zwolinski, V. Litovski
    Year: 2013
    Citation: 19
    Source: Computers & Electrical Engineering 39 (2), 190-201

  • Title: Performance Analysis of SSC/SC Combiner at Two Time Instants in the Presence of Rayleigh Fading
    Authors: P. Nikolić, D. Krstić, M. Milić, M. Stefanović
    Year: 2011
    Citation: 17
    Source: Walter de Gruyter GmbH & Co. KG 65 (11-12), 319-325

  • Title: Simulation of a Pick-and-Place Cube Robot by Means of the Simulation Software KUKA Sim Pro
    Authors: D. Lukač
    Year: 2018
    Citation: 11
    Source: 41st International Convention on Information and Communication Technology (ICT)

  • Title: Analog Filter Diagnosis Using the Oscillation-Based Method
    Authors: M.S. Andrejevic, M. Milic
    Year: 2012
    Citation: 11
    Source: Journal of Electrical Engineering 63 (6), 349

  • Title: Oscillation-Based Analog Testing—A Case Study
    Authors: M. Milić, M.A. Stošović, V. Litovski
    Year: 2011
    Citation: 10
    Source: Proceedings of the 34th International Convention MIPRO, 96-101

  • Title: Using VHDL Simulator to Estimate Logic Path Delays in Combinational and Embedded Sequential Circuits
    Authors: M.L.J. Sokolovic, V.B. Litovski
    Year: 2005
    Citation: 10
    Source: EUROCON 2005-The International Conference on “Computer as a Tool” 2, 1683-1686

  • Title: Arduino-Based Non-Contact System for Thermal-Imaging of Electronic Circuits
    Authors: M. Milic, M. Ljubenovic
    Year: 2018
    Citation: 9
    Source: Zooming Innovation in Consumer Technologies Conference (ZINC), 62-67

  • Title: From Artificial Intelligence to Augmented Age: An Overview
    Authors: D. Lukac, M. Milic, J. Nikolic
    Year: 2018
    Citation: 6
    Source: Zooming Innovation in Consumer Technologies Conference (ZINC), 100-103

  • Title: Daily Danube River Water Level Prediction Using Extreme Learning Machine Approach
    Authors: M. Milić, N. Radivojević, J. Milojković, M. Jeremić
    Year: 2024
    Source: Facta Universitatis, Series: Automatic Control and Robotics 23 (1), 077-094

  • Title: Adaptation of the Feedback Transfer Function for Oscillation-Based Testing of Second-Order Active RC Filters
    Authors: D. Mirković, M. Milić, M.S. Mirković
    Year: 2024
    Source: Facta Universitatis, Series: Automatic Control and Robotics 23 (1), 001-015

  • Title: Prediction of Reference Evapotranspiration Using Neural Networks
    Authors: M. Milić, M. Jeremić, J. Milojković, M.S. Mirković
    Year: 2024
    Source: 11th International Conference on Electrical, Electronic and Computing Technologies

  • Title: Extended, Short-Term Neural Prediction Methodology for European Electricity Production by Type
    Authors: M.L.J. Milic, J.B. Milojković, A.Z. Petrusic
    Year: 2024
    Source: ACTA POLYTECHNICA HUNGARICA 21 (8), 147-168

  • Title: A Defects Classification Algorithm for Hybrid OBT–IDDQ Fault Diagnosis in Analog CMOS Integrated Circuits
    Authors: D.D. Mirkovic, M.L. Milić, M. Stanojlovic, V.Z. Petrovic
    Year: 2024
    Source: Journal of Circuits, Systems and Computers (2024)