Ferdib Al Islam | Machine Learning | Excellence in Research

Mr. Ferdib Al Islam | Machine Learning | Excellence in Research

Assistant Professor, Northern University of Business and Technology Khulna Bangladesh

Ferdib-Al-Islam is an Assistant Professor at Northern University of Business and Technology Khulna, Bangladesh. He holds a Masterā€™s and Bachelorā€™s degree in Computer Science and Engineering from Khulna University of Engineering & Technology (KUET) and Bangabandhu Sheikh Mujibur Rahman Science and Technology University (BSMRSTU), respectively. His research expertise encompasses Machine Learning, Deep Learning, IoT, Data Science, and Computer Vision. Ferdibā€™s career includes experience as a software engineer in IoT R&D and lecturer roles, contributing significantly to academic and research pursuits.

Publication Profile

Google Scholar

šŸŽ“ Education

M.Sc. Eng. in Computer Science and Engineering from KUET (2023) ā€“ GPA: 3.50. B.Sc. Eng. in Computer Science and Engineering from BSMRSTU (2018) ā€“ GPA: 3.55. HSC in Science from Govt. PC College, Bagerhat (2012) ā€“ 5.00. SSC in Science from Bagerhat Govt. Secondary School (2010) ā€“ 5.00

šŸ’¼ Experience

Ferdib has progressed from an intern to a Senior Lecturer, and now an Assistant Professor at Northern University of Business and Technology Khulna. He served as a Lecturer in Computer Science and Engineering from March 2020 to January 2024. His career also includes a Jr. Software Engineer role at W3 Engineers Ltd. in the IoT R&D sector. Ferdib brings practical industry experience into his academic roles, fostering innovation and research.

šŸ† Awards & Honors

Ferdib has earned notable accolades, including the Gold Award at Semarak International Research Article Competition III 2024 for his work on Autism Spectrum Disorder detection. He also received the Best Paper Award at ICETIS 2021 for his research on Diabetes Mellitus prediction and the Honorable Mention Award at BDML 2020 for his IoT-based health monitoring tool.

šŸ”¬ Research Focus

Ferdibā€™s primary research interests are in Machine Learning, Deep Learning, IoT, Large Language Models, and Computer Vision. His work focuses on the application of AI techniques to healthcare, predictive modeling, and intelligent systems. His aim is to leverage machine learning for real-world applications like healthcare diagnostics, smart monitoring systems, and data-driven insights in various fields.

Conclusion

Ferdib Al-Islam is an exceptional researcher with notable accomplishments in machine learning, deep learning, and IoT. His commitment to advancing knowledge in these areas, demonstrated by his numerous awards and research contributions, marks him as a leading figure in his field. However, fostering greater interdisciplinary collaborations and increasing his global academic presence will be beneficial for his continued growth as a researcher. He is undoubtedly a deserving candidate for the Excellence in Research award, given his dedication, achievements, and potential for further contributions to the scientific community.

Publication Top Notes

  • Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam, MM Islam, MS Al-Rakhami, MR Haque
    • Citation: 73
  • An IoT Enabled Health Monitoring Kit Using Non-Invasive Health Parameters
    • Year: 2021
    • Authors: A Das, SD Katha, MS Sadi, Ferdib-Al-Islam
    • Citation: 31
  • Hepatocellular Carcinoma Patientā€™s Survival Prediction Using Oversampling and Machine Learning Techniques
    • Year: 2021
    • Authors: Ferdib-Al-Islam, L Akter, MM Islam
    • Citation: 21
  • An Enhanced Stroke Prediction Scheme Using SMOTE and Machine Learning Techniques
    • Year: 2021
    • Authors: Ferdib-Al-Islam, M Ghosh
    • Citation: 20
  • Early Identification of Parkinson’s Disease from Hand-drawn Images using Histogram of Oriented Gradients and Machine Learning Techniques
    • Year: 2020
    • Authors: Ferdib-Al-Islam, L Akter
    • Citation: 19
  • Dementia Identification for Diagnosing Alzheimer’s Disease using XGBoost Algorithm
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam
    • Citation: 17
  • COV-VGX: An automated COVID-19 detection system using X-ray images and transfer learning
    • Year: 2021
    • Authors: P Saha, MS Sadi, OFMRR Aranya, S Jahan, FA Islam
    • Citation: 9
  • Detection of Hepatitis C Virus Progressed Patientā€™s Liver Condition Using Machine Learning
    • Year: 2022
    • Authors: Ferdib-Al-Islam, L Akter
    • Citation: 6*
  • Diabetes Mellitus Prediction and Feature Importance Score Finding Using Extreme Gradient Boosting
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam
    • Citation: 4
  • COV-Doctor: A Machine Learning Based Scheme for Early Identification of COVID-19 in Patients
    • Year: 2022
    • Authors: Ferdib-Al-Islam, M Ghosh
    • Citation: 3*
  • Breast Cancer Risk Prediction Using Different Clustering Techniques
    • Year: 2022
    • Authors: L Akter, M Raihan, M Raihan, M Sarker, M Ghosh, N Alvi, Ferdib-Al-Islam
    • Citation: 3
  • Crop-RecFIS: Machine Learning Classifiers for Crop Recommendation and Feature Importance Scores Calculation
    • Year: 2023
    • Authors: MS Sanim, KM Hasan, MM Alam, MAA Walid, MR Islam
    • Citation: 2
  • Prediction of Dementia Using SMOTE Based Oversampling and Stacking Classifier
    • Year: 2023
    • Authors: Ferdib-Al-Islam, MS Sanim, MR Islam, S Rahman, R Afzal, KM Hasan
    • Citation: 2*
  • An Ensemble Learning Model to Detect COVID-19 Pneumonia from Chest CT Scan
    • Year: 2022
    • Authors: PC Shill
    • Citation: 2

 

 

 

Alaa Ali S Almohanna | Information Technology | Best Researcher Award

Dr. Alaa Ali S Almohanna | Information Technology | Best Researcher Award

Dr at University of Wollongong, Australia

Alaa Almohanna is an early-career researcher with a PhD in Computing and Information Technology from the University of Wollongong, Australia. His expertise lies in Artificial Intelligence (AI), persuasive technology, and health informatics. Alaa is passionate about using AI to improve healthcare outcomes and mitigate bias in big data. As a researcher and teacher, he contributes to projects that promote equity in healthcare AI and fosters innovation in tech-driven healthcare solutions. He is committed to advancing knowledge and creating practical solutions to complex healthcare challenges.

Profile

Scopus

Orcid

Scholar

šŸŽ“ Education

Alaa holds a PhD in Computing and Information Technology (2024) from the University of Wollongong, Australia, where he also completed his MSc in Computer Science, Software Engineering (2015). He earned his Bachelor’s in Computer Science and Engineering (2008) from Taibah University, Saudi Arabia. Alaa’s academic journey reflects a strong foundation in computing, software engineering, and health-related technologies, preparing him for impactful research in the field of AI and health informatics.

šŸ’¼ Experience

Alaa has worked as an Associate Researcher and Research Assistant at the University of Wollongong, contributing to projects focused on AI in healthcare. He has also been a part-time teaching staff member, developing innovative content and fostering inclusive learning environments. His research has involved operationalizing diversity in healthcare datasets and creating health-tech policy recommendations. He has worked on AI-related healthcare projects for the Australian Commission on Safety and Quality in Health Care, significantly impacting health governance.

šŸ† Awards and Honors

Alaa received the Best Paper Award at the 18th International Conference on Persuasive Technology (PERSUASIVE 2023) for his exceptional research in persuasive technology. He also earned High Distinction in research training skills subjects and received recognition for his research contributions to AI in healthcare. Alaa’s dedication to advancing the field of health informatics and AI has been acknowledged by peers and institutions alike, further highlighting his commitment to academic excellence and research innovation.

šŸ”¬ Research Focus

Alaa’s research focuses on AI and persuasive technology, particularly in healthcare. He aims to address issues of data diversity and bias in healthcare AI systems. His studies include the development of mHealth apps to promote breastfeeding and healthcare decision-making. Alaa’s work extends to evaluating user experiences, promoting equitable AI, and contributing to healthcare policy development. His ongoing research explores how AI can improve patient outcomes while minimizing biases and ensuring fairness in healthcare delivery systems.

Conclusion

Alaa Almohanna is a highly capable and innovative researcher with a demonstrated track record of excellence in both research and teaching. His contributions to AI in healthcare, along with his recognition through prestigious awards, position him as a strong contender for the Best Researcher Award. His continued focus on operationalizing diversity and improving healthcare technologies promises to create a lasting impact on the field. With a potential for broader collaboration and further pedagogical development, Almohanna is poised for significant academic and professional growth.

šŸ“šPublicationsĀ 

  1. Effectiveness of internet-based electronic technology interventions on breastfeeding outcomes: systematic review
    • Journal: Journal of Medical Internet Research
    • Date: 2020
    • DOI: e17361
    • Authors: AA Almohanna, KT Win, S Meedya

 

  1. Design and content validation of an instrument measuring user perception of the persuasive design principles in a breastfeeding mHealth app: A modified Delphi study
    • Journal: International Journal of Medical Informatics
    • Date: 2022
    • DOI: 104789
    • Authors: AAS Almohanna, KT Win, S Meedya, E Vlahu-Gjorgievska

 

  1. A study of womenā€™s perceptions and opinions of a persuasive breastfeeding mHealth app
    • Conference: International Conference on Persuasive Technology
    • Date: 2023
    • Pages: 142-157
    • Authors: AAS Almohanna, S Meedya, E Vlahu-Gjorgievska, KT Win

 

  1. Exploring User Experiences with a Persuasive mHealth App for Breastfeeding: An Empirical Investigation
    • Journal: International Journal of Humanā€“Computer Interaction
    • Date: 2024
    • Pages: 1-18
    • Authors: AAS Almohanna, S Meedya, E Vlahu-Gjorgievska, KT Win

 

  1. Operationalising data diversity for equitable artificial intelligence: A scoping review of health governance frameworks
    • Event: The Australasian Association of Bioethics and Health Law (AABHL) 2024 Conference
    • Date: 2024
    • Authors: AAS Almohanna, KT Win, AN Aguirre, YSJ Aquino

 

  1. Literature Review and Environmental Scan Report: AI Implementation in Hospitals: Legislation, Policy, Guidelines and Principles, and Evidence about Quality and Safety
    • Source: Australian Commission on Safety and Quality in Health Care
    • Date: 2024
    • Authors: F Magrabi, L Bates, K Brooke-Cowden, T Jayawardena, A Wang

 

  1. Exploring Persuasive System Design Features and Usersā€™ Perceptions of an mHealth Breastfeeding App: A Mixed-Method Study
    • Date: 2024
    • Author: AAS Almohanna

 

Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

Mr. Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

Mr at Shahid beheshti university Iran

Nastaran Mehrabi Hashjin is a researcher and engineer with a background in control and electronic engineering. She specializes in AI, medical imaging, and brain-computer interfaces. With a focus on diagnosing Alzheimer’s disease and optimizing AI algorithms, she has published multiple articles in top-tier journals. Nastaran has also contributed to UAV monitoring and fault detection in power systems. A member of Iranā€™s National Elite Foundation, she actively engages in research on neural networks, optimization algorithms, and advanced medical data processing. She is proficient in programming, circuit design, and VLSI systems, showcasing her technical acumen.

Profile

Scopus

Orcid

Scholar

šŸŽ“ Education

Ph.D. Candidate, Control Engineering (2023-2024) Shahid Beheshti University, Tehran, Iran | Elite Foundation Member. M.Sc. in Control Engineering (2021-2024) Shahid Beheshti University, Tehran, Iran | GPA: 3.54/4.0 | Alzheimerā€™s diagnosis using neural networks. B.Sc. in Electronic Engineering (2016-2020) Shomal University, Amol, Iran | GPA: 3.52/4.0 | PIR sensor system design

šŸ’¼ Experience

Graduate: System Identification, Non-linear Control, Modern Systems. Undergraduate: Electromagnetism, Electrical Machines, Labs Engineer, Tarashe Pardazane Jahan. Designed electronic circuits for smart doors. Intern, Mazandaran Electric Company. Energy distribution monitoring and operational map updates.

šŸ† Awards and Honors

Member, Iranā€™s National Elite Foundation. Ph.D. admission via Elite Foundation. Certifications in neuroscience and medical imaging (TUMS). Advanced neuroscience and AI courses (Shahid Beheshti University)

šŸ”¬ Research Focus

AI-driven fault detection in power plants. Brain-computer interfaces and Alzheimer’s diagnostics. Optimization algorithms: Type-3 fuzzy logic, HO algorithm. Medical imaging: FSL, CONN, Freesurfer

šŸŒŸ Conclusion

Nastaran Mehrabi Hashjin is an exemplary candidate for the Best Researcher Award due to their innovative contributions to AI-driven fault diagnosis, optimization, and medical imaging. Their rigorous academic record, diverse expertise, and impactful publications make them a strong contender. Addressing minor gaps in global collaboration and community engagement will further enhance their standing as a leader in their field.

Publications šŸ“š

Bhanu Shrestha | Computer Science | Best Researcher Award

Prof. Bhanu Shrestha | Computer Science | Best Researcher Award

Professor at Kwangwoon University, South Korea

Bhanu Shrestha is a Full Professor at Kwangwoon University, Korea. He holds expertise in electronic engineering with a background in various academic and professional roles, including Assistant and Associate Professorships at the same institution. A native of Nepal, he is passionate about research, education, and cultural exchange. Bhanu has also published books, research papers, and contributed to documentaries and music albums. His involvement extends to editorial positions, being Editor-in-Chief of the International Journal of Advanced Engineering since 2018. He is known for his academic and social contributions, particularly in the field of information technology and engineering.

 

Profile

Scopus

Orcid

Ā šŸŽ“ Education

Ph.D. in Electronic Engineering, Kwangwoon University, Seoul, Korea (2004-2008). M.S. in Electronic Engineering, Kwangwoon University, Seoul, Korea (2002-2004). B.S. in Electronic Engineering, Kwangwoon University, Seoul, Korea (1994-1998). S.L.C. from Bhim Secondary School, Dolakha, Nepal (1982)

šŸ’¼ Experience

Adjunct Professor, Kwangwoon University, Korea (2008-2011). Assistant Professor, Kwangwoon University, Korea (2011-2016). Associate Professor, Kwangwoon University, Korea (2016-2021). Full Professor, Kwangwoon University, Korea (2021-Present). Bhanu Shrestha has held various academic positions, contributing significantly to the field of electronic engineering and nurturing the next generation of engineers. He has also been involved in leadership roles in professional organizations.

šŸ† Awards and Honors

Achievement Award, IIBC Korea (2015). Best Paper Award, ISSAC 214 & ICACT 2014, IIBC, Seoul, Korea (2014). Excellent Paper Award, Korea Institute of Information Technology (2012). Certificate of Honorary Citizenship, Seong-buk District Office, Seoul, Korea (2012). Bellwave Excellent Paper Award, Korea Electromagnetic Engineering Society (2005). Vidhyabhusan Padak (Gold Medal), Nepal (2009) Bhanu has earned several prestigious awards, recognizing his academic excellence and contributions to research and development in engineering.

šŸ”¬ Research Focus

Bhanu Shrestha’s research interests include Internet of Things (IoT), artificial intelligence (AI), microelectromechanical systems (MEMS), and fuzzy logic applications in communication technology. His work also explores biosensors and nanotechnology for environmental remediation. As a guest editor for multiple journals, Bhanu’s research aims to push the boundaries of innovation in electronic engineering and its practical applications, particularly in smart systems and AI.

Conclusion

Bhanu Shresthaā€™s contributions to electronic engineering and technology, coupled with his leadership in academia, make him a highly deserving candidate for the Best Researcher Award. His accomplishments in publishing influential works, along with his global impact in the fields of artificial intelligence, IoT, and nanotechnology, showcase his research excellence. With continued collaboration and expansion into emerging areas, he is well-positioned to make even more significant strides in the scientific community, further cementing his legacy as a top researcher.

Publications šŸ“š

Rouholla Bagheri| Deep Learning | Best Researcher Award

Assoc Prof Dr. Rouholla Bagheri | Thermodynamics | Best Researcher Award

Assoc Prof Dr. Ferdowsi University of Mashhad Iran

Dr. Rouholla Bagheri is an Assistant Professor in the Department of Management at Ferdowsi University of Mashhad, Iran. He holds a Ph.D. in Systems Management from Shahid Beheshti University, focusing on knowledge networks in the automotive sector. With a distinguished academic record, Dr. Bagheri has received numerous awards, including the 26th National Outstanding Student Award. His research interests span IoT healthcare systems, supply chain networks, and multi-objective optimization. An active member of various professional associations, he has published extensively in peer-reviewed journals, contributing significantly to the fields of information systems and management.

 

Publication profile

 

šŸŽ“ Educational Background

Ph.D. in Systems Management (2013-2018) Shahid Beheshti University, Iran Dissertation: Design a Model of Developing Knowledge Networks in the Car Engine Research Center, GPA: A+. MBA (2012) Amirkabir University, Iran, GPA: A. B.Eng. in Computer Software Engineering (2005)
Bahonar University, Iran, GPA: B

šŸ“š Current Professional Memberships

Member, International Scientific Committee and Editorial Review Board, World Academy of Science, Engineering, and Technology. Member, Council of Knowledge Management in Iran. Member, AIS (Association for Information Systems) of Iran. Member, AKS (Association for Knowledge Management) of Iran. Head, Business Intelligence Department, Association of Management of Iran

šŸ† Honors and Awards

Distinguished Assistant Professor, Ferdowsi University (2022). National Outstanding Student Award Winner (2012, 2017). National Science Foundation Award (2013). Book of the Year Award in Information Systems and Management (2010)

Publication

    1. Assessing dimensions influencing IoT implementation readiness in industries: A fuzzy DEMATEL and fuzzy AHP analysis
      Authors: MZ Nezhad, J Nazarian-Jashnabadi, J Rezazadeh, M Mehraeen, …
      Year: 2023

     

    1. BERT-deep CNN: State of the art for sentiment analysis of COVID-19 tweets
      Authors: JH Joloudari, S Hussain, MA Nematollahi, R Bagheri, F Fazl, …
      Year: 2023

     

    1. The mediator role of KM process for creative organizational learning case study: knowledge based companies
      Authors: R Bagheri, MR Hamidizadeh, P Sabbagh
      Year: 2015

     

    1. Examining the impact of product innovation and pricing capability on the international performance of exporting companies with the mediating role of competitive advantage
      Authors: J Rezazadeh, R Bagheri, S Karimi, J Nazarian-Jashnabadi, MZ Nezhad
      Year: 2023

     

    1. The relationship of knowledge management and organizational performance in Science and Technology Parks of Iran
      Authors: MA Haghighi, R Bagheri, PS Kalat
      Year: 2015

     

    1. The Evaluation of Knowledge Management Maturity Level in a Research Organization
      Authors: R Bagheri, P Eslami, S Mirfakhraee, M Yarjanli
      Year: 2013

     

    1. Factors affecting the implementation of the blue ocean strategy: A case study of Medicom production manufacturing company
      Authors: R Bagheri, SP Eslami, M Yarjanli, N Ghafoorifard
      Year: 2013

     

    1. Modelling the factors affecting the implementation of knowledge networks
      Authors: A Rezaeian, R Bagheri
      Year: 2017

     

    1. Revolutionizing supply chain sustainability: An additive manufacturing-enabled optimization model for minimizing waste and costs
      Authors: P Roozkhosh, A Pooya, O Soleimani Fard, R Bagheri
      Year: 2024

     

    1. Robust cooperative maximal covering location problem: A case study of the locating Tele-Taxi stations in Tabriz, Iran
      Authors: H Rezazadeh, S Moghtased-Azar, MS Kisomi, R Bagheri
      Year: 2018

     

    1. Examining the Relationship between organizational Climate and Entrepreneurship with regard to Staffā€™s Locus of Control in Industry Companies in Iran
      Authors: R Bagheri, M Yarjanli, R Mowlanapour, N Mahdinasab
      Year: 2016

     

    1. Investigating the Effect of Perceived Ethical Leadership on Knowledge Hiding: A Case Study on an Automobile Factory
      Authors: F Imani, G Eslami, R Bagheri
      Year: 2022

    Conclusion šŸŽ“

    Rouholla Bagheri exemplifies the qualities of a strong candidate for the Best Researcher Award, with a robust educational background, a significant publication portfolio, and numerous accolades. By focusing on applied research, enhancing collaborative efforts, and increasing public engagement, he can further amplify his impact in the field of information systems and management. His dedication to advancing knowledge and fostering innovation positions him as a valuable asset to academia and beyond.

ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

Mr. ABEL YU HAO CHAI | DEEP LEARNING | BEST RESEARCHER AWARD

PHD at SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS Malaysia

Abel Chai Yu Hao is a PhD candidate at Swinburne University of Technology Sarawak, specializing in computer vision, machine learning, and deep learning. His research focuses on developing interpretable deep learning models for plant disease identification, collaborating with CIRAD and INRIA on innovative agricultural projects. With a Masterā€™s degree in wireless communication, Abel has contributed to improving rural connectivity in Sarawak through cost-effective wireless solutions. He has co-authored numerous journal articles and conference papers on topics ranging from unseen plant disease recognition to wireless data transmission. Abel is a recipient of multiple awards, including the Gold Award at the Innovation Technology Exposition 2023, and is an active IEEE member.

šŸŽ“ Education

Doctor of Philosophy (2022 – Present) Swinburne University of Technology Sarawak Campus Research focus: Computer Vision, Machine Learning, Deep Learning, AI. Master of Engineering (2019 – 2021) Swinburne University of Technology Sarawak Campus Research focus: Wireless communication, Wi-Fi, Rural connectivity. Bachelor of Engineering (Honours), Electrical & Electronics Engineering (2014 – 2018) Swinburne University of Technology Sarawak Campus CGPA: 3.97/4 (High Distinction)

šŸ« Professional Experience

Teaching Assistant (2019 – Present) Swinburne University of Technology Sarawak Campus Assisting in course delivery, tutorials, and research guidance

šŸ† Awards & Scholarships

Gold Award in Innovation Technology Exposition (2023). Best Paper Award at International UNIMAS Engineering Conference (EnCon) (2020). Sarawak Energy External Scholarship (2015-2018). Swinburne Entrance Scholarship (2014)

šŸŒ± Research Projects

Plant Disease Identification with Deep Learning (2022 – ongoing) Collaborating with experts from CIRAD, INRIA, focusing on AI-based plant disease detection. Rural Internet Connectivity Solutions (2019 – 2021) Conducted cost-performance analysis for wireless solutions in partnership with Sarawak Multimedia Authority (SMA)

Publication

  • Pairwise Feature Learning for Unseen Plant Disease Recognition
    Conference: International Conference on Image Processing (ICIP)
    Year: 2023
    Pages: 306ā€“310
    Contributors: Hao Chai A.Y., Han Lee S., Tay F.S., Bonnet P., Joly A.

 

  • Unveiling Robust Feature Spaces: Image vs. Embedding-Oriented Approaches for Plant Disease Identification
    Conference: Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
    Year: 2023
    Pages: 666ā€“673
    Contributors: Ishrat H.A., Chai A.Y.H., Lee S.H., Then P.H.H.

 

  • Development and Application of Outdoor Router Cost Estimation with Parametric Modelling Technique
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Lai C.H., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Model Study for Outdoor Data Transmission Performance
    Conference: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
    Year: 2022
    Contributors: Chai A.Y.H., Then Y.L., Tay F.S., Lim N.C.Y., Vithanawasam C.K.

 

  • Parametric Model Study for Outdoor Routers Cost Estimation
    Conference: 13th International UNIMAS Engineering Conference (EnCon)
    Year: 2020
    Contributors: Hao Chai A.Y., Hung Lai C., Su H.T., Siang Tay F., Yong L.

šŸ† Conclusion:

Abel Chai Yu Hao is a highly qualified candidate for the Best Researcher Award, given his solid academic background, impactful publications, international collaborations, and ongoing contributions to the field of AI and wireless communication. With continuous focus on expanding his research and increasing engagement, his profile can only continue to rise.

Prasanna Kumar G | Ubiquitous Networks | Excellence in Research

Dr. Prasanna Kumar G | Ubiquitous Networks | Excellence in Research

Dr Prasanna Kumar G The National Institute of Engineering India

Dr. Prasanna Kumar G has made substantial contributions to the fields of cybersecurity and ubiquitous networks through a diverse range of publications and research activities. His scholarly work spans several key areas including machine learning in cybersecurity, IoT-based networking solutions, and advanced network models for seamless connectivity.

Academic History šŸŽ“

Ph.D. in Networking and Internet Engineering, Visvesvaraya Technological University, Sri Jayachamarajendra College of Engineering, Mysore (2023).M.Tech in Networking and Internet Engineering, Visvesvaraya Technological University, Sri Jayachamarajendra College of Engineering, Mysore (2011) ā€“ 80.80%.Bachelorā€™s in Computer Science and Engineering, Visvesvaraya Technological University, Coorg Institute of Technology, Ponnampet (2009) ā€“ 58.14%.PUC, Karnataka PU Board, Sarada Vilas PU College, Mysore (2005) ā€“ 62.00%.S.S.L.C., Karnataka Secondary Education Board, Sadvidya High School, Mysore (2003) ā€“ 76.00%.

Technical Skills šŸ› ļø

Programming Languages: C, C++, Java, PHP, C#.Web Technologies: HTML, CSS, JavaScript, PHP.Operating Systems: Windows, Linux.Database Management: MySQL.Scripting: Shell Script

Projects and Patents šŸ—ļø

M.Tech Project: “Simulation of S-Bus Protocol Devices” ā€“ Development and component testing..Patent 1: “Smart Navigation Stick for the Visually Impaired” (Design No. 6295943).Patent 2: “AI-Based Smart Glasses for Visually Impaired” (Application No. 399870-001).

Training and Workshops šŸ§‘ā€šŸ«

Organized and attended various workshops on Python Programming, IoT, Smart Grid Technologies, Network Technologies, and Business Intelligence.

Achievements šŸ…

Guided projects that won awards, such as 1st prize in IEEE Project Expo 2023 and Best Paper Award in NCEIS-2019.

Publication

  • Introduction to Cyber Security
    Authors: S. Jadey, S.C. Girish, K. Raghavendra, H.R. Srinidhi, K.M. Anilkumar
    Book: Methods, Implementation, and Application of Cyber Security Intelligence and Analytics
    Year: 2022

 

  • NLADSS: Design of Connectivity as a Service (CaaS) Model using Node-Level Augmentation & Dynamic Sleep Scheduling for Heterogeneous Wireless Network Handoffs
    Author: P.K. Gurumallu
    Journal: International Journal of Intelligent Engineering & Systems
    Volume: 15 (5)
    Year: 2022

 

  • Machine Learning in Cybersecurity: A Comprehensive Survey of Data Breach Detection, Cyber-Attack Prevention, and Fraud Detection
    Authors: P. Kumar, D.Y. Gowda, A.M. Prakash
    Book: Pioneering Smart Healthcare 5.0 with IoT, Federated Learning, and Cloud Security
    Year: 2024

 

  • An Efficient IoT-based Ubiquitous Networking Service for Smart Cities Using Machine Learning Based Regression Algorithm
    Authors: G. Prasanna Kumar, N. Shankaraiah
    Journal: International Journal of Information Technology and Computer Science (IJITCS)
    Volume: 15, Pages 15-25
    Year: 2023

 

  • A Novel Approach by Integrating Dynamic Network Selection and Security Measures to Improve Seamless Connectivity in Ubiquitous Networks
    Authors: P. Kumar G, S. N., R. M. B., S. J., S. B. S., D. Y., M. K. B.
    Journal: International Journal of Wireless and Microwave Technologies (IJWMT)
    Volume: 14 (1)
    Year: 2024

 

  • A Metaheuristic Handover Model Using Network Augmentation and Game Theory for Seamless Connectivity in Heterogeneous Networks
    Authors: G. Prasanna Kumar, N. Shankaraiah
    Journal: Wireless Personal Communications
    Volume: 134 (1), Pages 133-150
    Year: 2024

 

  • Basics of Healthcare Informatics
    Authors: J. Sudeep, M. Goutham, G. Prasannakumar, K. Raghavendra, S.C. Girish
    Book: Intelligent Systems in Healthcare and Disease Identification using Data Science
    Year: 2023

 

 

Conclusion:

Dr. Prasanna Kumar Gā€™s body of work reflects a deep engagement with both theoretical and practical aspects of cybersecurity and network engineering. His research not only contributes to the academic community but also offers practical solutions and frameworks applicable to real-world problems. His innovative approaches to network design, security measures, and machine learning applications are indicative of a forward-thinking researcher dedicated to enhancing technological and scientific understanding.

 

 

Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Ms. Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Lecturer atĀ  University of Sri Jayewardenepura, Sri LankaĀ 

M.C. Akarshani Amarasinghe is an accomplished academic and researcher pursuing a PhD in Computer Engineering at the University of Sri Jayewardenepura, Sri Lanka. With a strong background in machine learning, image processing, and drone technology, her work focuses on innovative solutions for public health and agriculture. She has contributed to impactful research projects, such as identifying dengue mosquito breeding sites via drones and optimizing pesticide usage in arable lands. Alongside her research, Akarshani has extensive teaching experience, is a mentor for Google Summer of Code, and holds several prestigious awards for her research excellence.

Publication profile

Scholar

šŸŽ“ Higher Education

01.2024 – Present PhD in Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka Supervisors: Dr. Udaya Wijenayake, Prof. K.L. Jayaratne Research: Path planning algorithm for achieving multiple goals.. 2011 – 2016. BSc (Hons) in Computer Science, University of Colombo School of Computing, Sri Lanka Second Class Upper Division (3.25/4 – Four-Year Program)

šŸ”¬ Recent Research

D4D (Drone for Dengue) Sustainable Computing Research Group, University of Colombo School of Computing. Research on machine learning and image processing for identifying dengue mosquito breeding sites via drone images. Advisors: Prof. T.N.K. De Zoysa, Dr. C.I. Keppitiyagama. 2017 – Present GitHub Project

šŸ§‘ā€šŸ« Teaching Experience

03.02.2020 – Present Lecturer, Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka Subjects: Operating Systems, Data Mining, Natural Language Processing, Quality Engineering, Compilers.01.01.2019 – 31.01.2020 Assistant Lecturer, Department of Computer Science and Software Engineering, Sri Lanka Institute of Information Technology Subjects: Software Engineering Concepts, Programming, Distributed Systems. 01.02.2018 – 30.12.2018 Assistant Lecturer, University of Colombo School of Computing Subjects: Programming Using C, Data Structures, Operating Systems. 2018 Visiting Lecturer, National Institute of Business Management, Sri Lanka Subject: Image Processing. 02.01.2018 – 01.02.2018 Instructor, University of Colombo School of Computing

šŸ… Awards and Achievements

2023 Student Research Project of the Year at the National ICT Awards, NBQSA 2023. 2022 Best Paper in AI and ML Track, ICARC 2022. 2019 N2Women Travel Grant to attend ACM SenSys 2019. 2017 N2Women Travel Grant to attend MobiSys Women’s Workshop

šŸ¢ Professional Service

2023 – Present Treasurer, Past Pupilsā€™ Association, Sadhu Daham Pasala, Sri Lanka. 2015 – Present Committee Member, Thumbowila Api Welfare Society. 2012 – 2016 Committee Member, AIESEC Colombo – South

Publication

  1. Identifying mosquito breeding sites via drone images
    Authors: C Suduwella, A Amarasinghe, L Niroshan, C Elvitigala, K De Zoysa, …
    Conference: Proceedings of the 3rd Workshop on Micro Aerial Vehicle Networks, Systems
    Year: 2017
    Citations: 29

 

  1. A machine learning approach for identifying mosquito breeding sites via drone images
    Authors: A Amarasinghe, C Suduwella, C Elvitigala, L Niroshan, RJ Amaraweera, …
    Conference: Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems
    Year: 2017
    Citations: 15

 

  1. Suppressing dengue via a drone system
    Authors: A Amarasinghe, C Suduwella, L Niroshan, C Elvitigala, K De Zoysa, …
    Conference: 2017 Seventeenth International Conference on Advances in ICT for Emerging Regions
    Year: 2017
    Citations: 15

 

  1. A swarm of crop spraying drones solution for optimizing safe pesticide usage in arable lands
    Authors: A Amarasinghe, VB Wijesuriya, D Ganepola, L Jayaratne
    Conference: Proceedings of the 17th Conference on Embedded Networked Sensor Systems
    Year: 2019
    Citations: 10

 

  1. A path planning algorithm for an autonomous drone against the overuse of pesticides
    Authors: A Amarasinghe, VB Wijesuriya, L Jayaratne
    Conference: 2021 10th International Conference on Information and Automation for Sustainability
    Year: 2021
    Citations: 5

 

  1. Drones vs dengue: a drone-based mosquito control system for preventing dengue
    Authors: A Amarasinghe, VB Wijesuriya
    Conference: 2020 RIVF International Conference on Computing and Communication Technologies
    Year: 2020
    Citations: 4

 

  1. Stimme: a chat application for communicating with hearing impaired persons
    Authors: A Amarasinghe, VB Wijesuriya
    Conference: 2019 14th Conference on Industrial and Information Systems (ICIIS)
    Year: 2019
    Citations: 4

āœ… Conclusion

M.C. Akarshani Amarasinghe is an excellent candidate for the Research for Young Scientist Award. Her innovative contributions to drone technology for health and agriculture, leadership roles, and technical skills make her stand out. With continued expansion of her research portfolio and international exposure, she has the potential to achieve even greater recognition in the future.

 

seyed matin malakouti | AI | Best Researcher Award

seyed matin malakouti | AI | Best Researcher Award

Seyed Matin Malakouti is an accomplished Electrical Engineering professional specializing in machine learning and control systems. He holds an MS in Control System Engineering from the University of Tabriz and a BS in Electrical Engineering from Isfahan University of Technology. Malakouti has published extensively on topics including wind power prediction, temperature change modeling, and heart disease classification. His work has appeared in prominent journals such as Energy Exploration & Exploitation and Case Studies in Chemical and Environmental Engineering. He has received recognition for his research, including awards for Best Researcher and nominations for Best Paper. Malakoutiā€™s research interests span applied machine learning, renewable energy, and biomedical signal processing. He is also an active peer reviewer for various scientific journals.

Publication profile

google scholar

šŸŽ“ Education

MS in Electrical Engineering ā€“ Control System Engineering University of Tabriz, Tabriz, Iran (2019 – 2022). BS in Electrical Engineering
Isfahan University of Technology (IUT), Isfahan, Iran (2014 – 2019)

šŸ¢ Professional Experience

Undergraduate Teaching Assistant Dept. of Electrical Engineering, Isfahan University of Technology (IUT) (2015 – 2018) Assisted in teaching core courses such as Calculus I, II, Electrical Circuit I, II, and Electronics II.

šŸ† Awards & Fellowships

Best Researcher, International Conference on Cardiology and Cardiovascular Medicine (2023). Nominated for Best Paper Award, International Research Awards on Mathematics and Optimization Methods (2023)

šŸ‘Øā€šŸ« Teaching Experience

Spring 2018: Calculus I, Teaching Assistant. Spring 2017: Calculus II, Teaching Assistant. Fall 2016: Electrical Circuit I, Teaching Assistant. Spring 2015: Electrical Circuit II, Teaching Assistant

Research for Best Researcher Award: Seyed Matin Malakouti

šŸŒŸ Strengths for the Award

  1. Diverse Research Contributions: Seyed Matin Malakouti has an extensive list of publications covering a broad range of topics, from wind power generation and temperature change prediction to heart disease classification and asteroid detection. This indicates a high level of versatility and a strong ability to apply machine learning across different domains.
  2. Cutting-Edge Techniques: His work utilizes advanced machine learning techniques such as CNN-LSTM, ensemble methods, and Bayesian optimization. This demonstrates a commitment to leveraging state-of-the-art methods to address complex problems.
  3. High-Impact Publications: Malakouti has published in high-impact journals such as Energy Exploration & Exploitation, Biomedical Signal Processing and Control, and Case Studies in Chemical and Environmental Engineering. His work is also recognized by prestigious conferences and has received nominations for awards.
  4. Peer Review Engagement: Active involvement in peer review for numerous reputable journals reflects his expertise and recognition within the academic community.
  5. Awards and Recognition: Being named the Best Researcher at an international conference and receiving nominations for best paper awards highlights his research’s quality and impact.

šŸ” Areas for Improvement

  1. Broader Impact Assessment: While his technical contributions are substantial, including a focus on how his research impacts broader societal and industrial contexts could further enhance his profile. Emphasizing real-world applications and collaborations could demonstrate the practical significance of his work.
  2. Interdisciplinary Collaboration: Engaging in interdisciplinary projects could further enrich his research profile. Collaborating with researchers from other fields, such as environmental science or healthcare, could lead to innovative solutions and increase the impact of his work.
  3. Public Engagement and Outreach: Increasing efforts in public science communication and outreach could help bridge the gap between academic research and public understanding. Engaging with non-academic audiences through popular science articles, talks, or educational programs could be beneficial.

Publication top notes

  1. Title: Predicting wind power generation using machine learning and CNN-LSTM approaches
    Citations: 46
    Year: 2022
    Journal: Wind Engineering 46(6), 1853-1869

 

  1. Title: Heart disease classification based on ECG using machine learning models
    Citations: 39
    Year: 2023
    Journal: Biomedical Signal Processing and Control 84, 104796

 

  1. Title: Utilizing time series data from 1961 to 2019 recorded around the world and machine learning to create a Global Temperature Change Prediction Model
    Citations: 37
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100312

 

  1. Title: The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction
    Citations: 32
    Year: 2023
    Journal: Cleaner Engineering and Technology 15, 100664

 

  1. Title: Use machine learning algorithms to predict turbine power generation to replace renewable energy with fossil fuels
    Citations: 26
    Year: 2023
    Journal: Energy Exploration & Exploitation 41(2), 836-857

 

  1. Title: Evaluation of the application of computational model machine learning methods to simulate wind speed in predicting the production capacity of the Swiss basel wind farm
    Citations: 21
    Year: 2022
    Journal: 2022 26th International Electrical Power Distribution Conference (EPDC), 31-36

 

  1. Title: Improving the prediction of wind speed and power production of SCADA system with ensemble method and 10-fold cross-validation
    Citations: 19
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 8, 100351

 

  1. Title: Estimating the output power and wind speed with ML methods: a case study in Texas
    Citations: 17
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100324

 

  1. Title: Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in Predicting Wind Speed and Energy Generation
    Citations: 15
    Year: 2023
    Journal: Intelligent Systems with Applications 19, 200248

 

  1. Title: AERO2022-flying danger reduction for quadcopters by using machine learning to estimate current, voltage, and flight area
    Citations: 15
    Year: 2022
    Journal: e-Prime-Advances in Electrical Engineering, Electronics and Energy 2, 100084

 

  1. Title: Prediction of wind speed and power with LightGBM and grid search: case study based on Scada system in Turkey
    Citations: 8
    Year: 2023
    Journal: International Journal of Energy Production and Management 8.

 

šŸ† Conclusion

Seyed Matin Malakouti is a strong candidate for the Research for Best Researcher Award due to his diverse and impactful research contributions, utilization of advanced machine learning techniques, and recognition within the academic community. By focusing on broader impact, interdisciplinary collaboration, and public engagement, he can further enhance his research profile and increase the overall impact of his work.

Ali Bagheri Bardi| Digital Signal Processing | Best Researcher Award

Assoc Prof Dr. Ali Bagheri Bardi| Digital Signal Processing | Best Researcher Award

Assoc Prof Dr.Ā  Ali Bagheri Bardi Persian Gulf University Iran

Ali Bagheri Bardi is an accomplished mathematician with a Ph.D. from Kharazmi University, specializing in pure and applied mathematics, including functional analysis, Fourier analysis, and algebraic signal processing. He has held prestigious positions, such as a postdoctoral researcher and visiting professor at the University of Montenegro and has a significant teaching career at Persian Gulf University. Recognized for his contributions, he has received awards like the Abbas Kermani Mathematics Award. His research focuses on operator algebras, noncommutative harmonic analysis, and graph signal processing, with numerous publications in esteemed journals. He has also mentored Ph.D. students and delivered invited talks at international conferences.

Publication Profile

Scholar

Evaluation for Best Researcher Award: Ali Bagheri Bardi

Strengths for the Award:

  1. Extensive Academic and Research Background: Dr. Ali Bagheri Bardi has an impressive academic background with a Ph.D. in Mathematics from Kharazmi University and significant experience in both teaching and research at renowned institutions, including the University of Montenegro and Persian Gulf University.
  2. Diverse Research Contributions: His research spans a broad spectrum of mathematical disciplines, including pure mathematics, functional analysis, Fourier analysis, von Neumann algebras, and applied mathematics, specifically in algebraic signal processing and graph signal processing.
  3. Publication Record: Dr. Bardi has a strong publication record, with numerous papers in prestigious journals such as Signal Processing, Digital Signal Processing, and Linear Algebra and its Applications. His work is recognized for its depth and contribution to the fields of functional analysis and signal processing.
  4. International Recognition: Dr. Bardi has been invited to speak at various international conferences and universities, showcasing his expertise on a global platform. This recognition by the international community is a testament to the impact and significance of his research.
  5. Mentorship: He has supervised several Ph.D. students, guiding them through complex mathematical research, which reflects his dedication to fostering the next generation of researchers.
  6. Awards and Honors: His receipt of the Abbas Kermani Mathematics Award and an Honorable Mention in the International Mathematics Competition further highlight his excellence in research and mathematical problem-solving.

Areas for Improvement:

  1. Interdisciplinary Collaborations: While his work is strong within the realm of pure and applied mathematics, Dr. Bardi could enhance his research profile by engaging in more interdisciplinary collaborations that connect mathematics with other fields, such as computer science or engineering.
  2. Broader Impact and Outreach: Increasing public engagement through popular science articles or public lectures could help disseminate his work to a wider audience and elevate his influence beyond the academic community.
  3. Securing Larger Grants: Pursuing and securing larger-scale research grants, particularly those that support collaborative, multi-institutional projects, could further bolster his standing as a leading researcher.

šŸŽ“ Education

2004ā€“2008Ā  Ph.D, Kharazmi University. 2002ā€“2004Ā  M.Sc, Kharazmi University. 1998ā€“2002 B.Sc, Shahid Beheshti University.

šŸŽÆ Interests

Pure Math. & Functional Analysis – Fourier Analysis – von Neumann Algebras. Applied Math. & Algebraic Signal Processing – Graph Signal Processing

šŸ’¼ Working Experience

2023ā€“2024Ā  Postdoctoral Position, University of Montenegro, Electrical Engineering Department. 2022ā€“2023Ā  Visiting Professor, University of Montenegro, Electrical Engineering Department. 2020ā€“2022Ā  Associate Professor, Persian Gulf University. 2010ā€“2020Ā  Assistant Professor, Persian Gulf University.

šŸ† Awards

2000Ā  Honorable Mention, International Mathematics Competition for University Students (University College London). 2021 Abbas Kermani Mathematics Award (Shiraz University).

šŸŽ¤ Invited Talks and Conferences

2009 šŸ‡ŖšŸ‡ø Infinite Matrices over Completely Counteractive Banach Algebras, Madrid University, Spain. 2010 šŸ‡øšŸ‡Ŗ Operator-Valued Convolution Algebras, Chalmers University, Sweden. 2011 šŸ‡ÆšŸ‡µ Operator Algebras and their Applications, RIMS, Kyoto University, Japan. 2011 šŸ‡µšŸ‡± Operator Algebras and Quantum Groups, Banach Center, Poland. 2011 šŸ‡±šŸ‡ŗ Noncommutative Harmonic Analysis and Representation Theory, Luxembourg University, Luxembourg. 2023 šŸ‡«šŸ‡· Noncommutative Analysis on Groups and Quantum Groups, UniversitĆ© de Bourgogne Franche-ComtĆ©, France.

šŸŽ“ Ph.D. Students

Current Student
Fatemeh Zarei, Spectral Theory of Polynomial Transforms and Fourier Transform on Graphs
2021. Ā S. Javani, Some Analysis of K-Frames and its Dual
2019 . A. Elyaspour, An Algebraic Approach to the Structure Theory of B(H)
2018. Ā M. Khosheghbal, An Approach to Operator-Valued Measurable Functions

Publications

  • Wold-type decompositions in BaerāŽ-rings
    GA Bagheri-Bardi, A Elyaspour, GH Esslamzadeh
    2018
  • The role of algebraic structure in the invariant subspace theory
    GA Bagheri-Bardi, A Elyaspour, GH Esslamzadeh
    2019
  • Operator-valued measurable functions
    GA Bagheri-Bardi
    2015
  • Operator-valued convolution algebras
    GA Bagheri-Bardi, AR Medghalchi, N Spronk
    2010
  • Numerical solutions of a mathematical model of planktonā€“oxygen dynamics using a meshless method
    A Shirzadi, S Ghayedi, M Safarpoor, G Bagheri Bardi
    2018
  • Borel structures coming from various topologies on
    GA Bagheri-Bardi, M Khosheghbal-Ghorabayi
    2017
  • Zero-padding on Connected Directed Acyclic Graphs for Spectral Processing
    L Stanković, M Daković, M Brajović, I Stanković, AB Bardi
    2023
  • Vector-valued measurable functions
    GA Bagheri-Bardi
    2019
  • An extension of Riesz dual pairing in non-commutative functional analysis
    GA Bagheri-Bardi, A Elyaspour, S Javani, M Khosheghbal-Ghorabayi
    2018
  • Fourier Analysis of Signals on Directed Acyclic Graphs (DAG) Using Graph Zero-Padding
    L Stankovic, M Dakovic, AB Bardi, M Brajovic, I Stankovic
    2023
  • Eigenvalues of Symmetric Non-normalized Discrete Trigonometric Transforms
    AB Bardi, M Dakovic, T Yazdanpanah, L Stankovic
    2023
  • The Schur decomposition of discrete Sine and Cosine transformations of type IV
    Ali Bagheri Bardi, Milos Dakovic, Taher Yazdanpanah, Fatemeh Zarei, Ljubisa Stankovic
    2023
  • Wold-type decomposition of semigroups of isometries in BaerāŽ-rings
    GA Bagheri-Bardi, GH Esslamzadeh, M Sabzevari
    2021
  • Four Algorithms to Produce Approximate K-Dual Frames
    S Javani, GA Bagheri Bardi, F Takhteh
    2020

Conclusion:

The conclusion for the professional and academic profile of Ali Bagheri Bardi highlights his extensive expertise in both pure and applied mathematics, with a particular focus on functional analysis, operator algebras, and algebraic signal processing. Throughout his career, he has held prominent academic positions, contributed significantly to mathematical research, and received recognition for his scholarly achievements, including prestigious awards and invitations to international conferences. His research has led to numerous publications in high-impact journals, and his work continues to influence various fields, particularly in signal processing and noncommutative analysis. His dedication to mentoring Ph.D. students further underscores his commitment to advancing mathematical sciences.