Qiang Li | Computer Science | Best Researcher Award

Mr. Qiang Li | Computer Science | Best Researcher Award

Lecturer, Qingdao University, China

Dr. Li Qiang is an experienced lecturer in computer science with a PhD in Engineering. He specializes in high-performance computing and has a strong background in both teaching and research. Committed to fostering academic excellence and technological innovation, Dr. Li has been a dedicated educator and researcher at Qingdao University since 2015.

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Education 🎓

PhD in Engineering: University of the Chinese Academy of Sciences, Computer Network Information Center (2010-2014), Advisor: Lu Zhonghua. Master’s in Information Science and Engineering: Shandong University of Science and Technology (2007-2010), Advisor: Zhao Maoxian. Bachelor’s in Education: Qingdao University (2003-2007).

Experience 👨‍🏫

Lecturer at Qingdao University, School of Computer Science and Technology (January 2015-Present). Teaching undergraduate and graduate courses in computer science. Supervising student research projects and theses. Conducting research in high-performance computing. Published 12 research papers in journals and conferences. Granted 2 patents.

Research Interests 🔬

Dr. Li Qiang’s research interests lie in high-performance computing, particularly in the optimization and parallel implementation of numerical simulations and the development of new computational frameworks. His work focuses on enhancing computational efficiency and scalability in large-scale scientific computations.

Awards 🏆

Dr. Li Qiang has been recognized for his contributions to the field of high-performance computing through multiple publications and patents. His innovative work has led to advancements in computational methods and has garnered attention in the academic community.

Publications 📄

Optimization Research of Heterogeneous 2D-Parallel Lattice Boltzmann Method Based on Deep Computing Unit. Appl. Sci. 2024, 14, 6078.

Heterogeneous Parallel Implementation of Large-Scale Numerical Simulation of Saint-Venant Equations. Appl. Sci. 2022, 12, 5671. Cited by 6

The Study of Parallelization of SWAT Hydrology Cycle. The 32nd ACM International Conference on Supercomputing, Beijing, 2018. [Cited by 3]

A New Parallel Framework of Distributed SWAT Calibration. Journal of Arid Land, 2015, 7(1): 122-131. [Cited by 7]

Parallel Simulation of High-Dimensional American Option Pricing Based on CPU VS MIC. Concurrency and Computation: Practice and Experience, 2014, 27(5): 1110-1121. [Cited by 5]

Jihyeon Ryu | Computer Science | Best Researcher Award

Assist Prof Dr. Jihyeon Ryu | Computer Science | Best Researcher Award

Professor, Kwangwoon University, South Korea

👩‍🏫 Jihyeon Ryu is an Assistant Professor at the School of Computer and Information Engineering, Kwangwoon University. She specializes in split learning, convolutional neural networks, and user authentication, contributing significantly to the field of computer science with her extensive research and numerous publications.

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Education

Ph.D. in Software (Integrated Master’s and Doctorate Course) from Sungkyunkwan University (Mar. 2018 – Feb. 2023), advised by Prof. Dongho Won and Prof. Hyoungshick Kim. B.S. in Mathematics and Computer Science and Engineering from Sungkyunkwan University (Mar. 2013 – Feb. 2018). Early Graduation from Sejong Science High School (Mar. 2011 – Feb. 2013).

 

Research Interests:

Split Learning. Convolutional Neural Networks. User Authentication

Awards

Family Company Workshop Lecture, Hoseo University (Feb. 2022). Invited Lecturer, Mental Women’s High School (Nov. 2021). Excellence Prize, Software Department Excellence Research Awards (Feb. 2021). Graduate Merit Scholarship, Sungkyunkwan University (Mar. 2018 – Feb. 2021). SimSan Scholarship, Multiple instances (Mar. 2018 – Sep. 2020). Excellence Award, 국가 암호기술 전문인력 양성과정 (Nov. 2019). Grand Prize, Software Department Excellence Research Awards (Feb. 2019). Samsung Science Scholarship (Mar. 2013 – Feb. 2018)

Publications

Lightweight Hash-Based Authentication Protocol for Smart Grids. Sensors, 2024. Sangjin Kook, Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.

Enhanced Lightweight Medical Sensor Networks Authentication Scheme Based on Blockchain. IEEE ACCESS, 2024. Taewoong Kang, Naryun Woo, Jihyeon Ryu.

Secure and Anonymous Authentication Scheme for Mobile Edge Computing Environments. IEEE Internet of Things Journal, 2024. Hakjun Lee, Jihyeon Ryu, Dongho Won.

Distributed and Federated Authentication Schemes Based on Updatable Smart Contracts. Electronics, 2023. Keunok Kim, Jihyeon Ryu, Hakjun Lee, Youngsook Lee, Dongho Won.

An Improved Lightweight User Authentication Scheme for the Internet of Medical Things. Sensors, 2023. Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.

Najmeh Zamani | Engineering | Best Researcher Award

Dr. Najmeh Zamani | Engineering | Best Researcher Award 

Postdoc researcher, Concordia university, Canada

🌟 Najmeh Zamani (b. 29th July 1989) is a dedicated researcher in the field of electrical and computer engineering. She is currently a Postdoctoral Researcher at Concordia University, Canada, with a strong academic background from Isfahan University of Technology, Iran. Najmeh’s expertise spans control systems, nonlinear multi-agent systems, and deep learning applications. Married and proficient in both Persian and English, she is recognized for her significant contributions to her field.

 

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Education

🎓 Najmeh Zamani has an impressive academic record, starting with a Bachelor’s degree in Electrical Engineering from Isfahan University (2007-2011), where she ranked 1st. She continued at the same university for her Master’s degree (2011-2014), ranking 3rd, and then pursued a Ph.D. in Electrical Engineering at Isfahan University of Technology (2015-2021), achieving a GPA of 19/20. Her Ph.D. dissertation focused on the “Consensus of Nonlinear Multi-Agent Systems with Time-Delays and Actuator Faults.” Najmeh also completed postdoctoral research at Concordia University, Canada, in 2023.

Experience

💼 Najmeh Zamani has a robust professional background, including roles as a researcher at Isfahan University of Technology, an R&D researcher at Control Farayand Pasargad Company, and an electronic designer at Sirco Company. Her experience spans industrial projects like COVID-19 pandemic prediction models and power electronic boost converter design. Najmeh has also served as a visiting professor and teaching assistant in various institutions, sharing her expertise in control systems and electronics.

Research Interests

🔬 Najmeh Zamani‘s research interests are diverse and cutting-edge. They include distributed control systems and multi-agent systems, adaptive control of nonlinear systems with time-delays and faults, fault estimation and control theory, and control of distributed applications like mobile sensors. She is also passionate about deep learning, probabilistic graphical models (PGM), data-driven control, reinforcement learning, and data analysis.

Awards

🏆 Najmeh Zamani has received several accolades throughout her academic journey. She was ranked 1st among all graduated students in Electrical and Computer Engineering at Isfahan University in 2011. She was also recognized as an outstanding B.Sc. and M.Sc. student from 2007 to 2014. Notably, she received admission offers for both her graduate and doctoral studies at Isfahan University of Technology without needing to take the National Entrance Exam for Graduate Schools.

Publications

N. Zamani, M. Ataei, M. Niroomand, “Analysis and Control of Chaotic Behavior in Boost Converter by Ramp Compensation Based on Lyapunov Exponents Assignment: Theoretical and Experimental Investigation”, Chaos, Solitons and Fractals, 2015, cited by 20 articles. Link.

N. Zamani, J. Askari, M. Kamali, A. Aghdam, “Distributed adaptive consensus tracking control for non-linear multi-agent systems with time-varying delays”, IET Control Theory & Applications, 2020, cited by 15 articles. Link.

H. Kalantari, M. Mojiri, S. Dubljevic, N. Zamani, “Fast l1-MPC Based on Sensitivity Analysis Strategy”, IET Control Theory & Applications, 2020, cited by 10 articles. Link.

N. Zamani, J. Askari, M. Kamali, H. Kalantari, A. Aghdam, “Adaptive Tracking Control for Nonlinear Multi-Agent Systems with Stuck Failures and Unknown Control Directions”, Journal of the Franklin Institute, 2024. Link.

H. Kalantari, M. Mojiri, Najmeh Zamani, “Urban Traffic Control By Fast l1 Model Predictive Control Based on Sensitivity Analysis”, IET Control Theory & Applications, 2024. Link.