Chongan Zhang | Computer Science | Best Researcher Award

Mr. Chongan Zhang | Computer Science | Best Researcher Award

Researcher from Zhejiang University, China

Chongan Zhang is an accomplished researcher in the field of Biomedical Engineering with nearly a decade of hands-on experience in the research and development of advanced medical devices. Based at Zhejiang University, he has served as a core team member on numerous high-impact projects at national, provincial, and enterprise levels. His research has focused on the development and translational application of high-end medical endoscopes, surgical navigation systems, and digital processing systems used in endoscopic surgical robots. Chongan’s innovative contributions have led to the publication of 10 academic papers indexed in SCI and EI, covering significant topics such as endoscopy and surgical navigation. He holds one national invention patent, which reflects his ability to bridge the gap between academic research and real-world clinical applications. His interdisciplinary approach combines engineering, computer science, and medicine to address key challenges in minimally invasive surgery. Committed to improving surgical precision and patient outcomes, his work in the development of high-speed digital processing and core navigation components has gained recognition in both academic and industrial domains. With a clear focus on translational research, Chongan continues to strive toward excellence in biomedical device innovation, aligning scientific progress with societal healthcare needs.

Professional Profile

Education

Chongan Zhang pursued his academic journey in the field of Biomedical Engineering at Zhejiang University, one of China’s most prestigious institutions for engineering and medical sciences. His formal education provided him with a strong foundation in engineering principles, biological sciences, and clinical applications relevant to medical device development. During his academic tenure, he focused on courses related to medical instrumentation, imaging systems, embedded systems, and biomechanics, all of which shaped his research direction toward minimally invasive technologies and robotic systems. His graduate research work revolved around designing and optimizing surgical navigation systems and high-resolution endoscopic imaging techniques. This training equipped him with both theoretical knowledge and practical skills in device prototyping, data acquisition, digital signal processing, and interdisciplinary integration. The academic environment at Zhejiang University encouraged collaborative and innovation-driven learning, enabling Chongan to take part in cutting-edge projects and cross-disciplinary research. His thesis and project work often involved real-time system simulation, system control algorithms, and micro-electromechanical system (MEMS)-based designs for surgical applications. Overall, his education has been pivotal in preparing him for a research career at the intersection of biomedical engineering, computer science, and clinical technology, shaping his capacity for innovation and translational application in the healthcare sector.

Professional Experience

Chongan Zhang’s professional experience spans close to ten years in biomedical engineering, with a focus on the research, development, and translation of innovative medical devices. During his career, he has played a key role in multiple scientific and technological projects funded by national, provincial, ministerial, and enterprise-level agencies. At Zhejiang University, he has functioned as a central figure in research groups working on endoscopic surgical robots, minimally invasive surgical instrumentation, and high-speed digital processing systems. His primary responsibilities include system architecture design, component integration, algorithm development, and prototype validation. He has collaborated closely with clinicians, engineers, and industrial partners to ensure that the technologies under development meet real-world clinical needs. Notably, he has contributed significantly to the creation of next-generation medical endoscopes and surgical navigation platforms, ensuring they are both functionally advanced and ergonomically designed for clinical use. His experience also includes preparing documentation for regulatory approvals and technology transfer initiatives. By bridging research with industry, he has helped translate laboratory innovations into deployable healthcare solutions. His practical experience across diverse project scales and domains positions him as a well-rounded biomedical engineer with strong problem-solving skills and a commitment to healthcare advancement through engineering innovation.

Research Interests

Chongan Zhang’s research interests lie primarily in the design, development, and optimization of biomedical devices with a focus on endoscopic technologies and surgical navigation systems. He is particularly interested in the intersection of medical imaging, embedded systems, digital signal processing, and robotics, which collectively drive the innovation of next-generation surgical tools. His current research focuses on developing high-speed digital processing systems that enable real-time data handling during endoscopic procedures. Another key area of his interest is the advancement of surgical navigation systems to enhance accuracy and safety in minimally invasive surgeries. This involves both hardware design and the development of real-time localization and tracking algorithms. Chongan is also keen on translating academic research into clinically deployable technologies and is involved in designing core navigation components for robotic-assisted surgical systems. Furthermore, he is exploring the integration of AI-assisted guidance in endoscopic navigation, aiming to improve decision-making during surgeries. His long-term interest includes the development of patient-specific devices and systems that can adapt to diverse surgical environments. By bridging engineering and medicine, he seeks to contribute to the evolution of smart surgical environments and better patient outcomes through technical excellence and user-centered design.

Research Skills

Chongan Zhang possesses a comprehensive skill set that supports his research in biomedical device development and surgical system innovation. He is proficient in the design and fabrication of medical devices, particularly high-performance endoscopes and surgical navigation platforms. His technical capabilities include embedded system programming, high-speed digital signal processing, sensor integration, and real-time data acquisition, all of which are critical for surgical applications. He is also skilled in system modeling, simulation, and validation, enabling him to iterate quickly and efficiently through the research and development cycle. His experience with CAD tools, hardware prototyping, and microcontroller-based system design strengthens his ability to create customized solutions for complex clinical challenges. Chongan is adept in image processing techniques used in endoscopy and navigation, and he frequently applies machine learning methods for optimizing navigation accuracy. Additionally, he has strong competencies in managing interdisciplinary research projects and collaborating with cross-functional teams, including surgeons, regulatory specialists, and industrial engineers. His skill in writing academic papers and securing intellectual property rights through patent applications also reflects his well-rounded research acumen. With a firm grasp of both software and hardware aspects, Chongan is well-equipped to innovate in the highly demanding field of medical device engineering.

Awards and Honors

Throughout his career, Chongan Zhang has earned recognition for his contributions to the biomedical engineering field, particularly in surgical technology innovation. While early in his career relative to more senior researchers, he has already secured a national invention patent, which highlights the originality and practical impact of his research. His participation in multiple government-funded and enterprise-sponsored research projects reflects institutional trust and professional esteem in his capabilities. Furthermore, his ten SCI and EI-indexed academic publications demonstrate that his work meets rigorous scientific standards and contributes to global knowledge in endoscopy and surgical navigation. Though not yet decorated with widely known individual research awards, his track record of successful project execution, research output, and innovation places him on a trajectory for future recognition at national and international levels. His involvement in interdisciplinary teams and industry partnerships has also brought praise for his ability to effectively bridge academic research with real-world application. As his portfolio continues to grow, he is likely to be a strong candidate for awards recognizing innovation, translational research, and medical technology advancement. His achievements to date serve as a foundation for even greater impact and recognition in the biomedical and engineering communities.

Conclusion

Chongan Zhang is a highly competent and innovative researcher whose work in biomedical engineering—especially in the development of surgical navigation systems and endoscopic technologies—demonstrates both depth and practical relevance. With nearly a decade of experience and active involvement in multi-tiered research projects, he exemplifies the qualities of a forward-thinking biomedical engineer. His research is driven by the need for high-precision, minimally invasive surgical tools that can transform clinical practice and improve patient outcomes. He combines strong technical skills with a clear vision for translational research, evidenced by his publications, patent, and collaborative project roles. While still building an international reputation, his consistent academic contributions and technical innovations already place him among the promising researchers in his field. His ability to work across disciplines and his focus on both hardware and software elements of surgical systems make him uniquely equipped to contribute to the future of intelligent surgical environments. With continued support and expanded visibility, he has the potential to become a leading figure in biomedical device innovation. Based on his experience, output, and innovation potential, he is a worthy nominee for the Best Researcher Award and an asset to the global biomedical research community.

Publications Top Notes

📘 Registration, Path Planning and Shape Reconstruction for Soft Tools in Robot-Assisted Intraluminal Procedures: A Review

  • Authors: Chongan Zhang, Xiaoyue Liu, Zuoming Fu, Guoqing Ding, Liping Qin, Peng Wang, Hong Zhang, Xuesong Ye

  • Publication Year: 2025

Alireza Akoushideh | Computer Science | Best Researcher Award

Assist. Prof. Dr. Alireza Akoushideh | Computer Science | Best Researcher Award

Electrical and Computer Department from Iran’s National University of Skill, Iran

Dr. Alireza Akoushideh is an Assistant Professor in Electronics Engineering with a specialization in image processing, parallel processing, and microcontroller-based systems. With over two decades of experience in academia and research, he has made significant contributions to digital electronics, focusing on industrial applications. His expertise extends to supervising research projects, authoring academic books, and securing multiple patents. Dr. Akoushideh has been an active participant in national and international collaborations, including a visiting research position at the University of Twente in the Netherlands and participation in the Erasmus+ program in Romania. In addition to his academic contributions, he has played a vital role in fostering technological innovations as the former manager of the Growth Centre at Guilan Science and Technology Park. His work emphasizes bridging the gap between academia and industry, particularly in the development of applied research projects and commercialization of new technologies. Recognized for his research excellence, he has received multiple awards, including the Best Researcher title at Guilan Technical and Vocational University. With a strong background in electronics and computer engineering, Dr. Akoushideh continues to contribute to advancements in artificial intelligence, IoT, and digital systems, making him a distinguished researcher in his field.

Professional Profile

Education

Dr. Akoushideh has a strong academic foundation in electrical and electronics engineering. He earned his Ph.D. in Electrical Engineering with a specialization in Electronics from Shahid Beheshti University, where his research focused on developing noise-resistant feature extraction operators for texture classification. His doctoral work contributed significantly to the fields of image processing and pattern recognition. Prior to that, he completed his Master’s degree at Amirkabir University of Technology (Tehran Polytechnic), specializing in electronics. His master’s thesis revolved around designing a pacemaker system based on the detection of cardiac arrests, demonstrating his early interest in biomedical applications of electronics. Dr. Akoushideh obtained his Bachelor’s degree from the University of Guilan, where he specialized in electronics engineering. His undergraduate research involved the development of a computer-based microcontroller trainer, highlighting his inclination towards microcontroller-based system design. Throughout his academic journey, he has consistently focused on applying electronics engineering principles to real-world challenges, which is evident in his later research projects and technological innovations. His education, spanning three prestigious Iranian institutions, has provided him with the necessary expertise to excel in both theoretical and applied aspects of electronics, further enriching his contributions to academia, research, and industry.

Professional Experience

Dr. Akoushideh has had an extensive career in academia, research, and industry. He is currently an Assistant Professor at the Technical and Vocational University in Iran, where he teaches courses in image processing, computer architecture, microcontrollers, and digital systems. His role extends beyond teaching, as he actively supervises undergraduate and graduate research projects, guiding students in developing innovative solutions for industrial and technological challenges. He has also served as a visiting researcher at the University of Twente in the Netherlands, where he collaborated on biometrics and pattern recognition research. Additionally, he participated in the Erasmus+ program at Pitesti University in Romania, contributing to international discussions on vocational education and training. Dr. Akoushideh has held managerial roles, including serving as the Growth Centre Manager at Guilan Science and Technology Park, where he played a key role in supporting technology startups and commercializing academic research. His industry experience includes co-founding Rayaneh Gostar Moein Co., where he worked on network design, industrial automation, and electronic content production. His diverse professional background reflects his ability to integrate academic research with industrial applications, making significant contributions to both education and technology-driven initiatives.

Research Interests

Dr. Akoushideh’s research interests lie in the intersection of digital electronics, image processing, artificial intelligence, and microcontroller-based systems. His work primarily focuses on developing advanced image processing techniques for applications such as biometrics, video surveillance, and medical diagnostics. He has also contributed to research in pattern recognition, deep learning, and IoT-based automation systems. His interest in parallel processing has led him to explore hardware acceleration techniques for computationally intensive tasks, improving the efficiency of embedded systems. In addition to theoretical advancements, Dr. Akoushideh is deeply involved in applied research, particularly in developing smart electronic devices and automation systems for industrial and consumer applications. His projects include intelligent power management systems, real-time video analytics, and embedded system design for IoT applications. He is also keen on integrating artificial intelligence into embedded systems, exploring new methods for enhancing efficiency and performance in real-time processing environments. With a strong background in both academic and practical research, his work contributes to the advancement of smart technologies, automation, and digital signal processing, positioning him as a leading researcher in electronics and computer engineering.

Research Skills

Dr. Akoushideh possesses a diverse range of research skills spanning hardware and software domains. He has expertise in digital image processing, machine learning, and deep learning techniques, applying them to areas such as biometrics, video analysis, and industrial automation. His programming proficiency includes MATLAB, Python, C++, and hardware description languages like VHDL, allowing him to develop and implement complex algorithms for embedded systems. His hands-on experience with microcontrollers such as AVR, ARM, and PIC enables him to design and prototype advanced electronic devices. Additionally, he is skilled in PCB design using Altium Designer and FPGA-based system development using Xilinx ISE and Synopsys tools. His research capabilities extend to IoT and smart systems, where he has worked on projects involving sensor networks, remote monitoring, and intelligent control systems. Dr. Akoushideh is also experienced in conducting experimental research, statistical data analysis, and scientific writing, which are essential for publishing in high-impact journals. His interdisciplinary approach, combining hardware and software expertise, makes him highly proficient in designing, developing, and optimizing electronic and computational systems for various applications.

Awards and Honors

Dr. Akoushideh has been recognized multiple times for his contributions to research and technology. He was awarded the Best Researcher title at Guilan Technical and Vocational University in 2022 and previously in 2018 and 2019. In 2021, he received the first award at the Technical and Vocational University of Iran, a national-level recognition of his excellence in research and academia. He was also acknowledged by the Guilan Science and Technology Park for his contributions as an innovator and technologist, winning awards such as “Encouraging Thinkers, Technologists, and Innovators” in 2019. Additionally, he won a provincial award in the Young Idea Supporters category the same year. His entrepreneurial spirit was recognized in 2007 when he was named the Best Entrepreneur in Information Technology by the Ministry of Labor and Social Affairs. His academic achievements include ranking second in his graduating class in electronic engineering at Guilan University in 1997. These awards highlight his dedication to advancing research, education, and innovation, further solidifying his reputation as a leading researcher in his field.

Conclusion

Dr. Alireza Akoushideh is a distinguished researcher with extensive expertise in electronics engineering, particularly in image processing, embedded systems, and IoT applications. His academic journey, spanning Iran’s top universities, has provided him with a strong foundation in both theoretical and applied research. His professional experience as a university professor, visiting researcher, and technology leader has allowed him to make significant contributions to academia and industry. With numerous research projects, patents, and international collaborations, he has established himself as a key figure in his field. His research interests in artificial intelligence, parallel processing, and industrial automation align with current technological advancements, making his work highly relevant. His technical skills in programming, hardware design, and system optimization further enhance his ability to develop innovative solutions. Recognized with multiple awards for research excellence, teaching, and entrepreneurship, he has consistently demonstrated his commitment to knowledge creation and dissemination. Dr. Akoushideh’s career reflects a balance between academic research and practical applications, positioning him as a thought leader in digital electronics and embedded systems. His contributions continue to drive technological innovation, benefiting both academia and industry.

Publications Top Notes

  • Title: Motion-based vehicle speed measurement for intelligent transportation systems
    Authors: A. Tourani, A. Shahbahrami, A. Akoushideh, S. Khazaee, C.Y. Suen
    Year: 2019
    Citations: 33

  • Title: A robust vehicle detection approach based on faster R-CNN algorithm
    Authors: A. Tourani, S. Soroori, A. Shahbahrami, S. Khazaee, A. Akoushideh
    Year: 2019
    Citations: 25

  • Title: Facial expression recognition using a combination of enhanced local binary pattern and pyramid histogram of oriented gradients features extraction
    Authors: M. Sharifnejad, A. Shahbahrami, A. Akoushideh, R.Z. Hassanpour
    Year: 2020
    Citations: 19

  • Title: Iranis: A large-scale dataset of Iranian vehicles license plate characters
    Authors: A. Tourani, S. Soroori, A. Shahbahrami, A. Akoushideh
    Year: 2021
    Citations: 16

  • Title: Iranian license plate recognition using deep learning
    Authors: A.R. Rashtehroudi, A. Shahbahrami, A. Akoushideh
    Year: 2020
    Citations: 15

  • Title: High performance implementation of texture features extraction algorithms using FPGA architecture
    Authors: A.R. Akoushideh, A. Shahbahrami, B.M.N. Maybodi
    Year: 2014
    Citations: 13

  • Title: Copy-move forgery detection using convolutional neural network and K-mean clustering
    Authors: A. Pourkashani, A. Shahbahrami, A. Akoushideh
    Year: 2021
    Citations: 12

  • Title: Accelerating texture features extraction algorithms using FPGA architecture
    Authors: A.R. Akoushideh, A. Shahbahrami
    Year: 2010
    Citations: 12

  • Title: Parallel Implementation of a Video-based Vehicle Speed Measurement System for Municipal Roadways
    Authors: A.J. Afshany, A. Tourani, A. Shahbahrami, S. Khazaee, A. Akoushideh
    Year: 2019
    Citations: 10

  • Title: Challenges of Video-Based Vehicle Detection and Tracking in Intelligent Transportation Systems
    Authors: A. Tourani, A. Shahbahrami, A. Akoushideh
    Year: 2017
    Citations: 9

 

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