Jasur Sevinov | Artificial Intelligence | Best Researcher Award

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Mr. Jasur Sevinov | Artificial Intelligence | Best Researcher Award

Head of Department | Tashkent State Technical University | Uzbekistan

Mr. Jasur Sevinov, DSc, is a distinguished academic and researcher in automation, adaptive control systems, and info processing. He has built his career at Tashkent State Technical University, where he has served in progressive academic and leadership roles. Currently, he is the Head of the Department of Info Processing and Management Systems, contributing to the advancement of education, scientific research, and modern automation solutions. His work focuses on synthesizing adaptive control systems and enhancing efficiency in technological processes. He has guided projects, published extensively in international journals, and participated in collaborations across Europe and Central Asia.

Professional Profile

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Education

Mr. Jasur Sevinov pursued his full academic journey at Tashkent State Technical University. He earned a bachelor’s degree in automation and control, followed by a master’s degree in production process automation. His postgraduate studies focused on algorithms for synthesizing adaptive control systems, leading to his candidate degree defense in control engineering. He further advanced his expertise with a Doctor of Science degree, specializing in adaptive control systems for technological objects based on identification approaches. Complementing his degrees, he completed professional courses in info systems, technology, and quality management, and participated in training events in Türkiye and Belgium.

Experience

Mr. Jasur Sevinov career at Tashkent State Technical University spans from assistant to senior lecturer, associate professor, and later department head. His leadership as Head of the Department of Info Processing and Management Systems reflects his dedication to academic excellence and innovation. Alongside teaching, he has developed curricula, supervised research projects, and contributed to international scientific collaborations. His expertise extends to creating adaptive control methods for dynamic systems and intelligent info-management systems for industrial production. Active in scientific councils, he evaluates doctoral research and contributes to policy development for higher education, solidifying his reputation as a respected leader.

Research Interests

His research interests lie in adaptive control systems, neural network applications in automation, decentralized control, and intelligent info systems. He is deeply engaged in designing algorithms that address uncertainty in technological processes and developing methods for system identification. His studies often focus on integrating speed gradient approaches and neural networks for advanced control solutions. He also explores real-time industrial process management, aiming to improve automation efficiency in sectors like energy, oil, gas, and production. By linking theory with practical application, his work supports both academic advancements and industrial innovations in adaptive and intelligent control technologies.

Awards

Mr. Jasur Sevinov has received recognition for his contributions to adaptive control theory and its applications in engineering. His doctoral dissertation earned him the prestigious Doctor of Science degree, validating his innovative methods in synthesizing adaptive control systems. He has been awarded leadership positions in scientific councils, reflecting his high standing in the academic community. His role as a committee member in scientific seminars demonstrates his recognition by peers. Beyond formal awards, his achievements are also reflected in his successful international collaborations, completed projects funded by research institutions, and his publications in globally indexed journals.

Top Noted Publications

Title: Algorithms of adaptive identification of uncertain operated objects in dynamical models
Year: 2017
Cited by: 48

Title: Algorithms of Nonparametric Synthesis of Discrete One-Dimensional Controllers
Year: 2020
Cited by: 34

Title: Algorithms for the synthesis of gradient controllers in a nonlinear control system
Year: 2022
Cited by: 32

Title: THE ALGORITHM OF ADAPTIVE ESTIMATION IN THE SYNTHESIS OF THE DYNAMIC OBJECTS CONTROL SYSTEMS
Year: 2020
Cited by: 25

Title: Algorithms for the synthesis of optimal linear-quadratic stationary controllers
Year: 2020
Cited by: 21

Conclusion

Mr. Jasur Sevinov clearly stands out as a dedicated researcher with substantial contributions in control systems and automation. His consistent progression in academic leadership, along with impactful scientific achievements, makes him a strong candidate for the Research for Best Researcher Award. With continued expansion of international collaborations and enhanced global dissemination, his influence in the scientific community can reach even greater heights.

Hyeryung Jang | Machine Learning | Best Researcher Award

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Assist. Prof. Dr Hyeryung Jang | Machine Learning | Best Researcher Award

Assistant Professor, Dongguk University, South Korea 🧑‍🏫

Hyeryung Jang is an Assistant Professor at the Division of AI Software Convergence at Dongguk University, Seoul, South Korea. His research interests lie at the intersection of communication systems, probabilistic graphical models, and networked machine learning. He has contributed significantly to the development of algorithms for large-scale communication networks, with applications in healthcare, manufacturing, and beyond. He has held academic and research positions at prestigious institutions, including King’s College London and KAIST.

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🎓 Education

Hyeryung Jang earned his Ph.D. in Electrical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), South Korea, from March 2012 to February 2017. His doctoral thesis, titled Optimization and Learning of Graphical Models: A Stochastic Approximation Approach, was supervised by Prof. Yung Yi and co-advised by Prof. Jinwoo Shin. He also holds a Master’s degree in Electrical Engineering from KAIST, completed between March 2010 and February 2012, with a thesis on the Economic Benefits of ISP-CDN and ISP-ISP Cooperation, under the guidance of Prof. Yung Yi. Hyeryung Jang completed his Bachelor’s degree in Electrical Engineering at KAIST in February 2010.

💼 Experience

Hyeryung Jang currently serves as an Assistant Professor in the Division of AI Software Convergence at Dongguk University, where he has been leading the Intelligence and Optimization in Networks (ION) lab since March 2021. Before this, he was a Research Associate at King’s College London, in the Centre for Telecommunications Research, Department of Engineering, from March 2018 to February 2021. His post-doctoral research was conducted at KAIST from March 2017 to February 2018. Hyeryung also gained valuable experience as a Research Intern at Los Alamos National Laboratory in the USA during the summer of 2015.

🔬 Research Interests

Hyeryung Jang’s research interests are centered on mathematical modeling and communication systems, with a particular emphasis on networked machine learning. He explores innovative learning algorithms for probabilistic graphical models, deep learning, and reinforcement learning. His work aims to improve the stability and representation quality of generative models such as GANs, VAEs, and diffusion models. Jang is also focused on the learning and inference of graphical models, specifically for applications like robust recommendation systems and communication-efficient algorithms. Moreover, his research delves into efficient learning methods to address noisy data and real-world challenges in fields like healthcare, highlighting his broad interdisciplinary approach to solving complex problems in communication networks.

🏆 Awards

Hyeryung Jang has received recognition for his groundbreaking work in networked machine learning, contributing to innovative applications in healthcare and telecommunications. His research has been published in top-tier journals such as IEEE Transactions on Communications, IEEE Transactions on Neural Networks and Learning Systems, and Journal of Medical Internet Research (JMIR).

📚 Publications Top Notes

LinkFND: Simple Framework for False Negative Detection in Recommendation Tasks with Graph Contrastive Learning, IEEE Access, Dec. 2023.

In-Home Smartphone-based Prediction of Obstructive Sleep Apnea in Conjunction with Level 2 Home Polysomnography, JAMA Otolaryngology-Head & Neck Surgery, Nov. 2023.

Prediction of Sleep Stages via Deep Learning using Smartphone Audio Recordings in Home Environments, Journal of Medical Internet Research, June 2023.

Real-time Detection of Sleep Apnea based on Breathing Sounds and Prediction Reinforcement using Home Noises, Journal of Medical Internet Research, Feb. 2023.

Conclusion

Given his strong academic credentials, innovative contributions, and high-impact research, Hyeryung Jang is undoubtedly a strong contender for the Best Researcher Award. His work not only advances theoretical knowledge but also drives practical applications that address critical real-world challenges, particularly in communication systems and healthcare. Jang’s passion for interdisciplinary research and teaching further solidifies his suitability for this prestigious recognition.