Woosik Lee | Computer Science | Research Excellence Award

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Dr. Woosik Lee | Computer Science | Research Excellence Award

Korea Social Security Information Service | South Korea

Dr. Woosik Lee is a researcher at the Research Center of the Korea Social Security Information Service, specializing in wireless sensor networks, Internet of Things systems, and data-driven intelligent services. He holds advanced degrees in computer science with a focus on networked systems, sensor technologies, and intelligent algorithms. His professional experience spans academic, governmental, and international research environments, including faculty service, visiting research appointments, and leadership roles in applied research projects addressing healthcare monitoring, intelligent transportation, and social welfare analytics. His research focuses on low-power communication protocols, neighbor discovery mechanisms, wireless body sensor networks, human monitoring systems, and machine learning–based social welfare applications. He has authored numerous peer-reviewed journal articles and conference contributions, demonstrating sustained scholarly impact and interdisciplinary relevance. His work integrates theoretical modeling, protocol design, simulation, and real-world system implementation, contributing to both academic advancement and societal benefit. Dr. Lee’s research excellence has been recognized through competitive awards and sustained citation impact, highlighting his growing influence and strong potential for continued leadership in intelligent networked systems research.

Citation Metrics (Scopus)

140
100
50
25
0

Citations

140

Documents

24

h-index

8

Citations

Documents

h-index

 


Featured Publications

Shalli Rani | Computer Science | Best Researcher Award

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Prof. Shalli Rani | Computer Science | Best Researcher Award

Professor | Chitkara University | India

Prof. Shalli Rani is a distinguished researcher in the fields of Internet of Things, Wireless Sensor Networks, Cloud Computing, and Machine Learning, with a prolific record of high-impact publications, books, patents, and editorial contributions. She has demonstrated exceptional leadership in guiding numerous PhD and ME students, fostering innovation and research excellence. Her work effectively bridges academia and industry through applied projects, including smart healthcare solutions, Industry 5.0 initiatives, and explainable AI systems. Recognized globally through invited talks, conference engagements, and editorial responsibilities in top journals, she has established herself as a thought leader in her domain. Her research contributions reflect both depth and breadth, combining theoretical rigor with practical relevance. Prof. Rani’s measurable research impact on Scopus is remarkable, with 4,400 citations, 311 documents, and an h-index of 34, highlighting her sustained influence and scholarly excellence in the international research community.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. S. Rani, R. Talwar, J. Malhotra, S. Ahmed, M. Sarkar, and H. Song, “A novel scheme for an energy efficient Internet of Things based on wireless sensor networks,” Sensors, vol. 15, no. 11, pp. 28603–28626, 2015.

2. S. Rani, S. H. Ahmed, and R. Rastogi, “Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications,” Wireless Networks, vol. 26, no. 4, pp. 2307–2316, 2020.

3. S. Bharany, S. Badotra, S. Sharma, S. Rani, M. Alazab, and R. H. Jhaveri, “Energy efficient fault tolerance techniques in green cloud computing: A systematic survey and taxonomy,” Sustainable Energy Technologies and Assessments, vol. 53, p. 102613, 2022.

4. G. S. Brar, S. Rani, V. Chopra, R. Malhotra, H. Song, and S. H. Ahmed, “Energy efficient direction-based PDORP routing protocol for WSN,” IEEE Access, vol. 4, pp. 3182–3194, 2016.

5. S. Rani, D. Koundal, M. F. Ijaz, M. Elhoseny, and M. I. Alghamdi, “An optimized framework for WSN routing in the context of Industry 4.0,” Sensors, vol. 21, no. 19, p. 6474, 2021.

Fawwad Hassan Jaskani | Computer Science | Best Researcher Award

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Dr. Fawwad Hassan Jaskani | Computer Science | Best Researcher Award

Doctor at The Islamia University of Bahawalpur | Pakistan

Dr. Fawwad Hassan Jaskani is a distinguished researcher and leader specializing in machine learning, robotics, and advanced data-driven applications. As the Chief Executive Officer of FHJ Complex Infinite Solutions, he has guided teams in delivering high-quality research assistance and innovative technical solutions tailored to the needs of scholars and professionals. His expertise spans Microsoft Azure, Power BI, and Robotic Process Automation, which he effectively integrates into projects to enhance efficiency and impact. With an academic foundation rooted in The Islamia University of Bahawalpur and Universiti Tun Hussein Onn Malaysia, Dr. Jaskani has produced influential publications addressing diverse fields, including artificial neural networks, digital protection systems, Internet of Things, and medical data analysis. His contributions as a peer reviewer for international journals further underscore his dedication to advancing knowledge and ensuring quality in research. Combining academic rigor with practical application, he continues to shape the research landscape with innovation and leadership.

Professional Profile 

Google Scholar | Scopus Profile

Education

Dr. Fawwad Hassan Jaskani holds a strong academic background in machine learning and robotics, having pursued advanced studies at The Islamia University of Bahawalpur, where he completed his Master of Engineering with a focus on machine learning and robotics. He further enhanced his expertise by earning a Doctor of Philosophy in Machine Learning from Universiti Tun Hussein Onn Malaysia. His educational journey has provided him with a deep understanding of artificial intelligence, data analysis, and automation technologies, which he has effectively applied in his professional and research career. Through his academic training, he has developed a robust foundation in both theoretical concepts and practical implementations, enabling him to bridge the gap between innovation and application. His educational achievements have not only fueled his research pursuits but also established his credibility as a thought leader in the domains of artificial intelligence, data-driven technologies, and computational research methodologies.

Experience

Dr. Fawwad Hassan Jaskani brings extensive professional experience spanning leadership, research, and technical consultancy. As Chief Executive Officer of FHJ Complex Infinite Solutions, he has successfully led teams in providing tailored research assistance, technical simulations, and high-quality solutions for academic and professional clients. His experience as a peer reviewer for international journals with TechScience Press reflects his role in maintaining scholarly standards and contributing to the global research community. Over the years, he has also worked as a professional freelancer, collaborating with diverse clients on projects requiring specialized expertise in artificial intelligence, automation, and data science. These experiences have honed his project management, communication, and problem-solving skills, positioning him as both a leader and an innovator. His diverse career reflects a unique ability to merge academic insights with industry requirements, demonstrating his effectiveness in driving impactful outcomes while fostering research excellence and applied technological advancements.

Research Focus

Dr. Fawwad Hassan Jaskani’s research primarily focuses on machine learning, artificial intelligence, robotics, and their applications across interdisciplinary fields. His publications showcase a wide array of studies, including neural networks, digital differential protection schemes, operating systems for the Internet of Things, and predictive modeling for healthcare, particularly early detection of diseases. He also explores visualization techniques for complex biological datasets and comparative analyses of classification models, reflecting his commitment to advancing both theoretical and applied dimensions of research. His work emphasizes the integration of AI-driven solutions into real-world challenges, bridging the gap between academia and practical implementation. By combining algorithmic efficiency with innovation, Dr. Jaskani’s research contributes to fields as diverse as bioinformatics, automation, energy systems, and digital security. His ability to explore multiple disciplines through the lens of machine learning makes his research not only impactful but also forward-looking, contributing to global technological and scientific progress.

Award and Honor

Dr. Fawwad Hassan Jaskani has earned recognition for his contributions as a researcher, innovator, and academic leader. His role as a peer reviewer for international journals highlights the trust placed in his expertise and his influence within the scholarly community. His academic achievements, including successful completion of advanced degrees in machine learning and robotics, further underscore his dedication and excellence. In his professional career, he has been acknowledged for leading FHJ Complex Infinite Solutions, where his efforts in transforming research assistance into high-impact, customized solutions have been highly valued. Additionally, his publications across diverse areas of artificial intelligence and automation demonstrate his contribution to knowledge creation, which is itself a mark of distinction. While his recognitions are rooted in his academic and professional excellence, his ongoing commitment to innovation, mentorship, and applied research continues to elevate his profile as an accomplished researcher deserving of honors and awards.

Publication Top Notes

  • Title: Time-Series Prediction of Cryptocurrency Market using Machine Learning Techniques
    Year: 2021
    Citations: 73

  • Title: Comparison of classification models for early prediction of breast cancer
    Year: 2019
    Citations: 73

  • Title: ICC T20 Cricket World Cup 2020 winner prediction using machine learning techniques
    Year: 2020
    Citations: 38

  • Title: Prediction of Cardiovascular Disease on Self‐Augmented Datasets of Heart Patients Using Multiple Machine Learning Models
    Year: 2022
    Citations: 37

  • Title: IOTA‐Based Mobile Crowd Sensing: Detection of Fake Sensing Using Logit‐Boosted Machine Learning Algorithms
    Year: 2022
    Citations: 21

  • Title: An Investigation on Several Operating Systems for Internet of Things
    Year: 2019
    Citations: 17

  • Title: Lungs nodule cancer detection using statistical techniques
    Year: 2020
    Citations: 16

  • Title: Convolutional Autoencoder‐Based Deep Learning Approach for Aerosol Emission Detection Using LiDAR Dataset
    Year: 2022
    Citations: 15

  • Title: Urbanization Detection Using LiDAR‐Based Remote Sensing Images of Azad Kashmir Using Novel 3D CNNs
    Year: 2022
    Citations: 15

  • Title: Short-Term Prediction Model for Multi-Currency Exchange Using Artificial Neural Network
    Year: 2020
    Citations: 12

  • Title: Detection of Uterine Fibroids in Medical Images Using Deep Neural Networks
    Year: 2022
    Citations: 11

  • Title: Hybrid machine learning techniques to detect real time human activity using UCI dataset
    Year: 2021
    Citations: 9

  • Title: Detection of anomaly in videos using convolutional autoencoder and generative adversarial network model
    Year: 2020
    Citations: 9

  • Title: Comparative Analysis of Face Detection Using Linear Binary Techniques and Neural Network Approaches
    Year: 2018
    Citations: 7

  • Title: Karachi Stock Exchange Price Prediction using Machine Learning Regression Techniques
    Year: 2021
    Citations: 6

Conclusion

Dr. Fawwad Hassan Jaskani has established himself as a prolific researcher with impactful contributions across diverse domains, including machine learning, healthcare analytics, IoT systems, financial forecasting, and computer vision. His publications reflect a consistent effort to bridge academic theory with real-world applications, often addressing socially and technologically significant challenges such as disease prediction, urbanization monitoring, and market forecasting. The steady citation record of his work demonstrates both relevance and influence within the global research community. His ability to collaborate across disciplines, produce high-quality research outputs, and contribute to advancing modern computational techniques highlights his position as a strong candidate for recognition. With continued focus on interdisciplinary innovation and global engagement, he is well-poised to make even greater contributions to the fields of artificial intelligence and applied research.

Hatem Magdy Keshk | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Hatem Magdy Keshk | Computer Science | Best Researcher Award

Postdoc at King Fahd University of Petroleum and Minerals | Saudi Arabia

Dr. Hatem Magdy Keshk is an accomplished researcher and academic with extensive expertise in artificial intelligence, deep learning, remote sensing, satellite image processing, GIS, UAV applications, and smart cities. He has served in diverse academic and research roles, including teaching, curriculum development, and departmental leadership, while also conducting impactful research across multiple disciplines. His career spans leading institutions in Egypt, Saudi Arabia, and Hong Kong, where he has undertaken postdoctoral research in interdisciplinary and space-related fields. Beyond academia, he has contributed to national and international initiatives such as land cover classification for Arab countries and served as a member of research councils, reflecting his commitment to advancing both science and societal applications. With over a decade of experience in teaching and research, he continues to blend innovation with academic rigor, positioning himself as a valuable contributor to the global research community and a strong candidate for recognition

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Hatem Magdy Keshk has pursued an extensive academic journey in computer science and related fields, equipping himself with strong theoretical knowledge and practical expertise. His educational background is highlighted by a Postdoctoral Fellowship at The Hong Kong Polytechnic University, where he conducted interdisciplinary research at the Smart Cities Research Institute. He later advanced his postdoctoral work at King Fahd University of Petroleum and Minerals, focusing on artificial intelligence, deep learning, and UAV applications under the Interdisciplinary Research Center for Aviation and Space Exploration. Throughout his academic development, he has engaged in both teaching and research simultaneously, ensuring that his educational growth was complemented by practical exposure. This balanced foundation has enabled him to develop expertise in machine learning, programming, image processing, and networking, while also gaining international research exposure that broadened his perspective on addressing global scientific challenges through interdisciplinary approaches.

Experience

Dr. Hatem Magdy Keshk has accumulated extensive professional experience spanning over a decade across teaching, research, and academic leadership. He began his career as a teaching assistant and coordinator in computer science, where he managed courses, laboratories, and departmental coordination. His academic career includes teaching positions at leading Egyptian institutions such as Future University, Obour Institute, and others, where he taught a wide range of subjects from artificial intelligence to operating systems and GIS. Beyond teaching, he has played a significant role in research, serving as a researcher at the National Authority for Remote Sensing and Space Sciences, where he worked on satellite image analysis, GIS applications, and deep learning integration. His experience also extends internationally, with postdoctoral research at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals. These roles highlight his ability to blend teaching, research, and applied science, contributing to both academia and national projects.

Research Focus

The research of Dr. Hatem Magdy Keshk lies at the intersection of artificial intelligence, deep learning, and remote sensing, with strong applications in smart cities, UAV systems, and space exploration. His work has concentrated on developing algorithms and systems for processing and analyzing satellite images, contributing to fields such as land cover classification and environmental monitoring. By combining AI with geospatial technologies, his research aims to create efficient solutions for large-scale data analysis and decision support systems. He has also contributed to the advancement of UAV applications, integrating machine learning techniques for enhanced automation and real-world usability. His interdisciplinary approach extends to smart city development, where his work supports sustainable urban planning and technology-driven innovation. With contributions spanning data science, computer vision, and applied AI, his research not only strengthens academic knowledge but also provides solutions with societal and industrial impact, positioning him as a versatile and impactful researcher.

Award and Honor

Dr. Hatem Magdy Keshk has earned recognition for his sustained contributions to research, teaching, and academic service. His selection for prestigious postdoctoral fellowships at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals reflects international acknowledgment of his expertise and research potential. His involvement in high-level councils, including the Space Research Council under Egypt’s Ministry of Research and Higher Education, further highlights his standing as a respected contributor to national scientific initiatives. Additionally, his participation in globally significant programs, such as the FAO Land Cover Classification System for Arab countries, underscores the trust placed in his capabilities to contribute to large-scale, impactful projects. These honors, alongside his leadership roles in academic departments and curriculum development, showcase not only his research excellence but also his dedication to advancing education and interdisciplinary collaboration. Collectively, these achievements underline his status as a researcher of high merit.

Publication Top Notes

  • Title: Satellite super-resolution images depending on deep learning methods: a comparative study
    Year: 2017
    Citations: 24

  • Title: Change detection in SAR images based on deep learning
    Year: 2020
    Citations: 22

  • Title: Performance evaluation of quality measurement for super-resolution satellite images
    Year: 2014
    Citations: 16

  • Title: Obtaining super-resolution satellites images based on enhancement deep convolutional neural network
    Authors: HM Keshk, XC Yin
    Year: 2021
    Citations: 11

  • Title: Semantic segmentation of some rock-forming mineral thin sections using deep learning algorithms: a case study from the Nikeiba area, South Eastern Desert, Egypt
    Year: 2024
    Citations: 8

  • Title: Classification of EgyptSat-1 images using deep learning methods
    Year: 2020
    Citations: 8

  • Title: Three-pass (DInSAR) ground change detection in Sukari gold mine, Eastern Desert, Egypt
    Year: 2022
    Citations: 4

  • Title: Geometric Correction of Aerial Camera and LiDAR Hybrid System Data Using GNSS/IMU
    Year: 2022
    Citations: 2

  • Title: Retracted article: Sentinel-2 cloud mask classification using deep learning method
    Year: 2022
    Citations: 2

Conclusion

Dr. Hatem Magdy Keshk has made significant contributions to the fields of artificial intelligence, deep learning, and remote sensing, with a strong focus on satellite image processing, change detection, and smart applications in geosciences and urban development. His publications demonstrate a blend of theoretical advancements and practical applications, contributing to international research visibility. With impactful works published in respected journals and conferences, his research has attracted citations that reflect the recognition of his contributions within the scientific community. Despite one retracted paper, the overall body of his work shows consistency, innovation, and interdisciplinary application. His role as both a researcher and collaborator highlights his ability to address complex scientific challenges and develop solutions of societal and technological value. These accomplishments position him as a strong candidate for honors such as the Best Researcher Award, with ongoing potential to expand his impact globally.

Sheikh Shanawaz Mostafa | Computer Science | Best Researcher Award

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Dr. Sheikh Shanawaz Mostafa | Computer Science | Best Researcher Award

PostDoc at Instituto Superior Técnico, Portugal

Dr. Sheikh Shanawaz Mostafa is a dynamic researcher with over 12 years of experience in artificial intelligence, biomedical engineering, and computer science. He has an impressive track record of over 60 publications with a cumulative impact factor exceeding 144 and has contributed to impactful projects in healthcare, agriculture, energy, and smart systems. With academic credentials spanning Bangladesh and Portugal, including a Ph.D. from Instituto Superior Técnico, his work bridges interdisciplinary fields and real-world applications. He has led and contributed to high-profile projects such as Sleep Revolution, BASE, and AHEAD, demonstrating expertise in deep learning, explainable AI, and human-in-the-loop systems. Dr. Mostafa has supervised Ph.D., M.Sc., and B.Sc. theses, secured international research funding, and collaborated with institutions like Carnegie Mellon University and companies such as Zomato. Known for his mentorship, cross-cultural adaptability, and innovative thinking, he is a highly suitable candidate for the Best Researcher Award.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education

Dr. Sheikh Shanawaz Mostafa holds a Ph.D. in Electrical and Computer Engineering from Instituto Superior Técnico, University of Lisbon, Portugal, where he specialized in Networked Interactive Cyber-Physical Systems, a joint program with Carnegie Mellon University. He completed his M.Sc. in Biomedical Engineering and B.Sc. in Electronics and Communication Engineering from Khulna University of Engineering & Technology (KUET), Bangladesh. Throughout his academic journey, he has maintained a strong interdisciplinary focus, integrating electrical engineering, biomedical systems, and artificial intelligence. His Ph.D. thesis on sleep apnea detection was awarded “Pass with Distinction,” reflecting his academic excellence and research impact. With a consistent academic record across diverse technical disciplines, Dr. Mostafa’s educational background has provided a solid foundation for innovative research at the intersection of AI and health technologies.

Professional Experience

Dr. Mostafa brings over 12 years of international academic and experience, having worked with renowned institutions such as Instituto Superior Técnico, Madeira Interactive Technologies Institute, ARDITI, and KUET. Currently serving as a Postdoctoral Researcher (R3) at Instituto Superior Técnico, he has held multiple roles as an AI consultant, assistant professor, and principal researcher across EU-funded and industry-partnered projects. His key projects include Sleep Revolution, BASE (banana harvesting optimization), AHEAD (EV infrastructure planning), and RRSO (restaurant sentiment analytics). Dr. Mostafa has demonstrated excellence in leading interdisciplinary teams, securing competitive research grants, and collaborating with industry partners like Zomato and Asseco PST. He has also mentored numerous Ph.D., M.Sc., and undergraduate students and actively contributes to curriculum development. His ability to bridge academic research with practical, high-impact applications highlights his value as both a researcher and educator.

Research Interest

Dr. Mostafa’s research interests lie at the intersection of artificial intelligence and real-world problem-solving. His primary focus includes deep learning, explainable AI, machine learning, and human-in-the-loop systems, particularly in applications related to healthcare, biomedical signal analysis, smart agriculture, energy systems, and natural language processing. He has contributed significantly to advancing AI-driven diagnostics, such as in sleep disorder analysis, and to building predictive models for fields ranging from sports performance to restaurant sentiment analysis. He is also interested in the integration of AI into smart cities and infrastructure, including EV charging optimization and real-time decision systems. His interdisciplinary approach allows him to explore novel AI applications in medicine, agritech, and environmental systems. Combining theoretical modeling with applied innovation, Dr. Mostafa’s work seeks to create intelligent systems that are not only technically robust but also socially and economically impactful.

Award and Honor

Dr. Sheikh Shanawaz Mostafa has earned recognition throughout his academic and professional career for his contributions to research and education. While formal award listings are not detailed, his achievements—such as securing over $25,000 in competitive research funding, earning a Ph.D. with Distinction, publishing in high-impact journals, and successfully leading EU and industry-sponsored research projects—reflect significant professional recognition. His selection for collaborative international programs like the CMU-Portugal partnership, and his roles in innovative projects supported by organizations like the Portuguese Foundation for Science and Technology (FCT), further highlight his esteemed standing in the academic and research community. His work has also been showcased in prestigious venues, such as the Electronic Imaging conference in San Francisco. The impact of his research and mentorship, as well as the trust placed in him by academic and industrial collaborators, is a testament to his excellence and potential for future honors.

Conclusion

Dr. Sheikh Shanawaz Mostafa exemplifies the qualities of a leading interdisciplinary researcher, combining deep technical expertise with a commitment to solving real-world challenges through AI and engineering. His strong academic foundation, international experience, and impressive publication record reflect a sustained dedication to research excellence. He has not only led cutting-edge projects across healthcare, smart systems, and agriculture, but also mentored the next generation of scholars, thereby extending his impact. His adaptability across cultural and institutional contexts, successful collaborations with industry, and ability to secure research funding mark him as a forward-thinking and versatile contributor to the global scientific community. With a clear trajectory of growth, innovation, and leadership, Dr. Mostafa is highly deserving of recognition such as the Best Researcher Award and stands poised to make even greater contributions in the future.

Publications Top Notes

  • Title: A review of obstructive sleep apnea detection approaches
    Authors: F. Mendonca, S.S. Mostafa, A.G. Ravelo-Garcia, F. Morgado-Dias, T. Penzel
    Year: 2018
    Citations: 235

  • Title: An adaptive level dependent wavelet thresholding for ECG denoising
    Authors: M.A. Awal, S.S. Mostafa, M. Ahmad, M.A. Rashid
    Year: 2014
    Citations: 198

  • Title: A systematic review of detecting sleep apnea using deep learning
    Authors: S.S. Mostafa, F. Mendonça, A.G. Ravelo-García, F. Morgado-Dias
    Year: 2019
    Citations: 175

  • Title: Devices for home detection of obstructive sleep apnea: A review
    Authors: F. Mendonça, S.S. Mostafa, A.G. Ravelo-García, F. Morgado-Dias, T. Penzel
    Year: 2018
    Citations: 137

  • Title: A review of approaches for sleep quality analysis
    Authors: F. Mendonça, S.S. Mostafa, F. Morgado-Dias, A.G. Ravelo-Garcia, T. Penzel
    Year: 2019
    Citations: 119

  • Title: SpO2 based Sleep Apnea Detection using Deep Learning
    Authors: S.S. Mostafa, F. Mendonça, F. Morgado-Dias, A. Ravelo-García
    Year: 2017
    Citations: 86

  • Title: Performance analysis of Savitzky-Golay smoothing filter using ECG signal
    Authors: M.A. Awal, S.S. Mostafa, M. Ahmad
    Year: 2011
    Citations: 79

  • Title: XGB-RF: A hybrid machine learning approach for IoT intrusion detection
    Authors: J.A. Faysal, S.T. Mostafa, J.S. Tamanna, K.M. Mumenin, M.M. Arifin, M.A. Awal, …
    Year: 2022
    Citations: 66

  • Title: Multi-objective hyperparameter optimization of CNN for obstructive sleep apnea detection
    Authors: S.S. Mostafa, F. Mendonca, A.G. Ravelo-Garcia, G.G. Juliá-Serdá, …
    Year: 2020
    Citations: 56

  • Title: Human emotion recognition using frequency & statistical measures of EEG signal
    Authors: M. Islam, T. Ahmed, S.S. Mostafa, M.S.U. Yusuf, M. Ahmad
    Year: 2013
    Citations: 50

  • Title: Implementation strategy of CNNs on FPGAs for appliance classification using VI trajectory
    Authors: D. Baptista, S.S. Mostafa, L. Pereira, L. Sousa, F. Morgado-Dias
    Year: 2018
    Citations: 47

  • Title: Automatic detection of cyclic alternating pattern
    Authors: F. Mendonça, A. Fred, S.S. Mostafa, F. Morgado-Dias, A.G. Ravelo-García
    Year: 2022
    Citations: 39

  • Title: Optimization of sleep apnea detection using SpO2 and ANN
    Authors: S.S. Mostafa, J.P. Carvalho, F. Morgado-Dias, A. Ravelo-García
    Year: 2017
    Citations: 37

  • Title: An oximetry based wireless device for sleep apnea detection
    Authors: F. Mendonça, S.S. Mostafa, F. Morgado-Dias, A.G. Ravelo-García
    Year: 2020
    Citations: 30

  • Title: Design and optimization of ECG modeling for generating different cardiac dysrhythmias
    Authors: M.A. Awal, S.S. Mostafa, M. Ahmad, M.A. Alahe, M.A. Rashid, A.Z. Kouzani, …
    Year: 2021
    Citations: 26

Chandra Sekhar Kolli | Computer Science | Best Researcher Award

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Dr. Chandra Sekhar Kolli | Computer Science | Best Researcher Award

Associate Professor at Shri Vishnu Engineering College for Women, India

Dr. Chandra Sekhar Kolli is an accomplished academic in Computer Science with extensive teaching experience across multiple prestigious institutions. With a passion for research and a commitment to advancing knowledge in the field, Dr. Kolli has made significant contributions to areas such as machine learning, data science, and cyber security.

Profile

Scopus Profile

Education 🎓

Dr. Kolli holds a Ph.D. in Computer Science from GITAM (Deemed to be University), Visakhapatnam, obtained in 2021. He completed his M.E. in Computer Science Engineering from HITS (Deemed to be University), Chennai, in 2011 with a CGPA of 7.99, and earned his MCA from Andhra University in 2008 with a score of 74%. He also completed his B.Sc. in Computer Science from Andhra University in 2005, achieving a 71% score.

Experience 🏫

Dr. Kolli has over 13 years of teaching experience, currently serving as an Associate Professor at Shri Vishnu Engineering College for Women, Bhimavaram since June 2023. Prior to this role, he held positions such as Senior Assistant Professor at Aditya College of Engineering and Technology, and Assistant Professor at Koneru Lakshmaiah Education Foundation and Madanapalle Institute of Technology & Science, where he contributed significantly to curriculum development and student training.

Research Interests 🔍

Dr. Kolli’s research focuses on deep learning, privacy-enhanced technologies, fraud detection, and machine learning applications in various domains. His work seeks to leverage advanced algorithms to solve real-world problems, particularly in data security and intelligent systems.

Awards 🏆

Dr. Kolli was honored with the Best Teacher Award for the academic year 2019-20 at KLEF (Deemed to be University), Vijayawada. Additionally, he is a WIPRO Certified Faculty, having qualified in the Wipro Talent Next Global Certification in October 2020, showcasing his dedication to professional development in education.

Publications 📚

Dr. Kolli has a substantial publication record, including 16 journal articles and 13 conference publications, all indexed in SCOPUS. Notable publications include:

  1. Deep learning-based credit card fraud detection in federated learning
    • Authors: Venkata Krishna Reddy, V., Vijaya Kumar Reddy, R., Siva Krishna Munaga, M., Maddila, S.K., Sekhar Kolli, C.
    • Journal: Expert Systems with Applications
    • Year: 2024
    • Citations: 0
  2. Classification of defective product for smart factory through deep learning method
    • Authors: Raffik, R., Misra, P.K., Kolli, C.S., Chandol, M.K., Shukla, S.K.
    • Journal: AIP Conference Proceedings
    • Year: 2024
    • Citations: 0
  3. A review on machine learning in agricultural sciences
    • Authors: Rayalu, G.M., Farouq, K.M., Kolli, C.S., Herrera, A.P., Muhammad, R.S.
    • Journal: AIP Conference Proceedings
    • Year: 2024
    • Citations: 0
  4. Privacy enhanced course recommendations through deep learning in Federated Learning environments
    • Authors: Kolli, C.S., Seelamanthula, S., Reddy V, V.K., Reddy, M.R.K., Gumpina, B.R.
    • Journal: International Journal of Information Technology (Singapore)
    • Year: 2024
    • Citations: 1
  5. Deep learning-based privacy-preserving recommendations in federated learning
    • Authors: Kolli, C.S., Krishna Reddy, V.V., Reddy, T.S., Dasari, D.B., Reddy, M.R.
    • Journal: International Journal of General Systems
    • Year: 2024
    • Citations: 2

His research has been widely cited, contributing to the academic community and enhancing knowledge in his areas of expertise.

Conclusion ✨

Dr. Chandra Sekhar Kolli continues to inspire students and colleagues alike with his commitment to teaching and research. With numerous accolades and a solid publication record, he stands out as a prominent figure in the field of Computer Science, making impactful contributions that pave the way for future advancements in technology.

Sun Park | Computer Science | Best Research Article Award

Published on by World Top Scientists

Dr. Sun Park | Computer Science | Best Research Article Award

Research Associate Professor at, Gwangju Institute of Science and Technology, South Korea

Sun Park is a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, a position held since 2013. Her research focuses on data mining, information retrieval, information summarization, convergent marine ICT, smart farming, and IoT-cloud & AI computing. Prior to this role, she served as a Research Professor at Mokpo National University’s Information Industry Research Institute from 2010 to 2013. She also worked as a Full-time Lecturer at Honam University from 2008 to 2010 and as an Adjunct Professor at Hanseo University from 2002 to 2007. Sun Park holds a Ph.D. in Computer Information Engineering from Inha University (2007), a Master’s degree in Information and Communication Engineering from Hannam University (2001), and a Bachelor’s degree in Computer Science from Jeonju University (1996). References are available upon request.

Publication Profile

Strengths for the Award

  1. Extensive Experience in Research and Teaching: Sun Park has over a decade of research and teaching experience, with key positions at prestigious institutions like the Gwangju Institute of Science and Technology, Mokpo National University, Honam University, and Hanseo University. This variety of roles highlights a significant breadth and depth of expertise in the field of Computer Science and Engineering.
  2. Specialized Research Focus: Their research areas, including Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm, align well with current and emerging technological trends. This suggests that Sun Park is contributing to forward-thinking, impactful research.
  3. AI and Converging Technologies: As a Research Associate Professor at the Graduate School of AI, Sun Park is in a prime position to lead interdisciplinary projects, bringing together fields like AI, IoT, and smart technologies. These areas are critical for innovation, making their work relevant for contemporary challenges.
  4. Strong Academic Background: Holding a Ph.D. in Computer Information Engineering and advanced degrees in Information and Communication Engineering, Sun Park’s academic credentials demonstrate a high level of expertise. The progression from a Bachelor’s to a Ph.D. showcases a long-standing commitment to the field.
  5. Institutional Impact: Serving in high-ranking academic roles implies that Sun Park has contributed to shaping research strategies, mentoring students, and advancing their institution’s academic reputation, which is a critical factor for awards that recognize leadership in research.

Areas for Improvement

  1. Lack of Specific Research Achievements: The provided profile does not detail significant publications, patents, or specific innovations. A more robust record of high-impact publications or citations would strengthen Sun Park’s candidacy for the Best Researcher Award. Highlighting specific projects or research grants won would also add weight.
  2. Global Collaboration and Visibility: While the candidate is clearly well-established in South Korea, a stronger record of international collaborations, keynote speeches, or participation in global conferences would further elevate their profile. Visibility in international research communities is often crucial for award considerations.
  3. Applied Outcomes or Industry Impact: While the research areas are impressive, the profile does not specify applied outcomes or how these research fields have impacted industries or society. Showcasing tangible applications of research (e.g., how IoT solutions have benefited smart farms or marine industries) would demonstrate real-world influence.

Education:

Sun Park holds a Ph.D. in Computer Information Engineering from Inha University, earned between 2002 and 2007, which forms the foundation of their advanced expertise in computer science. Prior to this, they completed a Master’s degree in Information and Communication Engineering at Hannam University from 1997 to 2001. This followed a Bachelor’s degree in Computer Science from Jeonju University, obtained between 1992 and 1996. This strong academic background, progressing from undergraduate to doctoral levels, demonstrates a deep and comprehensive education in computing and engineering disciplines.

Experience:

Sun Park has over two decades of academic and research experience, spanning various prestigious roles in South Korea. Currently serving as a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, they focus on cutting-edge research in areas like Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm technologies. Previously, they held positions as a Research Professor at Mokpo National University and a Full-time Lecturer at Honam University. Sun Park’s academic journey, from earning a Ph.D. in Computer Information Engineering to holding multiple teaching and research roles, reflects a deep and broad expertise in computer science, with a strong commitment to innovation in AI and emerging technologies.

Research Focus:

Sun Park’s research focuses on several cutting-edge fields, including Data Mining, Information Retrieval, Information Summarization, Convergent Marine ICT, Smart Farming, and IoT-Cloud & AI Computing. This diverse range of interests demonstrates a commitment to advancing both theoretical and practical applications in technology. Their work bridges multiple domains, with a particular emphasis on integrating AI and IoT for innovative solutions in areas like agriculture and marine industries. By focusing on emerging technologies and their real-world implications, Sun Park’s research contributes to solving contemporary challenges in information management and intelligent systems.

Awards and Honors:

Sun Park’s awards and honors are not specifically listed in the provided profile. However, their notable academic positions, such as Research Associate Professor at the Graduate School of AI, Gwangju Institute of Science and Technology, and past roles at Mokpo National University and Honam University, suggest recognition of their expertise and leadership in their field. These roles reflect a high level of academic and research achievement, although further details on specific awards, honors, or recognitions would provide a clearer understanding of their accolades. Highlighting any formal awards or distinctions would strengthen their profile for the Best Researcher Award.

Publication Top Notes:

  • Design of Vessel Data Lakehouse with Big Data and AI Analysis Technology for Vessel Monitoring System
    • Authors: Park, S., Yang, C.-S., Kim, J.
    • Year: 2023
    • Citations: 6
  • Design and Implementation of Data Concentrator Unit supported with Multiple Synchronized Cameras for Object-Detection
    • Authors: Anvarjon, Y., Park, S., Kim, J.
    • Year: 2023
    • Citations: 0
  • Concept Design of Intelligent BoP Based on Slot-/Rack-type Fuel Cell for Integrated Management of Hydrogen Fuel Cells
    • Authors: Park, S., Chung, B.-J., Kim, J.
    • Year: 2023
    • Citations: 1
  • Correction to: Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 1
  • Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 3

Conclusion:

Sun Park’s extensive academic experience, specialized focus in key technological areas, and position within a prominent research institution make them a strong candidate for a research award. However, to be highly competitive for a Best Researcher Award, it would be beneficial for them to highlight specific high-impact research achievements, international collaborations, and real-world applications of their work. These additions would showcase a broader influence in both academic and industrial sectors, further solidifying their candidacy for this prestigious recognition.

Alex Mirugwe | Computer Science | Young Scientist Award

Published on by World Top Scientists

Mr. Alex Mirugwe | Computer Science | Young Scientist Award

Data Scientist at Makerere University, School of Public Health, Uganda

Alex Mirugwe is a highly skilled Data Scientist with over 4 years of experience, specializing in applying machine learning and AI to healthcare challenges, particularly in HIV, cancer, and tuberculosis diagnostics. He has a proven track record of developing data-driven solutions that improve patient outcomes in resource-constrained settings. His research has been published in several peer-reviewed journals, and he is proficient in a wide range of data science tools and methodologies. Alex also contributes to academia as an Assistant Lecturer and is involved in curriculum development and student mentoring in computer science.

Profile:

Strengths for the Award:

  1. Specialized Expertise in Healthcare Data Science: Alex Mirugwe has developed machine learning models and AI tools to solve critical health challenges, such as HIV patient care and cervical cancer detection. His work is not only technically sound but has made tangible impacts on healthcare delivery in resource-constrained environments.
  2. Research Contributions and Publications: Alex has authored multiple peer-reviewed journal articles on healthcare applications of AI, including sentiment analysis of public health data, tuberculosis detection, and cancer screening. These publications demonstrate his commitment to advancing the application of AI in public health and data science.
  3. Experience in Machine Learning and AI: His technical expertise spans a range of relevant tools and techniques, including deep learning, transfer learning, and predictive modeling, which are crucial for impactful healthcare interventions. His experience in both teaching and research also ensures that his knowledge is applied and shared within the academic community.
  4. Proven Success in Real-World Applications: Alex’s work on reducing HIV patient data duplication, predicting HIV patient outcomes, and improving cervical cancer screening speaks to his practical problem-solving skills in high-stakes environments. The use of AI to improve healthcare decision-making is well-aligned with global trends toward technology-driven health solutions.
  5. Cross-Disciplinary and Global Approach: Alex’s education, spanning institutions in Uganda and South Africa, and his research interests in global health issues, reflect his broad outlook. His involvement with international collaborators highlights his ability to bridge different disciplines and apply his knowledge across borders.

Areas for Improvement:

  1. More Diverse Research Focus: While Alex has concentrated on significant healthcare issues, expanding his research beyond HIV, cancer, and tuberculosis may enhance his portfolio. Including more work in diverse fields, such as environmental health or genomics, would add breadth to his achievements.
  2. Leadership in Research Projects: Alex has demonstrated technical prowess and teaching capabilities, but more emphasis on leadership roles in large-scale research projects or interdisciplinary initiatives could elevate his profile. Leading a significant multi-institutional study or directing larger research teams may help solidify his standing.
  3. Policy and Implementation Impact: Though Alex has made practical contributions, more evidence of his work leading to large-scale policy changes or national-level healthcare implementations could further strengthen his application. This would demonstrate how his AI models or algorithms scale to influence public health strategies at a systemic level.
  4. International Research Collaborations: Although his work is impactful within Uganda, expanding collaborations with more international research institutes or global health organizations could further enhance his visibility and contribution to global health initiatives.

 

Education:

Alex Mirugwe holds an MSc in Data Science from the University of Cape Town, South Africa, completed in 2021, where he conducted research on automated bird detection using machine learning. His academic performance was strong, with a GPA of 74.52%. Prior to this, he earned a BSc in Computer Engineering from Makerere University, Uganda, in 2019, graduating with a CGPA of 4.18/5.0. His undergraduate dissertation focused on developing a low-cost wireless TV audio transceiver, reflecting his early interest in applying engineering principles to real-world problems. His educational background combines technical proficiency in computer science with a strong emphasis on data science and machine learning applications.

Experience:

Alex Mirugwe is a highly skilled data scientist with over four years of experience applying machine learning and AI to healthcare challenges, particularly in diagnosing HIV, cancer, and tuberculosis. He has successfully developed predictive models to improve patient care and outcomes in resource-limited settings, such as creating algorithms for cervical cancer screening and reducing HIV patient data duplication. His work spans both practical implementation and academic research, with multiple publications on AI-driven health interventions. In addition to his research, Alex is an experienced educator, teaching data science and machine learning courses at the university level.

Research Focus:

Alex Mirugwe’s research focuses on leveraging data science and machine learning to address critical healthcare challenges, particularly in resource-constrained settings. His work encompasses developing predictive models for patient care in HIV treatment, enhancing cervical cancer screening accuracy through AI algorithms, and analyzing public sentiment during health crises, such as the Ebola outbreak. Additionally, he explores various applications of AI in public health, including improving tuberculosis detection and reducing data duplication in electronic medical records. Overall, his research aims to harness advanced data analytics to improve patient outcomes and inform public health strategies, making significant contributions to the field of healthcare data science.

Publications Top Notes:

  • Automating Bird Detection Based on Webcam Captured Images Using Deep Learning
    • Authors: A. Mirugwe, J. Nyirenda, E. Dufourq
    • Year: 2022
    • Citations: Not specified in the provided information.
  • Restaurant Tipping Linear Regression Model
    • Author: A. Mirugwe
    • Year: 2020
    • Citations: Not specified in the provided information.
    • Link: SSRNPaper
  • Sentiment Analysis of Social Media Data on Ebola Outbreak Using Deep Learning Classifiers
    • Authors: A. Mirugwe, C. Ashaba, A. Namale, E. Akello, E. Bichetero, E. Kansiime, J. Nyirenda
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Journal: Life, 14(6), 708.
  • Adoption of Artificial Intelligence in the Ugandan Health Sector: A Review of Literature
    • Author: A. Mirugwe
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Link: Available at SSRN 4735326.

Conclusion:

Alex Mirugwe presents an impressive and well-rounded portfolio, with extensive experience in applying machine learning and AI to tackle critical healthcare challenges. His achievements, particularly in HIV care and cancer screening, demonstrate his ability to leverage data science for real-world health outcomes. While he has a strong research and technical background, focusing on leadership, broadening his research scope, and contributing to systemic policy changes could bolster his case further. He is a strong candidate for the Best Researcher Award, especially within the domain of AI-driven healthcare solutions in resource-constrained settings.