Kah Ong Michael Goh | Computer Science | Best Researcher Award

Assist. Prof. Dr. Kah Ong Michael Goh | Computer Science | Best Researcher Award

Associate Professor from Multimedia University | Malaysia

Assoc. Prof. Ts. Dr. Goh Kah Ong Michael is a prominent academician and innovator in the field of Artificial Intelligence, particularly known for his contributions to biometrics, computer vision, image processing, and smart city systems. He is currently serving as an Associate Professor at the Faculty of Information Science and Technology (FIST), Multimedia University (MMU), Malaysia. His professional journey spans over two decades, beginning as a tutor and progressively advancing to senior academic roles, including a tenure as Deputy Dean for Student Affairs and Alumni. Dr. Goh’s work focuses on practical, high-impact research that integrates AI into real-world applications such as traffic management, intelligent authentication, and urban system automation. A hands-on technologist, he has built strong industry ties and led collaborative research projects involving government and private sectors. His accomplishments include numerous international awards and publications, reflecting his ability to merge theoretical depth with applied innovation. Dr. Goh’s contributions extend beyond academia through leadership roles, student mentoring, and his involvement in technology exhibitions and innovation showcases. With an ever-evolving research agenda, he continues to be a valuable contributor to Malaysia’s technological advancement and is a role model for aspiring researchers in AI and computer science.

Professional Profile

Scopus Profile | ORCID Profile | Google Scholar

Education

Dr. Michael Goh pursued all his higher education at Multimedia University (MMU), Malaysia, reflecting a strong and continuous academic association with the institution. He earned his Bachelor of Information Technology (Hons.), majoring in Software Engineering. This undergraduate foundation in software development provided him with a firm grounding in computational thinking and programming. He then obtained his Master of Science in Information Technology by Research, where he began to delve into research-oriented activities, focusing on emerging areas in digital systems and human-computer interaction. His academic progression culminated in the completion of his Doctor of Philosophy (Ph.D.) in Information Technology by Research. His doctoral work emphasized advanced topics in biometrics and contactless identity recognition, a theme that would continue to define his professional research identity. Throughout his academic journey, Dr. Goh has demonstrated exceptional scholarly dedication and subject mastery, which laid the groundwork for his teaching, supervision, and innovative research contributions at MMU. His educational background, centered on a research-intensive model, reflects the synthesis of academic theory and practical innovation that characterizes his work today.

Experience

Assoc. Prof. Dr. Goh Kah Ong Michael has a well-established professional history with Multimedia University, Malaysia, spanning over two decades. He began his career as a Tutor at the Faculty of Information Science & Technology (FIST). He was appointed as a Lecturer and elevated to Senior Lecturer. He served as Deputy Dean of Student Affairs and Alumni, where he provided strategic leadership in academic administration and student engagement. He also had an industrial attachment with Heathmetrics Sdn Bhd, fostering industry-academic collaboration and applying academic research to practical applications. This rich blend of academic and industry experience has honed his capabilities in academic governance, curriculum development, student mentorship, and real-world technology deployment. His ongoing role as Associate Professor continues to leverage his expertise in AI, biometrics, and software development. Through his involvement in university committees, innovation competitions, and cross-institutional collaboration, Dr. Goh demonstrates a commitment to excellence in teaching, research, and societal impact, making him a vital contributor to both MMU and Malaysia’s wider research ecosystem.

Research Interest

Dr. Goh’s research interests encompass a wide spectrum of areas within Artificial Intelligence and digital systems engineering. A significant portion of his work is dedicated to contactless biometric technologies, especially those using palm vein, palm print, and finger vein recognition. These technologies are integral to secure authentication systems and form the core of his early and ongoing research. He has also extensively explored video analytics, pattern recognition, image processing, and data classification for security, healthcare, and smart city applications. One of his signature projects, the “Smart Traffic Impact Assessment System”, represents a major advancement in urban AI, combining real-time data analysis with predictive modeling. Another domain of interest is gait recognition and spatiotemporal feature extraction, applied to age-based classification systems using AI algorithms. His interdisciplinary approach blends software engineering with signal processing and machine learning, leading to innovative tools with societal benefits. Additionally, he is actively engaged in research around reinforcement learning for dynamic pricing systems, integrating AI with economics. Dr. Goh’s projects reflect a strong application-driven research philosophy, pushing boundaries in how AI can be embedded into everyday environments for efficiency, safety, and sustainability.

Research Skills

Dr. Goh possesses a diverse and advanced set of research skills that have been instrumental in developing intelligent digital solutions. His core technical proficiencies include AI modeling, deep learning, video analytics, and multimodal data fusion, particularly in biometric systems. He is highly skilled in software and application development, with extensive experience in developing both academic prototypes and deployable commercial systems. His expertise also extends to database design and management, essential for handling large-scale biometric and visual data. He has a strong command over object recognition and pattern classification techniques using AI and machine learning frameworks. Dr. Goh is also experienced in reinforcement learning algorithms, used in his dynamic pricing and smart city projects. On the academic side, he is adept at writing research proposals, publishing in high-impact journals, and presenting findings at international conferences. His collaborative skills are evidenced by successful multi-author book chapters and interdisciplinary project leadership. Moreover, he excels in mentoring postgraduate students and coordinating innovation competitions. With this unique combination of programming, analytical, leadership, and project management skills, Dr. Goh consistently delivers impactful, high-quality research.

Awards and Honors

Dr. Goh has received numerous awards and recognitions at national and international levels, affirming his excellence in research and innovation. Most notably, he was awarded the ITEX SPECIAL MINDS Thematic Award 2024 and a Gold Medal for his “Smart Traffic Impact Assessment System” at the International Invention, Innovation, Technology Exhibition (ITEX). He also earned multiple accolades for “CloudPark – The Smart City Parking Solution,” including gold medals and top placements in PROCOM and Infineon competitions. His consistent success in innovation is further illustrated  for biometric systems, video puzzle learning tools, and intelligent scanning devices. he received the Outstanding Research Award from Multimedia University, a testament to his sustained scholarly contribution. Earlier recognitions, including the Silver Medal at ITEX for “Palm’n Go – A Touchless Biometric System”, mark the beginning of his decorated research journey. Dr. Goh’s portfolio of over 18 innovation awards highlights his commitment to creating solutions that are both technically robust and socially impactful. These accolades validate his role as a thought leader in biometric AI and smart systems research.

Publication Top Notes

  • “An automated palmprint recognition system”, Image and Vision Computing, 2005 – Cited 396.

  • “PalmHashing: a novel approach for cancelable biometrics”, Information Processing Letters, 2005 – Cited 255.

  • “Touch-less palm print biometrics: Novel design and implementation”, Image and Vision Computing, 2008 – Cited 245.

  • “Facial expression recognition using a hybrid CNN–SIFT aggregator”, International Workshop on Multi-disciplinary Trends in Artificial Intelligence, 2017 – Cited 198.

  • “Palmprint recognition with PCA and ICA”, Proc. Image and Vision Computing New Zealand, 2003 – Cited 163.

Conclusion

Assoc. Prof. Ts. Dr. Goh Kah Ong Michael stands as a shining example of how academic rigor, technological innovation, and community engagement can converge to make a lasting impact. His career is marked by groundbreaking contributions in AI-driven biometrics and smart city solutions, with practical outputs recognized at the highest levels through international innovation awards. As a mentor, educator, and innovator, he continues to shape the future of information technology and digital systems in Malaysia and beyond. His research not only addresses complex technical challenges but also offers scalable solutions that benefit society, including urban traffic management and secure identification technologies. With his impressive publication record, long-term academic service, and forward-looking research agenda, Dr. Goh is well-positioned to assume future leadership roles in research policy, international collaboration, and higher education development. His contributions exemplify excellence in research translation and academic leadership, making him a deserving candidate for international recognition and continued advancement in the global research landscape.

Elavarasi Kesavan | Computer Science | Best Industrial Research Award

Mrs. Elavarasi Kesavan | Computer Science | Best Industrial Research Award

Full-Stack QA Architect from Cognizant, India

Mrs. Elavarasi Kesavan is an accomplished Full Stack QA Architect with over 18 years of extensive experience in software quality assurance and automation testing. She has built a robust career with a strong specialization in Salesforce platforms, web-based applications, and various automated testing tools and methodologies. Her in-depth knowledge spans end-to-end software testing processes, mobile and web service testing, ETL validation, and automation using industry-standard tools like Selenium WebDriver, TestNG, Rest Assured, and Tricentis TOSCA. She is particularly proficient in test management, having implemented seamless integrations between tools like Jira and QTest. Elavarasi has consistently demonstrated excellence in designing testing frameworks, managing offshore teams, and ensuring quality compliance throughout the Software Development Life Cycle (SDLC). Additionally, she is well-versed in Agile, Waterfall, and V-Model methodologies and excels in accessibility testing using tools like JAWS Reader. She brings technical expertise in Java, JavaScript, and Ruby to her QA automation efforts. Through her leadership roles at Cognizant and other firms, she has led teams to deliver high-quality software solutions with a focus on automation, innovation, and efficiency. Her strong communication and client engagement skills have further enhanced her value in the industrial and research sectors.

Professional Profile

Education

Mrs. Elavarasi Kesavan holds a Bachelor of Technology (B.Tech) degree in Information Technology from Anjali Ammal Mahalingam Engineering College, affiliated with Anna University, which she completed in 2006. To complement her technical foundation, she pursued and successfully earned a Master of Business Administration (MBA) in General Management from SRM Easwari Engineering College, Anna University in 2011. Her academic journey reflects a unique blend of technical proficiency and managerial acumen, which has significantly contributed to her effectiveness in leading QA initiatives and managing cross-functional teams. Her academic training in Information Technology provided a solid grounding in programming languages, databases, and web technologies, while her MBA developed her capabilities in project management, strategic planning, and team leadership. This combination has been instrumental in her ability to bridge technical expertise with business-oriented decision-making. Additionally, her continuous pursuit of professional development through various certifications in AI testing, cloud technologies, and test automation tools demonstrates her commitment to lifelong learning and staying ahead in the rapidly evolving tech industry. Her education has laid the foundation for her successful career and her capacity to contribute meaningfully to industrial research and QA architecture.

Professional Experience

Mrs. Elavarasi Kesavan brings over 18 years of progressive experience in the IT industry, primarily focusing on software quality assurance, automation, and test architecture. She currently serves as an Engineer Manager and Full Stack QA Architect at Cognizant, a role she has held since November 2022. Prior to this, she worked at Concentrix as a Technology Lead for Full Stack QA Engineering from October 2021 to November 2022. Her earlier tenure at Cognizant (2010–2021) as a Senior Associate included responsibilities such as developing and maintaining automated test frameworks, integrating QA tools with defect tracking systems, and leading cross-functional teams. She began her professional journey as a Software Developer at IBM, followed by a stint at Vayana India Pvt Ltd. Elavarasi’s hands-on experience with a variety of test management and automation tools such as Selenium, TOSCA, Postman, Jira, and QTest highlights her adaptability and technical depth. She has effectively driven the QA strategy in complex project environments, aligning quality goals with business objectives. She is recognized for her innovative solutions, strong client interactions, and mentoring capabilities. Her ability to handle diverse tools, technologies, and methodologies has cemented her as a valuable leader in the QA domain across multiple industries.

Research Interests

Mrs. Elavarasi Kesavan’s research interests lie at the intersection of software quality assurance, automation engineering, AI-driven testing, and compliance-focused application validation. She is particularly focused on developing frameworks and methodologies for efficient and scalable automation testing of web, mobile, and enterprise applications, including CRM platforms like Salesforce. Her work emphasizes scriptless automation using tools like Tricentis TOSCA and integration of AI-based testing approaches to enhance test coverage, reliability, and efficiency. She is keenly interested in security and compliance testing, aligning quality assurance practices with international standards such as GDPR, HIPAA, and PCI-DSS. Elavarasi’s exploration of testing tools that support DevOps and Agile frameworks demonstrates her commitment to continuous delivery and integration practices. Moreover, she is enthusiastic about advancing quality engineering through research on defect prediction models, test data management, and automation in cloud-native environments. Her engagement in multidisciplinary forums and conferences reveals a strong inclination toward applied industrial research. She aspires to contribute to the future of QA through intelligent automation frameworks, optimization of test cycles using AI, and expanding automation in AI/ML-based systems. These interests align with the goals of the Best Industrial Research Award by showcasing innovation and impact on real-world software engineering challenges.

Research Skills

Mrs. Elavarasi Kesavan is equipped with a comprehensive set of research and technical skills that support her contributions to industrial software testing and automation research. She is adept in using a wide array of automation tools such as Selenium WebDriver, Tricentis TOSCA, Postman, and SOAP UI. Her proficiency in developing and implementing test strategies spans data-driven and behavior-driven frameworks, including TestNG, Cucumber, Jasmine, and Rest Assured. Elavarasi has advanced capabilities in API testing, cross-browser testing, accessibility validation (JAWS), and end-to-end test management using tools like Jira and QTest. Her programming expertise includes Java, JavaScript, and Ruby, which she employs for custom test scripts and automation logic. She is skilled in web service validation, database verification (SQL, Oracle, MySQL), and cloud environment testing, complemented by hands-on experience in CI/CD tools like Jenkins and Maven. Her analytical and documentation capabilities are evident in her creation of test plans, traceability matrices, and compliance validation reports. In AI testing, she applies certified methodologies for testing machine learning models and intelligent systems. Her research-oriented approach, combined with practical application and tool proficiency, positions her as a technically strong candidate capable of innovating in industrial software quality research.

Awards and Honors

Mrs. Elavarasi Kesavan has received numerous prestigious awards and honors that reflect her excellence in technology innovation, industrial research, and leadership in software quality assurance. Notably, she was the recipient of the Distinguished Technology Award at the Dubai Dynamic Ultimate Business & Academic Iconic Awards in 2025. Her innovative contributions to IoT were recognized through the Best Patent Award for the design and development of an IoT-based multifunction agriculture robot, presented by the Scientific International Publishing House. Elavarasi also received the Best Paper Award for her work on cloud computing in Industry 4.0 at the UAE International Conference on Multidisciplinary Research and Innovation (ICMRI-2025). Additionally, she was honored with the Best Woman Researcher Award at the International Conference on Computational Science, Engineering & Technology (ICCSET-2025). Her editorial contributions were acknowledged with a Certificate of Excellence for her role as Chief Editor in Contemporary Research in Engineering, Management, and Science. Furthermore, she was recognized with a Digital Excellence Award by the CAPE Forum and a Certificate of Emerging Leader in Technology Innovation by RCS International Awards. These accolades not only highlight her technical prowess but also her impact on industrial innovation and collaborative research.

Conclusion

Mrs. Elavarasi Kesavan presents a strong and compelling case for the Best Industrial Research Award. With nearly two decades of experience in software quality assurance and a consistent record of innovation in test automation and QA strategy, she stands out as a leader who bridges technical execution with strategic foresight. Her deep expertise in automation tools, QA methodologies, compliance testing, and AI testing frameworks positions her at the forefront of industrial QA research. The recognition she has received through multiple awards and her contributions in patent development and conference presentations further reinforce her role as a pioneering professional in the field. Elavarasi’s research-oriented mindset, hands-on technical proficiency, and proven ability to lead teams and deliver enterprise-grade solutions make her a strong candidate whose work aligns with the goals of industrial research excellence. While she could benefit from further academic publications in peer-reviewed journals to bolster her academic research credentials, her real-world impact, technical acumen, and award-winning innovations clearly demonstrate her merit. Overall, Mrs. Elavarasi Kesavan exemplifies the ideal qualities of an industrial researcher whose work drives both technological advancement and practical value in the software engineering domain.

Publication Top Notes

  • Title: The Impact of Cloud Computing on Software Development: A Review
    Author: E. Kesavan
    Journal: International Journal of Innovations in Science, Engineering and Management
    Year: 2025
    Citations: 3

  • Title: AI Adapt Digital Learning in Education
    Author: E. Kesavan
    Conference: International Conference Proceeding on Innovation and Sustainable Strategies
    Year: 2025

  • Title: Explore How Digital Infrastructure Has Shaped Startup Growth
    Author: E. Kesavan
    Conference: International Conference on the Role of Innovation Policies
    Year: 2025

  • Title: Artificial Intelligence in Commerce: How Businesses Can Leverage Artificial Intelligence to Gain a Competitive Edge in the Global Marketplace
    Author: E. Kesavan
    Publication: Thiagarajar College of Preceptors, Edu Spectra
    Year: 2025

  • Title: The Evolution of Software Design Patterns: An In-Depth Review
    Author: E. Kesavan
    Journal: International Journal of Innovations in Science, Engineering and Management
    Year: 2025

  • Title: Impact of Artificial Intelligence on Software Development Processes
    Authors: SMSA Cuddapah Anitha, Nirmal Kumar Gupta, Balaji Chintala, Daniel Pilli, E. Kesavan
    Journal: Journal of Information Systems Engineering and Management
    Volume/Issue: 10 (25s), Pages 431–437
    Year: 2025

  • Title: Information and Communication Technology Development in Emerging Countries
    Author: E. Kesavan
    Journal: Journal on Electronic and Automation Engineering
    Volume/Issue: 3 (1), Pages 60–68
    Year: 2024

  • Title: Comprehensive Evaluation of Electric Motorcycle Models: A Data-Driven Analysis
    Author: E. Kesavan
    Journal: REST Journal on Data Analytics and Artificial Intelligence
    Year: 2023
    ISSN: 2583-… (incomplete in original text)

  • Title: Assessing Laptop Performance: A Comprehensive Evaluation and Analysis
    Author: E. Kesavan
    Journal: Recent Trends in Management and Commerce
    Volume: 4, Pages 175–185
    Year: 2023

Saurabh Kumar | Computer Science | Best Researcher Award

Mr. Saurabh Kumar | Computer Science | Best Researcher Award

Shri Ramswaroop Memorial University, India

Saurabh Kumar is a passionate and driven Computer Science Engineering student with a strong focus on Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP). With a deep interest in solving complex real-world challenges, Saurabh has worked extensively on AI-driven projects, including fine-tuning state-of-the-art models, developing computer vision applications, and enhancing NLP systems. His expertise spans multiple domains, including deep learning, speech synthesis, and autonomous systems. Saurabh actively contributes to the tech community through open-source projects and research-driven initiatives. His commitment to continuous learning, innovation, and collaboration sets him apart as a dedicated researcher in AI.

Professional Profile

Education

Saurabh Kumar is currently pursuing a degree in Computer Science Engineering, specializing in Artificial Intelligence and Machine Learning. Throughout his academic journey, he has developed a strong foundation in data science, deep learning, and cloud computing. His coursework includes advanced machine learning algorithms, computer vision, NLP, and big data analysis. In addition to academic learning, he has actively participated in AI-focused bootcamps, hackathons, and online certifications to enhance his technical knowledge. His commitment to education is evident through his consistent efforts to bridge theoretical knowledge with practical applications in AI-driven research.

Professional Experience

Saurabh has gained hands-on experience through various AI-based projects and internships. His work includes developing a Vehicle Classification Model using deep learning and computer vision, creating an advanced Text-to-Speech (TTS) model, and building multiple real-time computer vision applications. Additionally, he has experience working with cloud platforms like IBM Cloud and using tools such as SQL, Tableau, and Docker for AI deployment. His ability to work with cutting-edge AI models and optimize them for real-world use cases highlights his technical acumen. Saurabh’s professional experience reflects a strong ability to innovate, research, and implement AI solutions effectively.

Research Interests

Saurabh Kumar’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, and Natural Language Processing. He is particularly passionate about Conversational AI, Reinforcement Learning, Explainable AI, and Generative AI. His work focuses on optimizing AI models for practical applications, enhancing NLP-based speech synthesis, and improving AI-driven automation. He is also interested in exploring AI ethics, fairness in machine learning, and the development of AI-driven assistive technologies. His continuous learning in AI research methodologies and practical deployment strategies showcases his commitment to pushing the boundaries of AI innovation.

Research Skills

Saurabh possesses a strong set of research skills, including data analysis, deep learning model optimization, and AI-driven problem-solving. He is proficient in Python, PyTorch, TensorFlow, OpenCV, and NLP frameworks such as Hugging Face. His expertise in AI extends to cloud computing, SQL-based data management, and deployment of machine learning models. He has hands-on experience with real-world AI challenges, including speech synthesis, computer vision applications, and text-based AI solutions. His ability to develop, fine-tune, and deploy AI models efficiently highlights his strong research-oriented approach.

Awards and Honors

Saurabh Kumar has been recognized for his contributions to AI and research. He has successfully completed the OpenCV Bootcamp, demonstrating expertise in Computer Vision and Deep Learning. His AI-driven projects have received recognition within the tech community, and his work in fine-tuning AI models has been acknowledged on various platforms. His commitment to advancing AI research is evident through his achievements in open-source contributions and AI development. These accolades showcase his dedication to continuous learning and impactful research in Artificial Intelligence.

Conclusion

Saurabh Kumar is a dedicated AI researcher and technology enthusiast committed to innovation, research, and problem-solving. His expertise in Artificial Intelligence, Machine Learning, and NLP, combined with his passion for AI-driven solutions, makes him a strong candidate for the Best Researcher Award. His extensive work in AI model development, contributions to open-source projects, and commitment to continuous learning set him apart as a future leader in AI research. By further expanding his research publications and collaborative efforts, he is well-positioned to make significant contributions to the field of AI.

Publications Top Notes

  1. Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
    Authors: T Maurya, S Kumar, M Rai, AK Saxena, N Goel, G Gupta
    Year: 2025

 

Qichuan Tian | Computer Science | Best Researcher Award

Prof. Dr. Qichuan Tian | Computer Science | Best Researcher Award

Prof. Dr. at  Beijing University of Civil Engineering and Architecture, China

Qichuan Tian, born in 1971, is a distinguished professor and technical expert specializing in artificial intelligence, pattern recognition, and computer vision. He holds a Ph.D. in Engineering from Northwestern Polytechnical University (2006) and currently serves as a professor and master’s supervisor at Beijing University of Civil Engineering and Architecture (BUCEA). As the Director of the Department of Artificial Intelligence at the School of Intelligent Science and Technology, he leads research in biometrics, human-computer interaction, and deep learning. He is a member of multiple prestigious organizations, including the National Information Technology Standardization Technical Committee and the Chinese Society of Biomedical Engineering. His career spans academia and industry, with significant contributions in developing national standards, publishing books, and mentoring graduate students. Tian has also played a key role in over 20 research projects funded by national and provincial foundations, solidifying his reputation as a thought leader in AI and computational sciences.

Professional Profile

Education

Qichuan Tian has an extensive academic background in engineering. He obtained his Bachelor of Engineering (1993) and Master of Engineering (1996) from Taiyuan University of Science and Technology. In 2006, he completed his Doctor of Engineering at Northwestern Polytechnical University, specializing in artificial intelligence and computer vision. His academic training laid a strong foundation for his later contributions to AI, biometrics, and deep learning. His studies focused on integrating computational intelligence into practical applications, a theme that continues to define his research and professional endeavors.

Professional Experience

Tian has a diverse career in academia and research. Since 2012, he has served as the Head of the Department of Artificial Intelligence at BUCEA, where he spearheads innovative AI programs. From 2009 to 2010, he was a Visiting Scholar at Auburn University, USA, gaining international exposure in computer science. Between 2006 and 2008, he conducted postdoctoral research at Tianjin University. Previously, he held various roles at Taiyuan University of Science and Technology (1993–2012), where he advanced from Assistant Professor to Associate Professor and later became the Chief Leader of Circuits and Systems. His leadership has been instrumental in shaping AI research and education in China.

Research Interests

Tian’s research interests focus on artificial intelligence, pattern recognition, image processing, and deep learning. He specializes in biometric recognition, computer vision, and human-computer natural interaction. His work extends to security authentication, big data analysis, and IoT-based embedded systems. Tian has published over 100 journal and conference papers, authored six books, and contributed significantly to national standards in AI applications. His interdisciplinary research bridges theoretical advancements with practical AI implementations, making substantial contributions to the field.

Research Skills

With expertise in artificial intelligence and computer vision, Tian possesses strong research skills in deep learning algorithms, biometric recognition systems, and real-time image processing. He has successfully led projects in autonomous driving, green building AI integration, and complex object detection. His experience includes handling large-scale datasets, implementing machine learning frameworks, and designing AI-driven applications. Additionally, he has obtained over 50 invention patents and software copyrights, showcasing his ability to translate theoretical research into impactful technological innovations.

Awards and Honors

Tian’s contributions to academia and AI research have earned him multiple accolades. In 2024, he was recognized among CNKI’s Highly Cited Scholars (Top 5). He received the First Prize for Teaching Achievements at BUCEA in 2021 and was honored for developing a National First-Class Blended Online and Offline Course in 2020. Additionally, he was awarded the Outstanding Master’s Thesis Advisor Award in 2012. His accolades highlight his commitment to education, research, and AI-driven innovations, reinforcing his influence in the field of intelligent science and technology.

Conclusion

Qichuan Tian is a prominent scholar and AI expert dedicated to advancing artificial intelligence and biometric research. His leadership in academia, combined with his extensive research portfolio, underscores his impact on technological advancements in pattern recognition, computer vision, and human-computer interaction. With a career spanning over two decades, Tian has played a pivotal role in shaping AI education, national standards, and industry collaborations. His legacy continues to influence emerging AI technologies and inspire the next generation of researchers in intelligent computing.

Publications Top Notes

  • Title: An improved framework for breast ultrasound image segmentation with multiple branches depth perception and layer compression residual module

    • Authors: K. Cui, Qichuan Tian, Haoji Wang, Chuan Ma
    • Year: 2025
  • Title: Mobile Robot Path Planning Algorithm Based on NSGA-II

    • Authors: Sitong Liu, Qichuan Tian, Chaolin Tang
    • Year: 2024
    • Citations: 1
  • Title: OcularSeg: Accurate and Efficient Multi-Modal Ocular Segmentation in Non-Constrained Scenarios

    • Authors: Yixin Zhang, Caiyong Wang, Haiqing Li, Qichuan Tian, Guangzhe Zhao
    • Year: 2024
  • Title: Convolutional Neural Network–Bidirectional Gated Recurrent Unit Facial Expression Recognition Method Fused with Attention Mechanism

    • Authors: Chaolin Tang, Dong Zhang, Qichuan Tian
    • Year: 2023
    • Citations: 4

 

 

 

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”
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