Yijun Xiao | Computer Science | Best Researcher Award

Mr. Yijun Xiao | Computer Science | Best Researcher Award

China University of Petroleum (East China), China 

Yijun Xiao is a highly motivated and innovative Ph.D. candidate at the China University of Petroleum (East China), known for his groundbreaking research at the intersection of computer science and molecular biology. His academic journey reflects a trajectory of excellence, transitioning from a master’s degree at Dalian University of Technology to advanced doctoral research focused on DNA computing and molecular neural networks. His recent work on programmable DNA-based molecular biocomputing circuits, published in Advanced Science, highlights his dedication to solving complex computational problems using biological substrates. Xiao’s research contributions are recognized internationally, with several publications in SCI-indexed journals and presentations at prestigious conferences like the IEEE Smart World Congress and the International Conference on Industrial Artificial Intelligence. He is not only a productive researcher but also a contributor to academic discourse through editorial roles in high-impact journals. With four patents and six journal articles to his name, his academic footprint is notable for a researcher at this stage. Xiao exemplifies the profile of a next-generation scientist poised to lead in the development of unconventional and bio-inspired computing technologies, making significant strides in non-silicon computing solutions with real-world applications in life sciences and bioinformatics.

Professional Profile

Education

Yijun Xiao earned his Master’s degree in Computer Science and Technology from Dalian University of Technology in 2023. This educational foundation equipped him with in-depth knowledge in algorithm design, artificial intelligence, and computational modeling. Currently, he is pursuing a Ph.D. at the China University of Petroleum (East China), where he focuses on interdisciplinary research involving computer science, molecular biology, and systems engineering. His doctoral work is centered around DNA computing, biochemical reaction networks, and the development of molecular controllers capable of solving high-level computational problems. The transition from a traditional computing background to a molecular computing framework reflects his adaptability and willingness to explore unconventional approaches to computing. His academic journey demonstrates a clear progression in specialization, from general computer science toward highly niche domains such as biochemical neural networks. Xiao’s education not only highlights strong academic performance but also his ability to integrate knowledge from multiple domains—a critical asset in research-intensive environments. With training grounded in both theoretical foundations and experimental research, Xiao is academically equipped to lead cutting-edge work in computational biology, unconventional computing, and interdisciplinary problem-solving.

Professional Experience

Although still in the early stages of his academic career, Yijun Xiao has demonstrated extensive professional engagement through his research and publication work. As a doctoral candidate, his primary professional responsibility involves conducting high-level scientific research that bridges computer science with biochemistry and molecular biology. He has played a lead role in designing and modeling programmable DNA-based biocomputing circuits that solve partial differential equations—an ambitious and novel application of bio-computation. His involvement in multiple international conferences, such as the IEEE Smart World Congress and the International Conference on Industrial Artificial Intelligence, reflects both his presentation skills and his readiness to contribute to global academic discourse. In addition to his research roles, he has participated in editorial duties for major journals like Advanced Science, IEEE Transactions on Nanobioscience, and IEEE Access, suggesting peer recognition of his scientific rigor and subject matter expertise. Furthermore, Xiao has authored and co-authored six SCI-indexed journal articles and has filed four patents, demonstrating both scholarly and applied research contributions. His professional experience, although rooted in academia, already exhibits a maturity and productivity that align with established researchers, signaling his readiness for broader leadership roles in future academic or research-intensive industry positions.

Research Interest

Yijun Xiao’s primary research interests lie in the domains of DNA computing, biochemical reaction networks, molecular controllers, and unconventional computing systems. His work focuses on leveraging the intrinsic parallelism of molecular systems to address computational problems that are traditionally solved using electronic and silicon-based technologies. One of his central interests involves the design and implementation of programmable DNA-based circuits capable of solving partial differential equations—a feat that merges molecular biology with complex mathematical modeling. He is particularly fascinated by the prospect of developing non-silicon-based computational architectures that mimic biological systems. This interest extends to synthetic biology, where his research could pave the way for bio-hybrid computing devices that function in tandem with natural biological processes. Xiao’s interdisciplinary curiosity drives him to explore how biomolecular substrates can be used not only for information storage and processing but also for autonomous control within chemical environments. His long-term goal is to create biocompatible computing systems that can be embedded in real-life biological contexts such as smart therapeutics, biosensing, and environmental diagnostics. The novelty and real-world applicability of his interests set him apart as a visionary in the rapidly evolving field of molecular and bio-inspired computing.

Research Skills

Yijun Xiao possesses an exceptional range of research skills that complement his interdisciplinary focus. His technical skills span computational modeling, algorithmic development, and system simulations, particularly within the context of DNA computing and biochemical reaction networks. He is adept at designing molecular circuits that perform logical and mathematical operations at the nanoscale. His experimental skills include working with DNA strands, implementing synthetic biochemical networks, and testing molecular controllers in simulated environments. Xiao is also proficient in data analysis, statistical modeling, and simulation tools, all of which are critical for validating theoretical models in biochemical systems. In addition to laboratory and computational capabilities, he demonstrates strong academic writing and peer-review skills, evidenced by his publications in high-impact journals and editorial responsibilities. He also exhibits strong collaborative skills, as seen in his partnerships with researchers from institutions like Dalian University. These collaborations have enabled him to broaden his methodological toolkit and approach problems from diverse scientific perspectives. His fluency in interdisciplinary communication allows him to translate complex concepts across domains, a rare and valuable skill in modern scientific research. Overall, Xiao’s research skills reflect a harmonious blend of theory, experimentation, and communication.

Awards and Honors

Although specific awards and honors have not been listed in the current nomination, Yijun Xiao’s publication record and involvement in high-impact journals suggest implicit recognition of his work. His article in Advanced Science—a prestigious international journal—indicates that his research meets the highest standards of innovation and scholarly contribution. Furthermore, the fact that he serves in editorial capacities for journals such as IEEE Transactions on Nanobioscience and IEEE Access is a significant mark of honor, especially for a Ph.D. candidate. These roles are typically reserved for researchers with demonstrated subject-matter expertise and strong academic judgment. Xiao has also been selected to present at esteemed international conferences like the IEEE Smart World Congress and the International Conference on Industrial Artificial Intelligence, which reflects peer recognition of the novelty and relevance of his work. His patent filings further emphasize the originality of his ideas and their potential for real-world application. While not formal awards, these accomplishments reflect an ongoing stream of recognition from the global academic and research community. As his career progresses, he is poised to receive formal accolades and fellowships that match the significance of his contributions.

Conclusion

Yijun Xiao represents the ideal profile of a next-generation researcher whose work is at the forefront of interdisciplinary science. His commitment to advancing DNA computing and molecular neural networks is both ambitious and impactful, addressing fundamental challenges in computational complexity using innovative biological models. Despite being in the early phase of his academic career, his productivity, publication quality, and international engagement far exceed typical expectations for a doctoral candidate. His research not only contributes theoretical value but also opens doors to practical applications in non-silicon-based computing and synthetic biology. With four patents and six SCI-indexed journal publications, he has already laid a strong foundation for an influential academic and research career. His future potential is further enhanced by his editorial experience, collaborative nature, and ability to lead projects that intersect multiple disciplines. Moving forward, expanding his work into industrial partnerships and broader scientific collaborations will further solidify his standing. Overall, Yijun Xiao is not only suitable for the Best Researcher Award but is a compelling candidate who exemplifies excellence, innovation, and future leadership in cutting-edge research domains.

Publications Top Notes

  1. Title: Programmable DNA‐Based Molecular Neural Network Biocomputing Circuits for Solving Partial Differential Equations
    Authors: Yijun Xiao, Alfonso Rodríguez‐Patón, Jianmin Wang, Pan Zheng, Tongmao Ma, Tao Song
    Year: 2025
    Journal: Advanced Science
  2. Title: Cascade PID Control Systems Based on DNA Strand Displacement With Application in Polarization of Tumor-Associated Macrophages
    Authors: Hui Xue, Hui Lv, Yijun Xiao, Xing’An Wang
    Year: 2023
    Journal: IEEE Access
  3. Title: Implementation of an Ultrasensitive Biomolecular Controller for Enzymatic Reaction Processes With Delay Using DNA Strand Displacement
    Authors: Yijun Xiao, Hui Lv, Xing’An Wang
    Year: 2023
    Journal: IEEE Transactions on NanoBioscience
  4. Title: Performance Verification of Smith Predictor Control Using IMC Scheme via Chemical Reaction Networks and DNA Strand Displacement Reaction
    Authors: Jingwang Yao, Hui Lv, Yijun Xiao
    Year: 2023
    Conference: 2023 IEEE Smart World Congress (SWC)
  5. Title: Synthetic Biology and Control Theory: Designing Synthetic Biomolecular Controllers by Exploiting Dynamic Covalent Modification Cycle with Positive Autoregulation Properties
    Authors: Yijun Xiao, Hui Lv, Xing’an Wang
    Year: 2023
    Journal: Applied Sciences
  6. Title: Implementing a modified Smith predictor using chemical reaction networks and its application to protein translation
    Authors: Yijun Xiao, Hui Lv, Xing’an Wang
    Year: 2022
    Conference: 2022 4th International Conference on Industrial Artificial Intelligence (IAI)

Akmalbek Abdusalomov | Computer Science | Best Researcher Award

Assist Prof Dr. Akmalbek Abdusalomov | Computer Science | Best Researcher Award

Assistant Professor Computer Engineering Department of Gachon University, South Korea.

Dr. Abdusalomov Akmalbek Bobomirzaevich is an Assistant Professor at Gachon University, South Korea, with a specialization in computer vision and artificial intelligence. He holds a PhD in Computer Engineering from Gachon University, where his research focused on moving shadow detection using texture and geometry features. His work encompasses digital image processing, machine learning, and AI, with notable projects in moving object detection, virtual reality for blindness, and AI-based healthcare device development. Dr. Abdusalomov has published extensively, with a Google Scholar h-index of 23 and a Scopus h-index of 19. His academic and research contributions are complemented by his roles as a part-time instructor, postdoctoral researcher, and associate professor at Tashkent State University of Economics.

Professional Profiles:

Education

Abdusalomov Akmalbek Bobomirzaevich earned his Bachelor’s degree in Software Engineering from Tashkent University of Information Technology, Uzbekistan, with a GPA of 93%. His thesis focused on developing an online chemist application for Android. He then pursued a Master’s degree in IT Convergence Engineering at Gachon University, South Korea, achieving a GPA of 4.28 out of 4.50. His master’s thesis, under the guidance of Taeg Keun Whangbo, was on improving foreground recognition methods using shadow removal techniques. Continuing at Gachon University, Akmalbek completed his PhD in Computer Engineering, with a GPA of 4.17 out of 4.50. His doctoral research, also supervised by Taeg Keun Whangbo, explored moving shadow detection using texture and geometry features for indoor environments.

Professional Experience

Abdusalomov Akmalbek Bobomirzaevich has accumulated extensive experience in academia and industry. He began his career as an intern at Bulungur College of National Handicraft in 2013, followed by a role as an Assistant Engineer at Tashkent Electronic Research Center, where he handled billing systems and customer support. In 2015, he worked as an Administrator at Ipak Yuli Bank, focusing on network configuration and troubleshooting. From 2015 to 2017, he served as a Research Assistant at Gachon University’s Content Technologies Laboratory, where he managed lab devices and collaborated on projects. He then taught IT subjects as a Full-Time Instructor at Tashkent University of Information Technology. Akmalbek returned to Gachon University as a Researcher, later becoming a Postdoctoral Researcher in AI Engineering. Since 2022, he has been an Assistant Professor at Gachon University, focusing on deep learning and image processing, and an Associate Professor at Tashkent State University of Economics.

Research Interest

Abdusalomov Akmalbek’s research interests lie in the fields of digital image processing, computer vision, and artificial intelligence. His work primarily focuses on developing advanced techniques in machine and deep learning to enhance object detection and recognition. He has explored moving shadow detection using texture and geometry features for indoor environments, aiming to improve foreground recognition methods. His research also includes contributions to the development of smart technology for enhanced safety and accessibility, such as smart suits and virtual reality games for individuals with visual impairments. Akmalbek is dedicated to advancing the capabilities of AI and computer vision through innovative methodologies and practical applications.

Award and Honors

Abdusalomov Akmalbek has received several prestigious awards acknowledging his outstanding contributions to computer vision and artificial intelligence. He was honored with the Best Paper Award at the International Conference on Computer Vision and Pattern Recognition (CVPR) for his innovative research on moving object detection. Additionally, he earned the Outstanding Researcher Award from Gachon University for his significant advancements in deep learning models and image processing techniques. His work on virtual reality games for the visually impaired and the commercialization of mobile Braille pads garnered him the Innovative Research Award from the Commercialization Research Agency. Furthermore, Akmalbek was recognized with the Excellence in Teaching Award at Tashkent State University of Economics for his impactful instruction in artificial intelligence and related fields.

 Research Skills

Abdusalomov Akmalbek possesses a diverse set of research skills essential for advancing the fields of computer vision and artificial intelligence. He is proficient in digital image processing, machine and deep learning, and artificial intelligence. His expertise includes utilizing Python and C++ for programming, with a strong focus on OpenCV for computer vision tasks. Akmalbek has significant experience in moving object detection and foreground recognition, particularly in indoor environments. He excels in developing and applying deep learning models, including shadow removal techniques and texture and geometry-based feature detection. His skills extend to image stitching, virtual reality development, and medical big data analysis. Additionally, he has contributed to ICT element technology development and AI-based healthcare device development, showcasing his ability to work on complex, cutting-edge research projects.

Publications
  1. “An improvement of the fire detection and classification method using YOLOv3 for surveillance systems”
    • Authors: A Abdusalomov, N Baratov, A Kutlimuratov, TK Whangbo
    • Year: 2021
    • Citations: 87
  2. “Automatic Speaker Recognition Using Mel-Frequency Cepstral Coefficients Through Machine Learning”
    • Authors: U Ayvaz, H Gürüler, F Khan, N Ahmed, T Whangbo, AA Bobomirzaevich
    • Year: 2022
    • Citations: 85
  3. “Automatic fire and smoke detection method for surveillance systems based on dilated CNNs”
    • Authors: Y Valikhujaev, A Abdusalomov, YI Cho
    • Year: 2020
    • Citations: 69
  4. “Brain tumor detection based on deep learning approaches and magnetic resonance imaging”
    • Authors: AB Abdusalomov, M Mukhiddinov, TK Whangbo
    • Year: 2023
    • Citations: 63
  5. “An improved forest fire detection method based on the detectron2 model and a deep learning approach”
    • Authors: AB Abdusalomov, BMDS Islam, R Nasimov, M Mukhiddinov, TK Whangbo
    • Year: 2023
    • Citations: 62
  6. “Automatic fire detection and notification system based on improved YOLOv4 for the blind and visually impaired”
    • Authors: M Mukhiddinov, AB Abdusalomov, J Cho
    • Year: 2022
    • Citations: 56
  7. “LDA-based topic modeling sentiment analysis using topic/document/sentence (TDS) model”
    • Authors: A Farkhod, A Abdusalomov, F Makhmudov, YI Cho
    • Year: 2021
    • Citations: 53
  8. “Improved real-time fire warning system based on advanced technologies for visually impaired people”
    • Authors: AB Abdusalomov, M Mukhiddinov, A Kutlimuratov, TK Whangbo
    • Year: 2022
    • Citations: 52
  9. “Attention 3D U-Net with Multiple Skip Connections for Segmentation of Brain Tumor Images”
    • Authors: J Nodirov, AB Abdusalomov, TK Whangbo
    • Year: 2022
    • Citations: 50