Ferdib Al Islam | Machine Learning | Excellence in Research

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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

 

 

 

Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

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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

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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

Ronny Mabokela | NLP and AI | Best Researcher Award

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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

šŸŽ“ 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.

šŸ’¼ Experience

Mabokelaā€™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.

šŸ† 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.

šŸ”¬ Research Focus

Koena Mabokelaā€™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 šŸ“š

Hyung-Pil Chang | Deep Learning | Best Researcher Award

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

Mr at Korea University,Ā  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

Orcid

Scholar

Education šŸŽ“

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 šŸ’¼

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 šŸ†

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 šŸ”¬

Changā€™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.

šŸ“ 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

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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.

Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

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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

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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.

Anuradha Laishram | Computer vision | Best Researcher Award

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Dr. Anuradha Laishram | Computer vision | Best Researcher Award

Doctorate at National Institute of Technology Manipur, India

Dr. Anuradha Laishram is an accomplished Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology Manipur. With a Ph.D. in Computer Science from the same institution, her research has significantly contributed to the fields of medical image processing and deep learning. She holds a Master’s degree from UVCE, Bangalore University, and a Bachelor’s degree from Visvesvaraya Technological University, Belgaum. Dr. Laishram is known for her expertise in machine learning and her active involvement in impactful research projects, including mHealth solutions and AI translation software. Her dedication to teaching and research makes her a prominent figure in the academic community.

profile:

Scopus Profile

šŸŽ“ Education

  • Ph.D. in Computer Science and Engineering
    • University: National Institute of Technology Manipur
    • Year of Award: 2022
    • Thesis Title: Automatic Classification of Kidney Diseases and Oral Types and Anomalies using Ultrasound Images and Orthopantomogram Radiography Images based on Hybrid Neural Networks and Deep Learning
  • Master of Engineering in Computer Science and Engineering
    • University: UVCE, Bangalore University
    • Year of Passing: 2011
    • Percentage: 79.8%
    • Project: Minimizing Delay and Maximizing Lifetime of Wireless Sensor Network
  • Bachelor of Engineering in Computer Science and Engineering
    • University: Visvesvaraya Technological University, Belgaum
    • Year of Passing: 2008
    • Percentage: 64.5%
  • Other Educational Achievement:
    • Qualified GATE Exam 2008 with an All India Rank of 474 and 97.29 percentile.

Professional Experience

Dr. Anuradha Laishram has extensive experience in academia, currently serving as an Assistant Professor at the National Institute of Technology Manipur in the Department of Computer Science and Engineering since 2014. Prior to this, she gained six months of teaching experience as a lecturer at Alpha College of Engineering, Bangalore in 2011. Her teaching repertoire includes both undergraduate and postgraduate courses such as Computer Programming in C, Data Structures and Algorithm, Computer Organization and Architecture, and Data Communication and Computer Networks. She is proficient in programming languages including C, C++, and Python.

šŸ”¬ Research

Dr. Laishram’s research interests lie in the fields of machine learning, deep learning, medical image processing, and wireless sensor networks. Her doctoral research focused on the automatic classification of kidney diseases and oral anomalies using advanced neural network techniques and deep learning models. She has also contributed to various sponsored research projects, including the development of mHealth solutions for remote tribal areas and AI translation software.

Publication:šŸ“

 

Sayandeep Dutta | Computer Science | Young Scientist Award

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Ā Mr. Sayandeep Dutta | Computer Science | Young Scientist AwardĀ 

Mr. Doon Heritage School, India

šŸ‘©ā€šŸ”¬Driven by a passion for entrepreneurship and cybersecurity, aims to excel as a developer and analyst, leveraging diverse skills in machine learning and creative writing. With a track record of achievements, including prestigious awards and contributions to projects like Krishi Sarthi and OWASP Juice Shop, they possess a strong foundation in tech innovation. As founder of Krishi Sarthi and a penetration tester, they combine technical expertise with leadership in organizing cybersecurity events. Certified in HTML and web application penetration testing, they exhibit a keen aptitude for continuous learning and advancement in the field.šŸŒŸ

 

Profile

 

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šŸš€Ā Career Aspiration

Aspiring to excel as an entrepreneur, developer, and cybersecurity analyst, I aim to reach the pinnacle of success in my chosen field. With a diverse background in projects ranging from NFT artistry to ethical hacking and machine learning development, I strive to make a significant impact in the tech industry. Recognized for my dedication, I continuously engage with communities and contribute to public development research.

šŸŽ“ Ā Education

  • High School Diploma (Class 10) ā€“ Jermelā€™s Academy, Siliguri (Apr 2011 ā€“ Apr 2022)
  • High School Senior Diploma (Class 12) ā€“ Doon Heritage School, Siliguri (Apr 2022 ā€“ Apr 2024)

šŸ† Ā Achievements

  • Nomination for Pradhan Mantri Rashtriya Bal Puraskar 2024
  • Youngest Participant at Young Scientist Conference, IISF 2023
  • Global Digital Innovation Award 2023

šŸ”Project Details

KrishiSarthi: Developed a project for calculating crop yield per hectare using geographical data. Bugbase Hall Of Fame: Recognized for contributions to bug bounty programs. CVE Issuances: Discovered and reported security vulnerabilities in web applications.

šŸ› ļøProjects

  • OWASP Juice Shop (Contributed): A sophisticated insecure web application for security training.
  • DialDetect (Self): A phone number details finder tool providing comprehensive information.

šŸ’¼Work Experience

Founder, KrishiSarthi: Calculated Crop Yield per hectare using geographical data. Content Writer, MAGICSTEP SOLUTIONS PRIVATE LIMITED: Learned project management and teamwork. Penetration Tester, WPScan – WordPress Security: Discovered CVEs and contributed to cybersecurity magazines. Team Leader, CyRaksha: Organized cybersecurity events to nurture talents. Digital Artist, OpenSea: Created NFTs and connected with other artists.

šŸ“œ Certification

HTML Workshop (2021). Technical Workshop on Web Application Penetration Testing (2023). High School Certificates – Certificate for n00bzCTF2023 (2023). Advance Javascript (2022). Effective Listening (2021)

šŸ”§ Ā Skill Highlights

Cybersecurity, Machine Learning, Creative Writing, Conference Speaking, Team Management

Publications Top Notes šŸ“

  • Development and bioavailability assessment of ramipril nanoemulsion formulation
    • Authors: S Shafiq, F Shakeel, S Talegaonkar, FJ Ahmad, RK Khar, M Ali
    • Journal: European journal of pharmaceutics and biopharmaceutics
    • Year: 2007
    • Volume: 66
    • Issue: 2
    • Pages: 227-243
    • Citations: 1006

 

  • Nanoemulsions as vehicles for transdermal delivery of aceclofenac
    • Authors: F Shakeel, S Baboota, A Ahuja, J Ali, M Aqil, S Shafiq
    • Journal: Aaps Pharmscitech
    • Year: 2007
    • Volume: 8
    • Pages: 191-199
    • Citations: 427

 

  • Formulation development and optimization using nanoemulsion technique: a technical note
    • Authors: S Shafiq-un-Nabi, F Shakeel, S Talegaonkar, J Ali, S Baboota, A Ahuja, …
    • Journal: AAPS pharmscitech
    • Year: 2007
    • Volume: 8
    • Pages: E12-E17
    • Citations: 420

 

  • Design, development and evaluation of novel nanoemulsion formulations for transdermal potential of celecoxib
    • Authors: S Baboota, F Shakeel, A Ahuja, J Ali, S Shafiq
    • Journal: Acta pharmaceutica
    • Year: 2007
    • Volume: 57
    • Issue: 3
    • Pages: 315-332
    • Citations: 397

 

  • A review on the strategies for oral delivery of proteins and peptides and their clinical perspectives
    • Authors: A Muheem, F Shakeel, MA Jahangir, M Anwar, N Mallick, GK Jain, …
    • Journal: Saudi Pharmaceutical Journal
    • Year: 2016
    • Volume: 24
    • Issue: 4
    • Pages: 413-428
    • Citations: 384