Supraja Ballari | Computer Science | Best Researcher Award

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Mrs. Supraja Ballari | Computer Science | Best Researcher Award

Assistant Professor from Guru Nanak Institutions Technical Campus, India

Smt. B. Supraja is an experienced academician and researcher in the field of Computer Science and Engineering. With over 15 years of teaching experience at various reputed technical institutions in India, she has consistently contributed to both pedagogy and applied research. Currently serving as an Assistant Professor at Guru Nanak Institutions Technical Campus, Telangana, she is also pursuing her Ph.D. in Computer Science from Dravidian University, Kuppam. Her academic journey is marked by a strong foundation in computer applications and engineering, with a focus on emerging areas such as machine learning, cybersecurity, blockchain, and data mining. She has authored several research papers in reputed journals and holds multiple patents reflecting her commitment to innovation. Her work spans interdisciplinary applications of computing in logistics, vehicular networks, and employee management systems. Known for her diligence and academic integrity, Smt. Supraja combines her teaching skills with active research, mentorship, and curriculum development. Her ability to blend theory with practical applications makes her a valuable asset in academia. Her academic contributions have positioned her as a researcher with great potential for national recognition, including eligibility for research excellence awards.

Professional Profile

Education

Smt. B. Supraja holds a rich academic background that lays the foundation for her current research pursuits. She is presently pursuing a Ph.D. in Computer Science from Dravidian University, Kuppam, with a focus on contemporary issues in cybersecurity, data analytics, and intelligent systems. She completed her M.Tech in Computer Science and Engineering from PBR Visvodaya Engineering College, Kavali (affiliated to JNTUA) between 2011 and 2014, where she deepened her technical knowledge in core computer engineering disciplines. Her postgraduate studies began with a Master of Computer Applications (M.C.A.) from Geethanjali College of PG Studies under Sri Venkateswara University, Nellore (2002–2005). Her academic credentials are well aligned with the technological demands of today’s dynamic research landscape. Her education spans foundational programming, software engineering principles, and advanced technologies, making her a capable researcher and instructor. Throughout her academic journey, she has remained focused on interdisciplinary applications of computer science in real-world contexts. Her continuous academic progression—culminating in her doctoral studies—underscores her lifelong commitment to education and research excellence.

Professional Experience

Smt. Supraja’s professional journey spans nearly two decades in the higher education sector, where she has served in various teaching capacities. She is currently employed as an Assistant Professor at Guru Nanak Institutions Technical Campus, Telangana (since February 2023), where she teaches undergraduate and postgraduate courses in Computer Science. Prior to this, she held the same role at Narayana Engineering College, Nellore from July 2021 to January 2023, and at Krishna Chaitanya Educational Institutions from December 2014 to July 2021, teaching a mix of B.Sc., BCA, and M.Sc. students. Her earlier roles included positions at S. Chaavan Institute of Science & Technology and S.V. Arts & Science College, Gudur, where she taught various computer science subjects to both undergraduate and postgraduate students. In each of these positions, she has contributed to academic instruction, student mentoring, and curriculum development. Her experience reflects a deep engagement with the academic process, ranging from foundational teaching to more research-oriented mentorship. This long-standing teaching career demonstrates not only her pedagogical strengths but also her dedication to shaping the next generation of computer scientists.

Research Interests

Smt. B. Supraja’s research interests span a wide range of cutting-edge domains in computer science. Her primary focus areas include machine learning, cybersecurity, blockchain applications, data mining and data warehousing, fog computing, and cloud-based control systems. Her work reflects a deep interest in the intersection of artificial intelligence with societal and industrial applications. She has conducted research on anomaly detection in software-defined networks, data sharing in vehicular social networks using blockchain, and logistics optimization through structural equation modeling. She also explores areas such as sentiment analysis using Naïve Bayes classifiers, encrypted control systems, and cyberattack prediction through machine learning techniques. These interests align closely with today’s technological priorities such as data protection, automation, and intelligent decision-making. Her work seeks to bridge the gap between academic research and industrial applicability. The diverse yet cohesive nature of her research interests indicates her adaptability and eagerness to explore interdisciplinary applications. These interests not only reflect technical competence but also her sensitivity to real-world challenges that require intelligent, scalable, and secure technological solutions.

Research Skills

Smt. B. Supraja brings a robust set of research skills honed through academic work, project collaborations, and innovation initiatives. She is proficient in programming languages such as Java, C, and C++, and has practical experience with databases like Oracle and MS Access, as well as web technologies like HTML, JavaScript, and XML. Her expertise includes operating within different development environments using tools like Eclipse and Editplus. These technical proficiencies support her capability in implementing machine learning models, simulation systems, and data analysis applications. She has successfully authored and co-authored peer-reviewed publications and book chapters, showing familiarity with scientific writing, research methodology, and collaborative scholarship. In addition, she has contributed to the innovation space through patent filings in areas such as employee churn prediction and cyberattack prevention systems using machine learning algorithms. Her ability to apply theoretical knowledge into practical systems design and her experience in real-world problem solving mark her as a capable and results-oriented researcher. Her academic and technological skills are further strengthened by her consistent teaching of core subjects, which reinforces her depth in fundamental computer science concepts.

Awards and Honors

While a formal list of awards and honors is not provided in her academic profile, Smt. B. Supraja’s achievements in publishing, patenting, and contributing to book chapters reflect strong professional recognition. Her patents—three of which are published between 2022 and 2024—indicate acknowledgment of her work’s novelty and utility in applied computer science. Her scholarly contributions to journals such as the Journal of Engineering Sciences and Design Engineering, alongside collaborative book chapters on contemporary issues like COVID-19’s digital impact, have been positively received in academic circles. These publications are indicative of her growing visibility in the research community. Furthermore, her inclusion in multidisciplinary anthologies and collaborations with senior academicians from diverse fields show a level of trust and professional respect. Although specific awards or titles are not yet documented, her research outputs and innovation track record position her as a strong candidate for future academic honors and distinctions. Her work is gaining momentum, and with further institutional and international engagement, she is well poised for formal recognition through research awards and academic fellowships.

Conclusion

In conclusion, Smt. B. Supraja is a dedicated academic professional and an emerging researcher in the field of computer science. Her profile reflects a balanced integration of long-standing teaching experience and active research engagement. She has demonstrated capability in producing impactful scholarly work through journal publications, book chapters, and patents. Her expertise spans across machine learning, blockchain, cloud systems, and cybersecurity—fields that are not only technologically significant but also socially relevant. While she is still progressing in her doctoral research, her current contributions are commendable and indicate strong future potential. Areas for growth include enhancing research impact through increased citation metrics, obtaining funded projects, and expanding global collaborations. However, the depth and diversity of her current academic efforts strongly support her candidacy for research awards. Smt. Supraja exemplifies the qualities of a modern researcher—technically skilled, pedagogically sound, and oriented towards practical applications. With continued dedication and strategic academic outreach, she is well-positioned to become a recognized contributor to India’s research and innovation landscape.

Publications Top Notes

  1. A vital neurodegenerative disorder detection using speech cues
    BS Jahnavi, BS Supraja, S Lalitha
    2020

  2. Simplified framework for diagnosis brain disease using functional connectivity
    T Swarnalatha, B Supraja, A Akula, R Alubady, K Saikumar, …
    2024

  3. DARL: Effectual deep adaptive reinforcement learning model enabled security and energy-efficient healthcare system in Internet of Things with the aid of modified manta ray
    B Supraja, V Kiran Kumar, N Krishna Kumar
    2025

  4. IoT based effective wearable healthcare monitoring system for remote areas
    S Tiwari, N Jain, N Devi, B Supraja, NT Chitra, A Sharma
    2024

  5. Securing IoT networks in healthcare for enhanced privacy in wearable patient monitoring devices
    V Tiwari, N Jharbade, P Chourasiya, B Supraja, PS Wani, R Maurya
    2024

  6. Machine learning-based prediction of cardiovascular diseases using Flask
    V Sagar Reddy, B Supraja, M Vamshi Kumar, C Krishna Chaitanya
    2023

  7. Real time complexities of research on machine learning algorithm: A descriptive research design
    GP Dr. N. Krishna Kumar, B. Supraja, B.S. Hemanth Kumar, U. Thirupalu
    2022

  8. IT employee job satisfaction survey during Covid-19
    GVMR Dr. N. Krishna Kumar, B. Supraja
    2022

  9. Covid-19 and digital era
    GVMR Dr. N. Krishna Kumar, B. Supraja
    2022

  10. Forwarding detection and identification anomaly in software defined network
    DNKK B. Supraja, A. Venkateswatlu
    2022

  11. Machine learning structural equation modeling algorithm on logistics and supply chain management
    UT B. Supraja, Dr. N. Krishna Kumar, B.S. Hemanth Kumar, B. Saranya, G …
    2022

  12. Sentiment analysis of customer feedback on restaurants using Naïve Bayes classifier
    DNKK A. Venkateswatlu, B. Supraja
    2021

  13. Design and implementation of fog-based encrypted control system in public clouds
    DNKK B. Supraja, A. Venkateswatlu
    2021

  14. Enhancing one to many data sharing using blockchain in vehicular social networks
    DNKK B. Supraja, A. Venkateswatlu
    2021

Seonae Hwangbo | Ultrasonic Manufacturing | Best Researcher Award

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Dr. Seonae Hwangbo | Ultrasonic Manufacturing | Best Researcher Award

CTO at FUST Lab, South Korea

Seonae Hwangbo is a prominent researcher and Chief Technology Officer at FUST Lab Co., Ltd., based in Daejeon, South Korea. With over a decade of experience in focused ultrasound technology, Hwangbo has made significant strides in the dispersion and emulsification of nanoparticles. His work, initially conducted at the Korea Research Institute of Standards and Science (KRISS), focuses on developing ultrasonic devices and advancing surfactant-free nanodispersion and nanoemulsification processes. Hwangbo’s contributions extend beyond theoretical research, as he successfully transitioned technology from KRISS to FUST Lab, highlighting his expertise in practical applications. His innovative approach in exploring various application areas for focused ultrasound technology underscores his impact in the field. To further strengthen his profile, Hwangbo could enhance his publication record, engage in collaborative research, and seek additional grants. His accomplishments and leadership in advancing nanotechnology make him a strong candidate for the Research for Best Researcher Award.

Profile

Education

Seonae Hwangbo has an extensive educational background that supports his expertise in focused ultrasound technology and nanomaterial development. He completed his undergraduate studies in Engineering Physics, where he developed a strong foundation in fundamental scientific principles and experimental techniques. He then pursued a Master’s degree in Applied Physics, focusing on advanced ultrasound technologies and their applications. His graduate studies provided him with a deep understanding of ultrasonic device development and nano-dispersion processes. Building on this solid academic base, Hwangbo earned his Ph.D. in Engineering, specializing in focused ultrasound technology. His doctoral research focused on the optimization of ultrasound equipment and processes for nanoparticle dispersion and emulsification. This advanced education equipped him with both theoretical knowledge and practical skills, enabling him to lead innovative research and development projects at the Korea Research Institute of Standards and Science (KRISS) and FUST Lab Co., Ltd.

Professional Experience

Seonae Hwangbo boasts over a decade of expertise in focused ultrasound technology. He initially honed his skills at the Korea Research Institute of Standards and Science (KRISS), where he conducted pioneering research on the dispersion and emulsification of nanoparticles using focused ultrasound. His work significantly advanced the field of nanomaterials and ultrasonic devices. Currently, as the Chief Technology Officer at Focused UltraSonic Tech. Lab. (FUST Lab) in Daejeon, South Korea, Hwangbo leads the development and optimization of focused ultrasound equipment. He is instrumental in creating processes for nano-dispersion and nano-emulsification, focusing on surfactant-free methods. His role at FUST Lab, a company established through technology transfer from KRISS, highlights his ability to bridge research and practical applications, driving innovation and exploring diverse application areas for his technology.

Research Interest

Seonae Hwangbo’s research interests are centered on the development and application of focused ultrasound technology. With over a decade of experience, Hwangbo has specialized in the dispersion and emulsification of nanoparticles using focused ultrasound, a field that holds significant promise for advancing nanomaterials and their applications. His work primarily involves ultrasonic device development, where he explores innovative methods for creating surfactant-free nanodispersion and nano-emulsification processes. This research addresses critical challenges in material science by simplifying the dispersion processes and enhancing the efficiency of nano-material synthesis. Additionally, Hwangbo is deeply invested in optimizing focused ultrasound equipment and developing new processes that expand the practical applications of his research. His focus on creating scalable and efficient techniques for nanomaterials underscores his commitment to bridging the gap between theoretical research and real-world technological advancements.

Research Skills

Seonae Hwangbo possesses exceptional research skills, particularly in the domain of focused ultrasound technology. His expertise spans over a decade, encompassing the development and optimization of ultrasonic devices, and pioneering surfactant-free nano-dispersion and nano-emulsification techniques. Hwangbo’s ability to translate complex research into practical applications is evidenced by his role as Chief Technology Officer at FUST Lab Co., Ltd., where he leads the advancement of focused ultrasound equipment and processes. His skills in nanoparticle dispersion and emulsification reflect a deep understanding of both theoretical principles and their practical implementations. Hwangbo’s research also demonstrates proficiency in exploring various application areas for nanomaterials, underscoring his capability to address diverse scientific and industrial challenges. His technical acumen, coupled with his experience in technology transfer and process development, showcases a robust set of research skills that contribute significantly to his field.

Award and Recognition

Seonae Hwangbo is a distinguished researcher recognized for his groundbreaking work in focused ultrasound technology and nanomaterial development. With over a decade of experience at the Korea Research Institute of Standards and Science (KRISS) and as Chief Technology Officer at FUST Lab Co., Ltd., Hwangbo has made significant strides in the fields of ultrasonic device development, surfactant-free nanodispersion, and nanoemulsification. His innovative research has led to the successful transfer of technology from a prominent research institute to a leading industry lab, showcasing his expertise and leadership. Hwangbo’s contributions have been pivotal in advancing practical applications of nanotechnology, earning him accolades within the scientific community. His work continues to influence and shape advancements in ultrasound technology and nanomaterial processes, affirming his role as a leading figure in his field.

Conclusion

Seonae Hwangbo is a strong candidate for the Research for Best Researcher Award due to his extensive experience, innovative research, and leadership in technology transfer. His work in focused ultrasound technology and nanoparticle dispersion represents a significant contribution to his field. To further enhance his candidacy, focusing on increasing his publication record, engaging in collaborative projects, and strengthening grant acquisition skills would be beneficial. Overall, Hwangbo’s achievements

Publications Top Notes

  1. Research on Optimizing Ultrasonic Frequencies for Efficient Single-Walled Carbon Nanotube Dispersion in Water Using a Focused Ultrasonic System
    • Authors: Kim, S.Y., Hwangbo, M., Hwangbo, S., Jeong, Y.G.
    • Year: 2024
    • Journal: Diamond and Related Materials
    • Volume: 147
    • Article Number: 111284
  2. Novel Ultrasonic Technology for Advanced Oxidation Processes of Water Treatment
    • Authors: Kim, S.Y., Kim, I.Y., Park, S.-H., Hwangbo, M., Hwangbo, S.
    • Year: 2024
    • Journal: RSC Advances
    • Volume: 14(17)
    • Pages: 11939–11948

 

Weile Kong | Power system | Best Researcher Award

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Mr. Weile Kong | Power system | Best Researcher Award

Student, Anhui University of Science and Technology, China

Weile Kong, a Master’s student at Anhui University of Science and Technology, is a promising researcher specializing in electrical engineering and automation. He has demonstrated strong academic performance, evidenced by multiple scholarships and awards, including the First Class Academic Scholarship and the Internet+ Second Prize. His research contributions are notable, with several high-impact SCI papers and patents under review. Kong’s work focuses on energy systems and optimization algorithms, supported by grants from the Energy Internet Joint Fund and the National Natural Science Foundations of China. His personal attributes—responsibility, strong communication skills, and perseverance—enhance his research potential. To further strengthen his profile, Kong could benefit from expanding his research scope, gaining international recognition, and taking on leadership roles in the academic community. Overall, his achievements reflect a strong foundation for continued success and recognition in the field of electrical engineering.

Profile

Education

Weile Kong’s educational journey showcases a robust foundation in engineering and a commitment to academic excellence. He earned his Bachelor of Engineering in Automation from Anhui University of Science and Technology in June 2022, where he developed a solid understanding of electrical engineering principles and automation technologies. Currently, he is pursuing a Master’s degree in Electrical Engineering at the same institution, having commenced his studies in September 2022. This advanced education has allowed him to delve deeper into specialized areas such as electric load analysis, integrated energy system optimization, and intelligent optimization algorithms. Throughout his academic career, Kong has been recognized for his outstanding performance, receiving both the First Class and Third Class Academic Scholarships. His ongoing research and coursework reflect a strong focus on innovative solutions within energy systems and optimization, underscoring his dedication to advancing the field of electrical engineering.

Professional Experience

Weile Kong, currently pursuing a Master’s degree in Electrical Engineering at Anhui University of Science and Technology, has accumulated significant professional experience in the field of energy systems and optimization. His academic journey began with a Bachelor’s degree in Automation, where he laid a solid foundation in electrical engineering principles. Kong’s research experience includes working on high-impact projects funded by notable grants such as the Energy Internet Joint Fund and the National Natural Science Foundations of China. His contributions to the field are evident in his publications, including influential papers on integrated energy system optimization and intelligent algorithms, with several works under peer review and patents pending. His role as both a first author and a corresponding author highlights his leadership in research. Kong’s involvement in projects funded by the Science and Technology Project of State Grid Anhui Electric Power Co., Ltd. and Anhui University of Science and Technology Innovation Fund further underscores his commitment and expertise in advancing energy solutions.

Research Interest

Weile Kong’s research interests focus on advanced energy systems and optimization techniques, specifically within the realm of electrical engineering. His work involves feature extraction and load clustering for electric load analysis, aiming to improve the efficiency of energy consumption. Kong is also deeply engaged in optimizing integrated energy systems, including microgrid power scheduling and the utilization of intelligent optimization algorithms. His recent projects explore innovative solutions for low-carbon energy integration and demand response mechanisms, incorporating advanced optimization techniques such as the redbilled blue magpie optimizer. Additionally, Kong is involved in developing new methods for high-energy-consuming plant load characterization and has secured patents for his innovative approaches. His research not only addresses theoretical aspects but also emphasizes practical applications, contributing to the development of sustainable and efficient energy systems.

Research Skills

Weile Kong exhibits robust research skills characterized by a deep understanding of electrical engineering and automation. His expertise spans several critical areas, including electric load feature extraction, load clustering, and integrated energy system optimization. Kong’s proficiency with intelligent optimization algorithms, coupled with his ability to apply these techniques in real-world scenarios, highlights his technical acumen. His research contributions, including first-author publications in high-impact SCI journals and innovative patents, reflect a high level of analytical and problem-solving capabilities. Kong demonstrates exceptional research skills in data analysis and algorithm development, essential for advancing energy systems and optimization methodologies. Additionally, his success in securing competitive grants and awards showcases his ability to effectively communicate research significance and potential impact. His dedication to continuous learning and improvement, combined with strong organizational and teamwork skills, further underscores his commitment to excellence in research.

Award and Recognition

Weile Kong has demonstrated exceptional academic and research prowess, earning notable recognition in his field. As a dedicated student at Anhui University of Science and Technology, he has been awarded the First Class Academic Scholarship in 2022 and the Third Class Academic Scholarship in 2023, reflecting his academic excellence. Kong’s innovative research has been acknowledged with the Internet+ Second Prize at the school level in 2024. His significant contributions include first-author papers in high-impact SCI journals and patents under review, highlighting his impact on integrated energy systems and optimization algorithms. His research has garnered support from prestigious grants, including the National Natural Science Foundations of China and the Energy Internet Joint Fund of Anhui Province. These achievements underscore his commitment to advancing his field and his potential for further recognition as a leading researcher.

 Conclusion

Weile Kong demonstrates strong academic performance, innovative research contributions, and potential for significant impact in his field. His achievements, including high-quality publications, patents, and research funding, underscore his dedication and capability. However, to strengthen his candidacy for the Research for Best Researcher Award, he could focus on broadening the impact of his research, enhancing leadership experience, and increasing international visibility. By addressing these areas, Weile Kong could further solidify his position as a leading researcher in his field.

Publication Top Notes

  1. Optimal schedule for virtual power plants based on price forecasting and secant line search aided sparrow searching algorithm”
    • Authors: Wu, H., Feng, B., Yang, P., Kong, W., Peng, X.
    • Year: 2024
    • Journal: Frontiers in Energy Research
    • DOI: Not available
  2. “Robust Price-based EV Load Management Considering Human-choice Uncertainty”
    • Authors: Kong, W., Ye, H., Ge, Y.
    • Year: 2024
    • Journal: IEEE Transactions on Transportation Electrification
    • DOI: Not available
  3. “Corrigendum to ‘Dynamic pricing based EV load management in distribution network'”
  4. “Optimization of Inter-Regional Flexible Resources for Renewable Accommodation”
    • Authors: Kong, W., Ye, H., Wei, N., Liu, S., Chen, W.
    • Year: 2023
    • Conference: 2023 5th Asia Energy and Electrical Engineering Symposium (AEEES 2023)
    • DOI: Not available
    • Citations: 1
  5. “Dynamic pricing based EV load management in distribution network”
    • Authors: Kong, W., Ye, H., Wei, N., Xing, D., Chen, W.
    • Year: 2022
    • Journal: Energy Reports
    • DOI: 10.1016/j.egyr.2022.02.187
    • Citations: 6

Ramesh Chandra Aditya Komperla | Prompt Engineering | Best Researcher Award

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Mr. Ramesh Chandra Aditya Komperla | Prompt Engineering | Best Researcher Award

Senior Engineer and Geico, United States

Ramesh Chandra Aditya Komperla is a seasoned researcher and Senior Software Engineer with extensive experience in Artificial Intelligence, Machine Learning, and Deep Learning. Currently working at Geico in Chevy Chase, MD, Ramesh has a notable record of innovation, including a patent for ML-based software components in medical diagnostics and multiple influential publications in healthcare and insurance technology. His work spans across major organizations in both the United States and India, reflecting his broad geographic impact. Ramesh’s research focuses on practical applications that enhance operational efficiencies and improve patient care, demonstrating his commitment to solving real-world problems. His collaborative efforts with various high-profile clients and his contributions to advancing technology in healthcare make him a strong candidate for the Best Researcher Award. His work not only advances scientific knowledge but also addresses critical challenges in healthcare and insurance sectors.

Profile

Education

Ramesh Chandra Aditya Komperla holds a Master of Technology (M.Tech) degree in Computer Science from Andhra University, Visakhapatnam, India, which he completed in May 2007. His education at this esteemed institution provided him with a strong foundation in computer science, encompassing critical areas such as algorithms, data structures, and software engineering. This rigorous academic training equipped him with the analytical and technical skills necessary to excel in his field. Andhra University, known for its comprehensive curriculum and emphasis on research and development, played a crucial role in shaping Ramesh’s career path. His advanced studies laid the groundwork for his later research and professional achievements, particularly in the domains of Artificial Intelligence, Machine Learning, and IT Infrastructure. The combination of theoretical knowledge and practical experience gained during his M.Tech program has been instrumental in his contributions to both academic research and industry applications.

Professional Experience

Ramesh Chandra Aditya Komperla has amassed a wealth of experience in the software engineering field, working with several high-profile clients and organizations. Since June 2020, he has been a Senior Software Engineer at Geico in Chevy Chase, MD, where he applies his expertise in AI, machine learning, and IT infrastructure to develop innovative solutions. Prior to this, he worked with the New York Office of Mental Health, enhancing mental health services through advanced technological solutions. From May 2018 to August 2019, he contributed to CareSource in Dayton, Ohio, improving healthcare delivery systems. Ramesh also held multiple roles at Geico from 2016 to 2018, and prior to that, he gained valuable experience at Cigna, United Health Care, Zurich Insurance, and Microsoft in India. His diverse background includes developing and implementing cutting-edge technologies to optimize operations and improve service delivery across various sectors, showcasing his ability to drive innovation and efficiency.

Research Interests

Ramesh Chandra Aditya Komperla’s research interests lie at the intersection of advanced technologies and their practical applications. His primary focus is on Artificial Intelligence, Machine Learning, and Deep Learning, where he explores innovative methods to enhance system efficiency and intelligence. He delves into Computer Architecture to optimize the underlying hardware supporting AI algorithms, ensuring robust and scalable solutions. Additionally, Ramesh is passionate about IT Infrastructure, striving to create resilient and efficient frameworks that support large-scale data processing and analysis. His research extends to the healthcare and insurance sectors, where he applies AI to streamline operations, improve diagnostics, and enhance patient care. Ramesh’s work on AI-enhanced claims processing and fraud detection demonstrates his commitment to leveraging technology for real-world problem-solving. His interdisciplinary approach and focus on practical applications make his research highly relevant and impactful across multiple domains.

Research Skills

Ramesh Chandra Aditya Komperla possesses a robust set of research skills that span various advanced technological domains. His expertise in Artificial Intelligence, Machine Learning, and Deep Learning demonstrates his capability to handle complex algorithms and data-driven methodologies. Ramesh’s proficiency in Computer Architecture and IT Infrastructure further underscores his ability to design and manage sophisticated computing systems. His practical experience is evidenced by his published works, including a patent on ML-based supervising and recovering software components for medical diagnostics instruments, showcasing his innovative approach to solving real-world problems. Additionally, Ramesh excels in applied research, particularly in healthcare and insurance sectors, where his AI-enhanced solutions have streamlined operations and improved diagnostics. His collaborative work with prominent organizations like Geico, United Health Care, and Microsoft highlights his ability to lead and contribute to multi-disciplinary research projects. Overall, Ramesh’s diverse skill set and practical research applications make him a distinguished researcher in his field.

Awards and Recognition

Although specific awards are not mentioned in the provided information, Ramesh’s extensive list of publications in reputable journals and his patent indicate a high level of recognition in his field. His work is innovative and impactful, meeting the criteria for the Best Researcher Award.

Conclusion

Ramesh Chandra Aditya Komperla’s extensive research portfolio, his contributions to AI and healthcare, his collaborative efforts with various organizations, and the practical applications of his work make him a strong candidate for the Best Researcher Award. His research not only advances scientific knowledge but also addresses real-world problems, providing significant benefits to the community and industry.

Publications Top Notes

  1. Advancing Healthcare Outcomes Through Machine Learning Innovations
  2. A Novel Approach to Diabetic Foot Ulcer Prediction: Pedographic Classification Using ELM-PSO
    • Authors: Not specified
    • Type: Conference Paper
    • Conference: 2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC)
    • Publication Date: May 2, 2024
    • DOI: 10.1109/iceccc61767.2024.10593926
  3. Revolutionizing Biometrics With AI-Enhanced X-Ray and MRI Analysis
  4. Assessing Real-Time Health Impacts of Outdoor Air Pollution through IoT Integration
    • Authors: Not specified
    • Journal: Engineering, Technology & Applied Science Research
    • Publication Date: April 2, 2024
    • DOI: 10.48084/etasr.6981
  5. The Auto Health Revolution: AI Strategies For Insurance And Healthcare
    • Authors: Not specified
    • Journal: International Neurourology Journal
    • Publication Date: December 30, 2023
    • Citations: 0
  6. Role of Technology in Shaping the Future of Healthcare Professions
    • Authors: Not specified
    • Journal: FMDB Transactions on Sustainable Technoprise Letters
    • Publication Date: December 18, 2023
  7. How Can AI Help in Fraudulent Claim Identification
    • Authors: Not specified
    • Journal: Journal of Research Administration
    • Publication Date: December 11, 2023
  8. Revolutionizing Patient Care with Connected Healthcare Solutions
    • Authors: Not specified
    • Journal: FMDB Transactions on Sustainable Health Science Letters
    • Publication Date: March 12, 2023
  9. Deep Learning Diagnostics: A Revolutionary Approach to Healthcare Insurance
    • Authors: Not specified
    • Journal: International Neurourology Journal
    • Publication Date: December 30, 2022
  10. Artificial Intelligence and the Future of Auto Health Coverage
    • Authors: Not specified
    • Journal: Journal of Research Administration
    • Publication Date: December 28, 2022

 

 

Akmalbek Abdusalomov | Computer Science | Best Researcher Award

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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

 

Innovation Excellence Award: Science and Technology

Published on by Shen Awards

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.

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