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

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

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

“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
“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
“Automatic fire and smoke detection method for surveillance systems based on dilated CNNs”
- Authors: Y Valikhujaev, A Abdusalomov, YI Cho
- Year: 2020
- Citations: 69
“Brain tumor detection based on deep learning approaches and magnetic resonance imaging”
- Authors: AB Abdusalomov, M Mukhiddinov, TK Whangbo
- Year: 2023
- Citations: 63
“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
“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
“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
“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
“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

Introduction of Innovation Excellence Award: Science and Technology

Welcome to the forefront of scientific and technological innovation! The Innovation Excellence Award in Science and Technology is a beacon of recognition for those pushing the boundaries of what's possible. This prestigious award celebrates pioneers who drive advancements in our understanding of the world and its possibilities through groundbreaking research and technological breakthroughs.

About the Award:

The Innovation Excellence Award in Science and Technology is open to professionals and researchers across diverse fields, emphasizing a commitment to excellence in pushing the boundaries of knowledge and application. There are no age restrictions, and eligibility is open to individuals or teams demonstrating exceptional innovation in science and technology.

Qualifications and Publications:

Candidates should possess a proven track record of innovation, demonstrated through impactful publications and contributions to the scientific and technological community. Qualifications may include a Ph.D. or equivalent experience, highlighting a commitment to advancing the frontiers of knowledge.

Evaluation Criteria:

The evaluation process emphasizes the significance, originality, and potential impact of the innovation. Judges will assess the candidate's contributions to scientific and technological progress, considering the quality and influence of their work.

Submission Guidelines:

Submit a comprehensive biography, an abstract outlining the innovation's key aspects, and supporting files that showcase the practical applications and results of the work. Ensure all submissions adhere to the provided guidelines for a fair and thorough evaluation.

Recognition and Community Impact:

The Innovation Excellence Award not only celebrates individual accomplishments but also recognizes the broader impact on the scientific and technological community. Winners become ambassadors for progress, inspiring others to pursue excellence in their endeavors.

Biography, Abstract, and Supporting Files:

Craft a detailed biography showcasing your journey in the field. The abstract should concisely convey the innovation's significance, and supporting files should offer a comprehensive view of the work's methodology, outcomes, and potential applications.

Akmalbek Abdusalomov | Computer Science | Best Researcher Award

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

Education

Professional Experience

Research Interest

Award and Honors

Innovation Excellence Award: Science and Technology

Introduction of Innovation Excellence Award: Science and Technology

About the Award:

Qualifications and Publications:

Evaluation Criteria:

Submission Guidelines:

Recognition and Community Impact:

Biography, Abstract, and Supporting Files:

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