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 Master’s and Bachelor’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. Ferdib’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

πŸŽ“ Education

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

πŸ’Ό 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.

πŸ† 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.

πŸ”¬ Research Focus

Ferdib’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 Patient’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 Patient’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

πŸŽ“ 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.

πŸ’Ό 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.

πŸ† 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.

πŸ”¬ 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.

πŸ“šPublicationsΒ 

  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 women’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 Human–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 Users’ 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 Iran’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

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Scholar

πŸŽ“ 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 | Alzheimer’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

πŸ’Ό 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.

πŸ† Awards and Honors

Member, Iran’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)

πŸ”¬ 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

🌟 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 πŸ“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

Β πŸŽ“ 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)

πŸ’Ό 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.

πŸ† 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.

πŸ”¬ 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 Shrestha’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 πŸ“š

Ronny Mabokela | NLP and AI | Best Researcher Award

Mr. Ronny Mabokela | NLP and AI | Best Researcher Award

PHD at University of Johannesburg, South Africa

Koena Ronny Mabokela is a South African computer scientist with a diverse background in technology and education. Currently pursuing a PhD in Computer Science at the University of the Witwatersrand, he has built a career focused on speech technology, system integration, and tech innovation. With years of experience as an educator, lecturer, and researcher, he also holds a leadership role at the University of Johannesburg, where he serves as Acting Deputy Head of Department and Head of the Technopreneurship Centre. Koena is passionate about fostering technological advancements, particularly in education and enterprise systems.

Profile

Scholar

πŸŽ“ Education

Koena Ronny Mabokela holds a PhD in Computer Science from the University of the Witwatersrand (2020-2024). He earned a Master of Science in Computer Science with a focus on Speech Technology at the University of Limpopo (2012-2014). His academic journey includes a Bachelor of Science Honours in Computer Science (2011) and a Bachelor of Science in Computer Science and Mathematics (2008-2010), both from the University of Limpopo.

πŸ’Ό Experience

Mabokela’s career spans various leadership and academic roles. He is currently the Acting Deputy HoD for CEPs/SLPs and Online at the University of Johannesburg. Previously, he served as the Head of the Technopreneurship Centre, managing strategy, projects, and research. He has taught various programming modules and supervised postgraduate students while conducting research and engaging in community development. His professional experience also includes roles at Vodacom and Telkom in business systems integration and product development.

πŸ† Awards and Honors

Mabokela has received numerous accolades, including being a session chair for SATNAC 2014 and a peer reviewer for prestigious conferences like IEEE and SATANC. He has also contributed to the scientific community with his published research in areas such as sentiment analysis and AI for under-resourced languages. His leadership skills and contributions to innovation have been recognized throughout his academic and professional career.

πŸ”¬ Research Focus

Koena Mabokela’s research interests revolve around speech technology, AI, and multilingual sentiment analysis, particularly for under-resourced languages. He focuses on enhancing language identification and sentiment analysis systems for South African languages. His work includes exploring distant supervision approaches and applying AI to tackle social challenges, as seen in his published papers and presentations at international conferences. His research aims to bridge technological gaps in underrepresented languages and communities.

Conclusion

Koena Ronny Mabokela is an outstanding researcher with a diverse and impactful portfolio that bridges academia and industry. His extensive experience, leadership in academic development, and commitment to advancing knowledge in computer science and technology position him as a top candidate for the Best Researcher Award. While there are opportunities to expand his interdisciplinary work and enhance the practical impact of his research, his contributions to the academic community and the field of technology are significant. His future work promises to continue shaping the landscape of digital innovation and research.

Publications πŸ“š

Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr. Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr at Korea University,Β  South Korea

Hyung-pil Chang is a dedicated graduate student at Korea University, pursuing a Ph.D. in Computer Science and Engineering. With a keen interest in deep learning and speech processing, he focuses on enhancing communication between humans and machines. He has contributed to several innovative projects in voice conversion and speech recognition, demonstrating a commitment to advancing technology in these fields. In addition to his academic pursuits, Chang actively engages in various sports and cultural activities, reflecting a well-rounded personality. His passion for research is complemented by his desire to develop practical solutions for real-world problems in artificial intelligence.

Profile

Scopus

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Scholar

Education πŸŽ“

Hyung-pil Chang began his academic journey at Hansung University, where he earned a Bachelor of Science in Information System and Engineering from March 2014 to February 2020. He continued his studies at Korea University, obtaining a Master of Science in Computer Science and Engineering from 2020 to 2022. Currently, he is pursuing his Doctor of Philosophy in the same field at Korea University, enhancing his knowledge and expertise in deep learning, speech recognition, and human-computer interaction.

Experience πŸ’Ό

Chang has gained valuable experience as a research assistant at Korea University’s Artificial Intelligence Laboratory since March 2020, working under the guidance of Prof. Dongsuk Yook. He has also served as a teaching assistant for undergraduate courses in Artificial Intelligence and Machine Learning, honing his teaching skills and sharing his knowledge with students. Additionally, he briefly worked in the Voice Generation Team at KT on a multi-modal project, where he contributed to advancements in voice conversion technologies, further solidifying his practical experience in the field.

Awards and Honors πŸ†

Hyung-pil Chang has received recognition for his academic and research achievements, including publications in reputable journals such as MDPI Applied Sciences and IEEE Access. His contributions to voice conversion and speaker anonymization research have garnered attention in the field of speech processing. While specific awards are not listed, his active participation in conferences and collaboration on innovative projects highlight his commitment to excellence in research and development, positioning him as an emerging talent in artificial intelligence and deep learning.

Research Focus πŸ”¬

Chang’s research centers on enhancing communication between people and machines, particularly in speech processing. He aims to improve speech recognition models using self-training techniques on large amounts of unlabeled data. His work also explores explainable AI and the development of a general-purpose domain agent capable of interacting with humans across various tasks, including vision and natural language processing. Key areas of focus include speech recognition, synthesis, voice conversion, and human-computer interaction, contributing to advancements in multi-modal language models.

πŸ“ Conclusion

Hyung-pil Chang demonstrates strong potential as a leading researcher in deep learning and speech processing. His academic background, research contributions, and innovative spirit position him well for the Best Researcher Award. By focusing on collaboration, expanding his publication record, and engaging more with the broader community, he can enhance his impact even further. Given his current trajectory, he is well on his way to making significant contributions to his field and is a worthy candidate for recognition.

Publications Top Notes

  • Wav2wav: Wave-to-Wave Voice Conversion
    C Jeong, H Chang, IC Yoo, D Yook
    Applied Sciences, 2024, 14(10), 4251.

 

  • Zero-Shot Unseen Speaker Anonymization via Voice Conversion
    HP Chang, IC Yoo, C Jeong, D Yook
    IEEE Access, 2022, 10, 130190-130199.

 

  • CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models
    D Yook, G Han, HP Chang, IC Yoo
    Applied Sciences, 2024, 14(20), 9595.

 

 

 

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

 

πŸŽ“ 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

πŸ“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

πŸ† 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 Staff’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 πŸŽ“

    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 Master’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.

πŸŽ“ 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)

🏫 Professional Experience

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

πŸ† 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)

🌱 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: 306–310
    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: 666–673
    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.

πŸ† 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.

Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Ms. Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Lecturer atΒ  University of Sri Jayewardenepura, Sri LankaΒ 

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

πŸŽ“ 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)

πŸ”¬ 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

πŸ§‘β€πŸ« 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

πŸ… 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

🏒 Professional Service

2023 – Present Treasurer, Past Pupils’ 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

βœ… 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. Malakouti’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

πŸŽ“ Education

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

🏒 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.

πŸ† 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)

πŸ‘¨β€πŸ« 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

🌟 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.

πŸ” 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.

 

πŸ† 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.