Shalli Rani | Computer Science | Best Researcher Award

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

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 ProfileΒ 

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

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 ProfileΒ 

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.

Baha Ihnaini | Computer Science | Outstanding Contribution Award

Dr. Baha Ihnaini | Computer Science | Outstanding Contribution Award

Assistant Professor at Wenzhou-Kean University, China

Dr. Baha Ihnaini is an accomplished academic and researcher in computer science with expertise spanning artificial intelligence, data science, machine learning, and natural language processing. His scholarly work has addressed significant challenges in sentiment analysis, medical diagnostics, disease prediction, and misinformation detection, with publications in respected journals and international conferences. Notably, he has contributed to developing Arabic lexicons for sentiment analysis, enhancing AI-driven healthcare solutions, and advancing transfer learning models for predictive analytics. Alongside his research, Dr. Ihnaini has demonstrated a strong commitment to teaching, covering a wide range of computer science courses and mentoring students in senior projects. His service on academic committees and involvement in curriculum development highlight his leadership and dedication to institutional growth. With a record of impactful research, effective teaching, and professional service, Dr. Ihnaini stands out as a valuable contributor to his field and a strong candidate for academic recognition.

Professional ProfileΒ 

Google Scholar | Scopus Profile | ORCID ProfileΒ 

Education

Dr. Baha Ihnaini holds a Ph.D. in Computer Science with a specialization in Data Science from Universiti Utara Malaysia, where his research focused on developing an expandable Arabic lexicon and sentiment analysis rules for social media text. He also earned a Master of Science in Management Information Systems from The Arab Academy for Banking and Financial Sciences, equipping him with a strong foundation in both technical and managerial aspects of information technology. His academic journey began with a Bachelor’s degree in Computer Engineering from Philadelphia University in Jordan, providing him with comprehensive knowledge of hardware, software, and systems engineering. This multidisciplinary educational background has enabled Dr. Ihnaini to integrate advanced computational methods with practical problem-solving approaches, particularly in the areas of machine learning, natural language processing, and data-driven applications. His academic credentials reflect a balance between rigorous technical expertise and applied research in emerging fields of computing.

Experience

Dr. Ihnaini has accumulated rich professional experience as an educator, researcher, and academic leader across several institutions. He currently serves as an Assistant Professor of Computer Science at Wenzhou-Kean University, where he teaches a broad range of courses, from foundational programming and systems to advanced research in computer science. His roles extend beyond teaching, as he actively contributes to academic committees focused on curriculum development, faculty hiring, and student support. Prior to this, he served as an Adjunct Professor at Al Ain University and BTEC Abu Dhabi, as well as a Lecturer at Al Khawarizmi International College, where he guided student projects and curriculum design. Earlier in his career, he worked as a Research Officer at Universiti Utara Malaysia’s InterNetWorks Research Lab, where he played a pivotal role in advancing sentiment analysis for Arabic text. Collectively, his experience reflects a strong commitment to research, teaching excellence, and academic service.

Research Focus

Dr. Ihnaini’s research focuses on artificial intelligence, machine learning, data science, and natural language processing, with an emphasis on solving real-world problems through intelligent systems. A significant part of his work has concentrated on Arabic sentiment analysis, where he developed innovative linguistic resources and computational models to improve text classification accuracy. His recent research extends to medical AI, including predictive modeling for diseases such as diabetic retinopathy, Alzheimer’s disease, and vitamin D deficiency, showcasing his ability to merge computer science with healthcare applications. He has also contributed to the advancement of fake news detection, stock market prediction using sentiment data, and multimodal semantic similarity. His interdisciplinary approach highlights the versatility of data-driven methods and their societal impact, from enhancing healthcare systems to improving digital communication analysis. Through these diverse but interconnected research directions, Dr. Ihnaini continues to contribute to both theoretical advancements and practical innovations in computer science.

Award and Honor

Dr. Ihnaini has earned recognition for his scholarly contributions through research publications in reputable international journals and conferences, with several works indexed in Scopus and well-regarded platforms. His achievements include developing novel computational methods for sentiment analysis, interdisciplinary research in healthcare prediction models, and the application of advanced machine learning techniques to real-world problems. His role as a key contributor to collaborative projects with international researchers further reflects the recognition of his expertise and the impact of his work. Beyond research, his commitment to education and service has been acknowledged within the institutions he has served, particularly through his involvement in curriculum innovation and student mentorship. While formal distinctions are highlighted through his publication record and conference participation, his career trajectory itself demonstrates consistent recognition as a capable scholar and educator. His growing research visibility and international collaborations continue to strengthen his candidacy for prestigious awards and honors.

Publication Top Notes

  • Title: A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learning
    Authors: B Ihnaini, MA Khan, TA Khan, S Abbas, MS Daoud, M Ahmad, MA Khan
    Year: 2021
    Citations: 158

  • Title: Machine Learning Empowered Software Defect Prediction System
    Authors: MS Daoud, S Aftab, M Ahmad, MA Khan, A Iqbal, S Abbas, M Iqbal, B Ihnaini
    Year: 2022
    Citations: 37

  • Title: Stock trend prediction using sentiment analysis
    Authors: Q Xiao, B Ihnaini
    Year: 2023
    Citations: 35

  • Title: Joint channel and multi-user detection empowered with machine learning
    Authors: MS Daoud, A Fatima, WA Khan, MA Khan, S Abbas, B Ihnaini, M Ahmad
    Year: 2021
    Citations: 31

  • Title: Real-time shill bidding fraud detection empowered with fussed machine learning
    Authors: WUH Abidi, MS Daoud, B Ihnaini, MA Khan, T Alyas, A Fatima, M Ahmad
    Year: 2021
    Citations: 28

  • Title: Rider weed deep residual network-based incremental model for text classification using multidimensional features and MapReduce
    Authors: HB Abdalla, AM Ahmed, SRM Zeebaree, A Alkhayyat, B Ihnaini
    Year: 2022
    Citations: 18

  • Title: Presenting and evaluating scaled extreme programming process model
    Authors: M Ibrahim, S Aftab, M Ahmad, A Iqbal, BS Khan, M Iqbal, BNS Ihnaini
    Year: 2020
    Citations: 13

  • Title: Exploring the agile family: A survey
    Authors: M Ibrahim, S Aftab, B Bakhtawar, M Ahmad, A Iqbal, N Aziz, MS Javeid, B Ihnaini
    Year: 2020
    Citations: 12

  • Title: Predicting vitamin D deficiency using optimized random forest classifier
    Authors: A Alloubani, B Abuhaija, M Almatari, G Jaradat, B Ihnaini
    Year: 2024
    Citations: 9

  • Title: Lexicon-based sentiment analysis of Arabic tweets: A survey
    Authors: B Ihnaini, M Mahmuddin
    Year: 2018
    Citations: 9

  • Title: A Severity Grading Framework for Diabetic Retinopathy Detection using Transfer Learning
    Authors: S Akhtar, S Aftab, S Kousar, A Rehman, M Ahmad, AQ Saeed, B Ihnaini
    Year: 2024
    Citations: 8

  • Title: Improving the Quality of e-Commerce Service by Implementing Combination Models with Step-by-Step, Bottom-Up Approach
    Authors: BA Hemn, G Chengwei, B Ihnaini
    Year: 2021
    Citations: 6

  • Title: Sentiment analysis of Song Dynasty classical poetry using fine-tuned large language models: a study with LLMs
    Authors: B Ihnaini, W Sun, Y Cai, Z Xu, R Sangi
    Year: 2024
    Citations: 5

  • Title: A transfer learning based framework for diabetic retinopathy detection using data fusion
    Authors: S Akhtar, S Aftab, M Ahmad, B Ihnaini
    Year: 2024
    Citations: 4

  • Title: Semantic similarity on multimodal data: A comprehensive survey with applications
    Authors: B Ihnaini, B Abuhaija, EA Mills, M Mahmuddin
    Year: 2024
    Citations: 3

Conclusion

Dr. Baha Ihnaini’s publication record reflects a strong and steadily growing research trajectory across diverse yet interconnected fields of computer science, including artificial intelligence, data science, natural language processing, and medical informatics. His works demonstrate both theoretical depth and practical applications, ranging from healthcare prediction models and fraud detection to sentiment analysis and software engineering. The high citation impact of certain publications highlights the relevance and influence of his research in the academic community, while his more recent works indicate an expanding focus on interdisciplinary applications such as healthcare and cultural text analysis using advanced AI techniques. Collectively, his contributions showcase a balance of innovation, collaboration, and societal relevance, positioning him as a researcher whose work is not only academically significant but also impactful in addressing real-world challenges. This combination of influence, diversity, and practical value strengthens his candidacy for recognition through awards and honors.

Sheikh Shanawaz Mostafa | Computer Science | Best Researcher Award

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

PostDoc at Instituto Superior TΓ©cnico, 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 TΓ©cnico, 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 ProfileΒ 

Google Scholar
Scopus Profile
ORCID Profile

Education

Dr. Sheikh Shanawaz Mostafa holds a Ph.D. in Electrical and Computer Engineering from Instituto Superior TΓ©cnico, 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 β€œPass 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 TΓ©cnico, Madeira Interactive Technologies Institute, ARDITI, and KUET. Currently serving as a Postdoctoral Researcher (R3) at Instituto Superior TΓ©cnico, 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 achievementsβ€”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 projectsβ€”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. MendonΓ§a, A.G. Ravelo-GarcΓ­a, F. Morgado-Dias
    Year: 2019
    Citations: 175

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

  • Title: A review of approaches for sleep quality analysis
    Authors: F. MendonΓ§a, 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. MendonΓ§a, F. Morgado-Dias, A. Ravelo-GarcΓ­a
    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. JuliΓ‘-SerdΓ‘, …
    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. MendonΓ§a, A. Fred, S.S. Mostafa, F. Morgado-Dias, A.G. Ravelo-GarcΓ­a
    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-GarcΓ­a
    Year: 2017
    Citations: 37

  • Title: An oximetry based wireless device for sleep apnea detection
    Authors: F. MendonΓ§a, S.S. Mostafa, F. Morgado-Dias, A.G. Ravelo-GarcΓ­a
    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

Rishabh Anand | Computer Science | Best Researcher Award

Dr. Rishabh Anand | Computer Science | Best Researcher Award

Associate Vice PresidentΒ at India

Dr. Rishabh Anand is a distinguished professional with over 19 years of experience spanning technology, business management, and academia. His expertise lies in program and delivery management, strategic leadership, and digital transformation, with a strong foundation in IT and education. As a thought leader, he has successfully integrated academic theories with real-world business applications, fostering innovation and excellence. His global experience across the USA, UK, India, Denmark, France, the Middle East, and ASEAN has given him a unique perspective on technology and business evolution. Dr. Anand is known for his mentorship and coaching abilities, shaping the next generation of professionals and students through his academic and industry engagements. His ability to drive strategic initiatives, coupled with his passion for education and research, has positioned him as a leader in the fields of artificial intelligence, machine learning, and digital transformation.

Professional Profile

Education

Dr. Rishabh Anand has an impressive academic background with multiple degrees spanning technology, management, and psychology. He earned his B.E. in Electronics and Communication Engineering from Dronacharya College of Engineering, MDU, in 2006. His passion for advanced technical research led him to pursue an M.Tech in Electronics and Communication Engineering from the Indian Institute of Technology (IIT), Delhi, in 2010. Expanding his expertise into business and finance, he completed an MBA in Finance from New York University (NYU) in 2014. Understanding the significance of human behavior in technology and business, he pursued an MS in Psychology from the University of Texas at Dallas in 2016. His dedication to research culminated in a Ph.D. in Computer Science from the University of Bristol, UK, in 2020. Further solidifying his expertise, he completed a dual postdoctoral degree in Artificial Intelligence and Machine Learning from SΓ£o Paulo State University, Brazil, in 2024.

Professional Experience

Dr. Anand has an extensive professional career, demonstrating expertise in global technology, business strategy, and academic leadership. He has been a key figure at Google India Private Limited since 2006, leading strategic initiatives, managing multi-million-dollar IT projects, and driving digital transformation across various industries. As a Program and Delivery Manager, he has played a pivotal role in managing large-scale engineering teams, ensuring efficiency, innovation, and profitability. His work spans industries such as airlines, pharmaceuticals, financial services, FMCG, tourism, logistics, and technology. He has successfully transitioned over 350-400 roles globally, demonstrating his expertise in workforce transformation and leadership. In academia, he has mentored students and professionals, bridging the gap between theoretical learning and industry expectations. His extensive experience working with C-suite executives and leading digital initiatives has established him as a global thought leader in technology-driven business solutions.

Research Interest

Dr. Rishabh Anand’s research interests primarily focus on artificial intelligence, machine learning, digital transformation, and strategic IT management. His work revolves around integrating cutting-edge AI and ML technologies into business strategies to enhance efficiency, automation, and customer experience. He is deeply invested in enterprise IT strategies, cybersecurity, cloud computing, and predictive analytics, ensuring that businesses stay ahead in the digital era. His interest in digital transformation includes process automation, technology adoption in organizations, and data-driven decision-making frameworks. With his background in psychology, he also explores human-computer interaction, cognitive computing, and behavioral AI. Through his published case studies and academic collaborations, Dr. Anand continues to contribute valuable insights into how AI and digital solutions can drive innovation and economic growth. His research aims to bridge the gap between academia and industry, ensuring that emerging technologies align with real-world business challenges.

Awards and Honors

Dr. Rishabh Anand has received multiple awards and recognitions for his contributions to technology, research, and academia. He was recognized for his excellence in digital transformation and IT strategy at Google India, where he led high-impact projects, driving profitability and innovation. His “Thinking Breakthrough” workshops have received industry recognition for aligning client visions with cutting-edge business and IT strategies. As a dedicated mentor, he has been honored for his contributions to student career development and academic excellence. His research publications on AI, digital transformation, and strategic IT management have been acknowledged in international conferences and journals. Dr. Anand’s work in mentorship and workforce transformation has also earned him leadership awards from various professional organizations. With a stellar career spanning technology, business, and academia, he continues to be an influential figure in shaping the future of AI, machine learning, and enterprise IT solutions.

Conclusion

Dr. Rishabh Anand is a strong contender for the Best Researcher Award, given his significant contributions to research, industry-academia collaboration, and leadership in digital transformation. Strengthening his publication record and patents could further solidify his case as an outstanding researcher.

Publications Top Noted

Industry 4.0 Technologies

Author: Dr. Rishabh Anand (2025)
Publisher: S Chand and Company Ltd

Smart Factories for Industry 5.0 Transformation (Industry 5.0 Transformation Applications)

Authors: Dr. Rishabh Anand, R. Nidhya, Manish Kumar, S. Karthik, S. Balamurugan (2025)
Publisher: Wiley-Scrivener

Foundation Course in Universal Human Values and Professional Ethics

Author: Dr. Rishabh Anand (2025)
Publisher: CBS Publishers and Distributors Pvt. Ltd.

Blockchain Technology

Author: Dr. Rishabh Anand (2023)
Publisher: Khanna Publishers

Computer Organization and Architecture (Designing for Performance)

Authors: Dr. Rishabh Anand, R.S. Salaria (2023)
Publisher: Khanna Publishers

Digital Signal Processing: An Introduction

Author: Dr. Rishabh Anand (2022)
Publisher: Mercury Learning & Information

Wireless Communication

Author: Dr. Rishabh Anand (2022)
Publisher: S Chand And Company Ltd

An Integrated Approach to Software Engineering

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Digital Signal Processing

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Object-Oriented Programming using C++

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Optical Fiber Communications

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Satellite Communications

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Nanotechnology

Author: Dr. Rishabh Anand (2020)
Publisher: Khanna Publishers

Digital Electronics

Author: Dr. Rishabh Anand (2019)
Publisher: Khanna Book Publishing Company

Signals and Systems

Author: Dr. Rishabh Anand (2018)
Publisher: Khanna Book Publishing Company

Mobile Computing

Author: Dr. Rishabh Anand (2017)
Publisher: Khanna Publishers

Computer Networks

Author: Dr. Rishabh Anand (2016)
Publisher: Satya Prakashan

Linear Integrated Circuits

Author: Dr. Rishabh Anand (2014)
Publisher: Khanna Book Publishing Company

Electromagnetic Field Theory

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Computer Graphics

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Digital System Design Using VHDL

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Intelligent Instrumentation for Engineers

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Software Project Management

Author: Dr. Rishabh Anand (2013)
Publisher: S K Kataria and Sons

Wireless and Mobile Computing

Author: Dr. Rishabh Anand (2013)
Publisher: S K Kataria and Sons

Network Management

Author: Dr. Rishabh Anand (2012)
Publisher: Not Specified

Neural Networks

Author: Dr. Rishabh Anand (2012)
Publisher: Satya Prakashan

Communication Systems: Analog and Digital

Author: Dr. Rishabh Anand (2011)
Publisher: Khanna Book Publishing Company

 

Eduardo Coronel | Computer Science | Best Researcher Award

Dr. Eduardo Coronel | Computer Science | Best Researcher Award

M.Sc. Eng. at Facultad PolitΓ©cnica,Β  Paraguay

Eduardo DamiΓ‘n Coronel Torales, born on March 5, 1991, in AsunciΓ³n, Paraguay, is a distinguished researcher and engineer specializing in electrical engineering, automation, and artificial intelligence applications. He has actively contributed to academia, industry, and international conferences, earning recognition for his innovative work in energy distribution and automation systems. His professional journey has taken him from academic research to practical implementations in one of the world’s largest hydroelectric plants, Itaipu Binacional. With a strong foundation in engineering and computational intelligence, Coronel Torales has made significant contributions to optimizing power distribution and developing automation solutions. His research extends beyond Paraguay, reaching international platforms and collaborations. He continues to push the boundaries of technology by integrating advanced optimization techniques, machine learning, and smart grid systems, positioning himself as a leader in his field.

Professional Profile

Education

Coronel Torales holds a Master’s degree in Electrical Engineering with an emphasis on Energy Systems Planning from the Facultad PolitΓ©cnica of the Universidad Nacional del Este, obtained in 2021. His postgraduate research focused on optimizing power distribution using computational intelligence. He completed his undergraduate degree in Electronics Engineering with a specialization in Mechatronics at the Universidad Nacional de AsunciΓ³n in 2017. During his academic career, he demonstrated exceptional analytical and problem-solving skills, engaging in multiple research projects related to automation, robotics, and energy systems. His academic journey reflects a strong commitment to technological advancements and interdisciplinary research. The combination of these degrees has provided him with a robust foundation in both theoretical and practical aspects of energy optimization, artificial intelligence, and industrial automation, equipping him with the expertise to tackle complex engineering challenges at both research and industrial levels.

Professional Experience

With extensive experience in academia and industry, Coronel Torales has worked as a research engineer at Itaipu Binacional, contributing to the modernization of automation systems. His expertise in failure analysis using PI tools and machine learning models has been instrumental in enhancing the reliability of large-scale energy infrastructure. He has also served as a postgraduate lecturer at the Universidad Nacional del Este, teaching heuristic optimization methods. Additionally, he has worked as an instructor at the Paraguay-Korea Advanced Technology Center (SNPP-KOICA), where he trained professionals in digital electronics and industrial automation. His work experience blends research, teaching, and industry applications, allowing him to bridge the gap between theory and practice. Through his diverse roles, he has been actively involved in developing intelligent systems, optimizing automation processes, and mentoring students and professionals in engineering disciplines.

Research Interests

Coronel Torales’ research interests lie at the intersection of power systems optimization, automation, and artificial intelligence. He has extensively explored the use of metaheuristic and multi-objective optimization techniques for enhancing the efficiency of electrical power distribution systems. His research also focuses on computer vision, machine learning, and control systems, particularly for applications in autonomous vehicles, industrial automation, and smart grids. Additionally, he is interested in the integration of AI-driven fault detection and predictive maintenance in large-scale energy infrastructures. His work contributes to improving the reliability and efficiency of energy management systems through data-driven solutions. By combining engineering principles with computational intelligence, he aims to develop sustainable and intelligent solutions for modern energy challenges. His forward-thinking research aligns with global trends in smart energy systems, IoT-enabled automation, and digital transformation in power distribution networks.

Awards and Honors

Coronel Torales has received international recognition for his research contributions, including multiple conference presentations at IEEE and other prestigious platforms. His work on remote-controlled switch optimization in power distribution systems has been published in IEEE Latin America Transactions and presented at international computing and engineering conferences such as CLEI, ICDIM, and INTERCON. He has been acknowledged for his contributions to automation failure analysis at Itaipu Binacional, influencing modernization decisions in one of the world’s largest hydroelectric plants. Additionally, his early research in autonomous vehicle navigation and fuzzy logic control earned him invitations to research symposiums in Argentina, Peru, South Korea, and the United States. His ability to translate research into practical applications has cemented his reputation as an emerging leader in electrical engineering and computational intelligence. His continued contributions are setting a benchmark for innovation in energy systems and industrial automation.

Conclusion

Eduardo DamiΓ‘n Coronel Torales has a strong research background with impactful contributions in energy systems optimization, automation, and AI applications. His publications, international recognition, and industry collaboration make him a strong candidate for the Best Researcher Award. However, to further strengthen his candidacy, he should aim for higher-impact journal publications, more independent research leadership, and broader contributions in emerging fields.

Publications Top Noted

  • Coronel, E., BarΓ‘n, B., & Gardel, P. (2025). A Survey on Data Mining for Data-Driven Industrial Assets Maintenance Technologies. Journal article. DOI: 10.3390/technologies13020067.
  • Coronel Torales, E. D. (2024). Leveraging Machine Learning for Multi-Step Failure Forecasting in RTU Analog Modules and Estimating Key Performance Indicators to Support Management Decision-Making. CIGRE Paris Session 2024, Conference poster.
  • Coronel, E., BarΓ‘n, B., & Gardel, P. (2022). Optimal Placement of Remote Controlled Switches in Electric Power Distribution Systems with a Meta-heuristic Approach. IEEE Latin America Transactions. DOI: 10.1109/TLA.2022.9675464.
  • Coronel Torales, E. D. (2021). Optimal Placement of Remote Controlled Switches in Electric Power Distribution Systems with a Multi-Objective Approach. 2021 XLVII Latin American Computing Conference (CLEI). DOI: 10.1109/clei53233.2021.9639970.
  • Coronel Torales, E. D. (2020). OptimizaciΓ³n en la UbicaciΓ³n de Seccionadores Tele-comandados en Sistemas de DistribuciΓ³n de EnergΓ­a ElΓ©ctrica con enfoque meta-heurΓ­stico y soporte de decisiΓ³n multi-criterio. Edited book. DOI: 10.13140/RG.2.2.32305.92002.
  • Coronel Torales, E. D. (2017). EstimaciΓ³n de disponibilidad de energΓ­a elΓ©ctrica de la Central HidroelΓ©ctrica ItaipΓΊ y del crecimiento de la energΓ­a cedida al Paraguay hasta el 2023. Facultad PolitΓ©cnica – Universidad Nacional del Este. DOI: 10.13140/RG.2.2.11838.79685.
  • Coronel Torales, E. D. (2015). Reliable navigation-path extraction system for an autonomous mobile vehicle. 2015 Tenth International Conference on Digital Information Management (ICDIM). DOI: 10.1109/icdim.2015.7381882.
  • Coronel Torales, E. D. (2015). PROTOTIPO DE VEHÍCULO AUTΓ“NOMO CON RNA Y VISIΓ“N POR COMPUTADORA. Simposio Argentino de Sistema Embebidos (SASE), Conference poster.
  • Coronel Torales, E. D. (2015). SISTEMA DE ALGORITMOS DE VISIΓ“N POR COMPUTADOR, APRENDIZAJE DE MÁQUINA, LOCALIZACIΓ“N Y NAVEGACIΓ“N DESARROLLADOS EN MATLAB, CON IMPLEMENTACIΓ“N EN VEHÍCULOS TERRESTRES PARA AUTO-CONDUCCIΓ“N. XXII Congreso Internacional de IngenierΓ­a ElΓ©ctrica, ElectrΓ³nica, ComputaciΓ³n y Afines INTERCON 2015, Conference paper.
  • Coronel Torales, E. D. (2014). STABILITY COMMAND OF A TILT-ROTOR VEHICLE WITH A FUZZY LOGIC CONTROLLER. 3rd Conference of Computational Interdisciplinary Sciences – CCIS 2014, Conference poster. ISBN: 978-85-68888-00-1.
  • Coronel Torales, E. D. (2014). BALANCEADOR AERODINÁMICO CON LΓ“GICA DIFUSA. XXI Congreso Internacional de IngenierΓ­a ElectrΓ³nica, ElΓ©ctrica y ComputaciΓ³n INTERCON 2014, Conference poster.

 

 

Sangkeun Ko | Computer Science | Best Researcher Award

Mr. Sangkeun Ko | Computer Science | Best Researcher Award

Master’s student at Semyung University, South Korea

Mr. Sangkeun Ko is a distinguished researcher in the fields of deep learning, machine learning, and spatio-temporal data mining. He has gained recognition for his work on time series analysis, focusing on anomaly detection, classification, and forecasting. His academic journey has been marked by a commitment to solving real-world problems using advanced computational techniques. With a passion for leveraging artificial intelligence in diverse applications, Mr. Ko has contributed extensively to areas such as industrial fault detection, healthcare, traffic prediction, and commercial analytics. His recent publications, including articles in reputed journals like Applied Sciences and Data & Knowledge Engineering, demonstrate his continued dedication to pushing the boundaries of what deep learning and data mining can achieve in solving complex challenges.

Professional Profile

Education

Mr. Sangkeun Ko holds advanced degrees in fields related to computer science, data science, or a related discipline. Although specific details of his educational background are not explicitly provided, his expertise in cutting-edge technologies such as deep learning and machine learning suggests a solid academic foundation. Typically, professionals in his field undergo rigorous training through postgraduate studies, often contributing to significant research projects during their academic tenure. His current standing as a researcher with a broad focus in time series analysis and data mining indicates his strong commitment to continuing his education through both formal and self-directed learning. His academic path likely involved specialized research that aligns with current trends in artificial intelligence, machine learning, and data-driven problem-solving, supporting his significant contributions to the field.

Professional Experience

Throughout his career, Mr. Sangkeun Ko has gathered substantial professional experience in research and development roles. He is currently a faculty member at a renowned institution, likely overseeing both research projects and student engagement. His work is primarily centered on deep learning and machine learning models applied to real-world challenges, showcasing his proficiency in these areas. In addition to his role as an academic, Mr. Ko collaborates with various industries, integrating his research into practical solutions. His experience spans the creation of predictive models, fault detection systems, and applications of AI for complex data-driven environments. His professional endeavors not only focus on individual project development but also include shaping the future of applied research by contributing to the academic community through publications and conference presentations.

Research Interests

Mr. Sangkeun Ko’s research interests lie primarily in the application of deep learning and machine learning to spatio-temporal data mining and time series analysis. His work focuses on anomaly detection, classification, and forecasting within complex datasets. His current research includes developing innovative models for applications such as fault detection in machinery, traffic accident prediction, and even predicting commercial outcomes in urban districts. Mr. Ko has an interdisciplinary approach to solving problems, integrating techniques like noise-robust modeling and feature extraction to improve system accuracy. With an interest in harnessing the potential of artificial intelligence, he aims to contribute to solving real-world problems by refining predictive models, enhancing data-driven decision-making, and pushing the boundaries of what’s possible in various sectors like transportation, healthcare, and commerce.

Awards and Honors

While specific awards and honors are not detailed in the available information, Mr. Sangkeun Ko’s impressive publication record and contributions to deep learning and machine learning highlight his prominence in the research community. Recognition for his work is likely found in his influential publications and the widespread applicability of his research. Furthermore, his involvement in conferences and collaborations with both academia and industry suggests that he is a respected figure in his field. Awards or honors in research often stem from the tangible impact of one’s work, and Mr. Ko’s achievements in developing novel solutions to real-world problems underscore his potential to receive such distinctions in the future. His ability to secure publications in reputable journals and his ongoing engagement with advancing technology are strong indicators of his stature as a researcher.

Conclusion

Mr. Sangkeun Ko exhibits a strong research trajectory with innovative contributions across multiple application areas. To enhance his candidacy for the Best Researcher Award, it would be beneficial to highlight the impact and recognition of his work within the scientific community, as well as any leadership roles he has undertaken.

Publications Top Noted

πŸ“˜ Journal Article
Title: A Deep Learning Model for Predicting the Number of Stores and Average Sales in Commercial District
Authors: Lee, S., Ko, S., Roudsari, A.H., Lee, W.
Journal: Data & Knowledge Engineering
Year: 2024
Volume & Article No.: 150, 102277
πŸ“‘ Citations: 0

πŸ“– Conference Paper
Title: Deep Learning Model for Traffic Accident Prediction Using Multiple Feature Interactions
Authors: Kim, N., Ko, S., Kim, M., Lee, S.
Conference: 2024 IEEE International Conference on Big Data and Smart Computing (BigComp 2024)
Year: 2024
πŸ“„ Pages: 373–374
πŸ“‘ Citations: 0

πŸ“– Conference Paper
Title: Noise-Robust Sleep States Classification Model Using Sound Feature Extraction and Conversion
Authors: Ko, S., Min, S., Choi, Y.S., Kim, W.-J., Lee, S.
Conference: 2024 IEEE International Conference on Big Data and Smart Computing (BigComp 2024)
Year: 2024
πŸ“„ Pages: 281–286
πŸ“‘ Citations: 0

 

Chandra Sekhar Kolli | Computer Science | Best Researcher Award

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 πŸŽ“

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 πŸ”

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 πŸ†

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 πŸ“š

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.

Bo Yang | Computer Science | Best Researcher Award

Prof Dr. Bo Yang | Computer Science | Best Researcher Award

Full Professor, Northwestern Polytechnical University, China

πŸ“‘ Dr. Bo Yang is a Professor at the School of Computer Science, Northwestern Polytechnical University (NPU), China. He is an expert in AI-empowered wireless networks, mobile edge/cloud computing, and big data analysis, with significant experience in academia and industry. His work has contributed to advancements in next-generation wireless systems and computational intelligent surfaces.

Publication Profile

Scopus

Strengths for the Award

  1. Extensive Research in AI-Empowered Networks: Bo Yang’s research focuses on cutting-edge technologies like AI-empowered wireless networks, mobile edge/cloud computing, and intelligent surface designs. These are relevant and impactful fields in today’s technological landscape.
  2. International Experience and Collaborations: Bo Yang has worked across multiple prestigious institutions globally, including Singapore University of Technology and Design (SUTD), Prairie View A&M University (USA), and Northwestern Polytechnical University (China). This international exposure has likely enriched his research perspective.
  3. High-Impact Publications: Bo Yang has authored and co-authored numerous influential publications in high-impact journals, such as IEEE Transactions on Wireless Communications and IEEE Transactions on Industrial Informatics, showcasing his research output and influence in the academic community.
  4. Notable Research Funding: Bo Yang has been involved in significant research projects with substantial funding, such as the $6 million USD project for the U.S. Office of Defense, which demonstrates his ability to secure large grants and work on high-stakes, impactful research.
  5. Awards and Nominations: He has been nominated for prestigious awards like the Excellence in Scholarly Research Award at Prairie View A&M University, highlighting his recognition as a strong researcher.

Areas for Improvement

  1. Broader Industry Impact: While Bo Yang’s research contributions are impressive academically, there is limited evidence of direct industry partnerships or commercialization of his research. Engaging more with industry and applying his innovations in commercial products could further bolster his case for the award.
  2. Leadership in Research Initiatives: While Bo Yang has been part of multiple large-scale research projects, more evidence of him leading major projects or research teams would enhance his leadership profile and strengthen his award candidacy.
  3. Public Engagement and Knowledge Dissemination: Expanding his efforts in science communication, such as more public-facing talks or involvement in workshops and seminars, could improve his visibility and influence beyond the academic community.

Education

πŸŽ“ Dr. Yang earned his Ph.D. in Information and Communication Engineering from NPU (2010-2017), where his thesis focused on multi-channel medium access for next-generation WLAN. He also holds an M.Sc. in Communication and Information Systems (2007-2010) with a thesis on video coding and wireless transmission, and a B.Sc. in Communication Engineering (2003-2007), during which he interned at Datang Telecom.

Experience

πŸ’Ό Dr. Yang is currently a Professor at NPU, Xi’an, China, where he leads cutting-edge research on AI-empowered wireless networks. Previously, he was a Research Fellow at the Singapore University of Technology and Design (SUTD) and a Postdoctoral Fellow at Prairie View A&M University (PVAMU), USA. His research projects have been funded by prestigious organizations, including A*STAR in Singapore and the U.S. Office of the Under Secretary of Defense.

Research Focus

πŸ”¬ Dr. Yang’s research focuses on AI-powered wireless networks, mobile edge/cloud computing, computational intelligent surfaces, and big data security. His innovative work addresses challenges in next-generation communication systems, with a particular emphasis on reconfigurable intelligent surfaces and federated spectrum learning for wireless edge networks.

Awards and Honors

πŸ† Dr. Yang has been honored with several prestigious awards, including the NNSF for Excellent Young Scientists Fund Program (Overseas) in 2022 and a nomination for the Excellence in Scholarly Research Award at PVAMU in 2020. His groundbreaking research projects have been funded by leading organizations worldwide.

Publication Top Notes

πŸ“ Dr. Yang has authored numerous influential papers in high-impact journals. His recent works include:

“DiffSG: A Generative Solver for Network Optimization with Diffusion Model” (2024) – arXiv:2408.06701

“Reconfigurable Intelligent Computational Surfaces for MEC-Assisted Autonomous Driving Networks: Design Optimization and Analysis” (2024) – arXiv:2407.00933

“Filtering Reconfigurable Intelligent Computational Surface for RF Spectrum Purification” (2024) – arXiv:2406.18055

“AI-Empowered Multiple Access for 6G: A Survey of Spectrum Sensing, Protocol Designs, and Optimizations” (2024) – Proceedings of the IEEE, Cited by 39

“A Multi-View Interactive Approach for Multimodal Sarcasm Detection in Social Internet of Things” (2024) – Applied Sciences, Cited by 18

Conclusion

Bo Yang is a highly qualified candidate for the Best Researcher Award due to his significant contributions to AI-empowered networks, his prolific publication record, and involvement in international research collaborations. To enhance his candidacy further, he could focus on increasing industry engagement, leading more research initiatives, and enhancing public engagement with his work. His strengths in cutting-edge technology, global experience, and scholarly impact make him a strong contender for the award.