Assist. Prof. Dr. Getachew Wegari | Natural Language Processing (NLP) | Best Researcher Award

Assist. Prof. Dr. Getachew Wegari | Natural Language Processing (NLP) | Best Researcher Award

Assist. Prof. Dr. Getachew Wegari | Jimma University | Ethiopia

Dr. Getachew Mamo is an Assistant Professor of IT at Jimma University, specializing in Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI). With a PhD in Information Technology from Addis Ababa University, he has dedicated his career to advancing language technologies, particularly for the Afaan Oromo language. His expertise spans Python, Java, and C++, alongside deep learning frameworks such as PyTorch and OpenCV. Beyond academia, he has led key research projects and held administrative roles, including Dean of the Faculty of Computing and Informatics. His contributions to AI and NLP continue to impact Ethiopia’s tech landscape. πŸš€

Professional Profile:

Google Scholar

Suitability for Best Researcher Award

Dr. Getachew Mamo is a strong candidate for a Best Researcher Award due to his significant contributions to Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI), particularly in the context of Afaan Oromo language technologies. His work aligns with the award’s objective of recognizing impactful research that advances technological and scientific knowledge.

πŸŽ“ Education & Experience

  • PhD in Information Technology (Language Technology) – 2019 πŸŽ“
    Addis Ababa University, Ethiopia

    • Thesis: Morphological Analysis Using Suffix-Sequences Based Machine Learning Approach
  • MSc in Information Science – 2009 πŸŽ“
    Addis Ababa University, Ethiopia

    • Thesis: Parts of Speech Tagging for Afaan Oromo
  • Assistant Professor (2018 – Present) πŸ‘¨β€πŸ«

    • Lecturing MSc courses: NLP, AI, Machine Learning, Python, Data Science
    • Supervising postgraduate students
  • Lecturer (2009 – 2017) πŸŽ“

    • Teaching undergraduate courses: Java, C++, DBMS, Networking
    • Supervising student projects
  • Graduate Assistant – Assistant Lecturer (2005 – 2008) πŸŽ“

    • Assisting and teaching IT-related courses
  • Chairperson, Department of IT (2006-2007, 2008-2011) πŸ›οΈ

  • Dean, Faculty of Computing and Informatics (2018-2020, 2022-Present) πŸŽ–οΈ

πŸ“ˆ Professional Development

Dr. Getachew Mamo has made significant contributions to academia through research, teaching, and leadership. As an expert in NLP and AI, he has developed various machine learning models for language processing, including morphological analysis and speech recognition for Afaan Oromo. His extensive teaching experience covers key areas such as deep learning, artificial intelligence, and data science. He has held leadership roles, fostering academic growth and innovation at Jimma University. Additionally, he actively engages in research collaborations, publishing in international journals and conferences. His passion for technological advancements continues to drive Ethiopia’s progress in AI and IT. πŸš€πŸ“–

πŸ”¬ Research Focus

Dr. Getachew Mamo’s research primarily revolves around Natural Language Processing (NLP) πŸ€–, Artificial Intelligence (AI) 🧠, and Machine Learning (ML) πŸ“Š. His work has significantly contributed to Afaan Oromo language processing, including morphological analysis, parts of speech tagging, and speech-based command systems. He is also involved in big data analytics and deep learning models for medical applications, such as breast cancer diagnosis. His ongoing projects include an AI-based road safety management system and an Afaan Oromo spell checker. Through his research, he aims to enhance language technology, improve communication systems, and integrate AI into real-world applications. πŸŒπŸ’‘

πŸ† Awards & Honors

  • πŸ… Best Teaching Performance Award – College of Engineering and Technology, Jimma University (2010)

Publication Top Notes:

πŸ“Œ Parts of speech tagging for Afaan Oromo – GM Wegari, M Meshesha | International Journal of Advanced Computer Science and Applications 1(3),Β  πŸ“‘ Cited by: 12
πŸ“Œ Suffix sequences based morphological segmentation for Afaan Oromo – GM Wegari, M Melucci, S Teferra | AFRICON 2015, 1-6Β  πŸ“‘ Cited by: 2
πŸ“Œ Probabilistic and grouping methods for morphological root identification for Afaan Oromo – GM Wegari, M Melucci, S Teferra | 2016 6th International Conference-Cloud System and Big Data EngineeringΒ  πŸ“‘ Cited by: 1
πŸ“Œ The Integration of Deep Learning Techniques and Big Data Analytics for Improved Breast Cancer Diagnosis and Treatment: A Systematic Review – HM Gebre, GM Wegari | 2024 International Conference on Information and Communication TechnologyΒ  πŸ“‘ Cited by: N/A
πŸ“Œ An Assessment of Big Data Analysis Technologies for Improved Information Delivery – SR Chanthati, T Velmurugan, N Gulati, N Kedia, F Akram, GM Wegari | 2023 3rd International Conference on Smart Generation Computing Β πŸ“‘ Cited by: N/A

 

 

 

Ms. Yuri Kim | Natural Language Processing | Best Researcher Award

Ms. Yuri Kim | Natural Language Processing | Best Researcher Award

Ms. Yuri Kim, Korea University, South KoreaΒ 

Yuri Kim is a Ph.D. candidate in Computer Science at Korea University πŸŽ“, specializing in Natural Language Processing (NLP), machine learning, and algorithm development πŸ€–. She has extensive experience in academia and industry, having worked as a lecturer and researcher while managing projects in business automation. With a strong background in backend development and functional programming, she has contributed to multiple innovative projects, including AI-based systems and stock trading analytics πŸ“ˆ. As a recipient of prestigious scholarships and an active participant in startup programs, Yuri is dedicated to bridging AI with real-world applications πŸš€.

Professional Profile:

ORCID

Suitability for Best Researcher Award

Yuri Kim is a highly suitable candidate for the Best Researcher Award, given her extensive contributions to Natural Language Processing (NLP), machine learning, and algorithm development. As a Ph.D. candidate at Korea University, she has made significant strides in both academic research and industry applications. Her ability to merge backend development and functional programming with AI-driven systems demonstrates a unique interdisciplinary expertise.

Education & Experience πŸŽ“πŸ’Ό

  • Korea University, Seoul, South Korea 🏫 (2020.09 – Present)

    • Ph.D. Candidate in Computer Science
    • Recipient of ICT Elite Talent Development Program Scholarship πŸŽ–οΈ
    • Research Assistant πŸ”¬
  • EΓΆtvΓΆs LorΓ‘nd University, Budapest, Hungary πŸ‡­πŸ‡Ί (2016.09 – 2019.08)

    • B.Sc. & M.Sc. in Computer Science (Integrated Program)
    • GPA: 4.28 / 4.5 (Master’s) | GPA: 4.48 / 4.5 (Bachelor’s)
    • Recipient of Stipendium Hungaricum (Hungarian Government Scholarship) πŸŽ“
  • The Mihalik Group, Chicago, IL (Remote) 🌍 (2023.08 – 2024.07)

    • Project Manager (PM) πŸ—οΈ
    • Developed in-house business automation software
    • Managed resources, schedules, and project phases
  • Korea University Graduate School of Education, Seoul 🏫 (2022.09 – 2023.02)

    • Lecturer – Advanced Data Structures πŸ“Š
    • Delivered lectures, designed exams, and instructional materials
  • EΓΆtvΓΆs LorΓ‘nd University, Budapest πŸ‡­πŸ‡Ί (2018.02 – 2019.02)

    • Lecturer – Functional Programming (Clean Language) πŸ’‘
    • Taught programming concepts and designed assignments
  • Ericsson, Budapest, Hungary 🌍 (2018.09 – 2019.01)

    • Student Backend Developer πŸ’»
    • Developed performance test cases using C and conducted code reviews

Professional Development πŸš€πŸ“š

Yuri Kim actively engages in cutting-edge research and innovative projects, focusing on NLP, machine learning, and AI-based automation πŸ€–. As a startup enthusiast, she has participated in entrepreneurial programs like the Korean I-Corps Program and the Innovation Startup School, where she developed AI-powered solutions, including a personalized makeup consulting system and a celebrity memorabilia auction platform 🎭. Additionally, she has managed and contributed to AI-driven projects such as audiobook auto-generation and motion slide automation πŸ“ˆ. With a passion for education, she has also worked as a lecturer, emphasizing functional programming and data structures.

Research Focus πŸ”¬πŸ’‘

Yuri Kim specializes in Natural Language Processing (NLP) πŸ—£οΈ, machine learning 🧠, and algorithm development πŸ“Š, with applications in finance, education, and AI-driven automation. Her research includes developing rule-based stock trading recommendation systems πŸ“ˆ, serendipity-incorporated recommender systems 🎯, and Linked Data visualization tools 🌐. She also explores the interdisciplinary applications of functional programming and the enhancement of distributed computing ⚑. Her work contributes to improving data processing, AI-driven decision-making, and user engagement strategies across various domains, from stock market analytics to interactive learning platforms πŸ“š.

Awards & Honors πŸ†πŸŽ–οΈ

  • ICT Elite Talent Development Program Scholarship πŸ“œ (Korea University)
  • Stipendium Hungaricum Scholarship πŸ‡­πŸ‡Ί (Hungarian Government)
  • 2024 Korean I-Corps Program πŸš€ (AI-Based Personalized Makeup Consulting)
  • 2023 Innovation Startup School – Team Tech School Track πŸ’‘ (AI-Based Celebrity Memorabilia Auction Platform)

Publication Top Notes:

πŸ“ˆπŸ“Š”A Rule-Based Stock Trading Recommendation System Using Sentiment Analysis and Technical Indicators”
πŸ’»πŸ“–”Introduction to programming Using Clean”

 

Mr. Feng Wang | Computational Analysis | Best Researcher Award

Mr. Feng Wang | Computational Analysis | Best Researcher Award

Mr. Feng Wang, China Three Gorges University, China

Mr. Feng Wang is an Associate Professor at China Three Gorges University, specializing in bridge and tunnel engineering. With a Ph.D. from Wuhan University of Technology, he has conducted groundbreaking research on nonlinear dynamic responses of long-span cable structures. His work has been applied in major engineering projects, contributing significantly to seismic design and wind/ice resistance of overhead transmission lines. As a visiting scholar at The University of Queensland, he collaborated with leading experts to enhance computational analysis methods. With over 50 academic publications and 60 patents, Mr. Wang’s contributions have had a lasting impact on structural engineering. His interdisciplinary approach integrates AI-driven assessment models, vibration suppression techniques, and disaster protection strategies, making him a leader in modern civil engineering. Recognized with multiple teaching awards, he continues to mentor young engineers while advancing critical infrastructure development. πŸš€πŸ—οΈ

🌏 Professional Profile

Orcid

πŸ† Suitability for Best Researcher AwardΒ 

Mr. Feng Wang is a highly accomplished researcher whose work in structural engineering has led to significant advancements in bridge safety, vibration control, and AI-driven assessment models. His contributions address critical engineering challenges, including dynamic catastrophe protection and seismic resistance for large-scale structures. Having led and participated in over 30 research projects funded by prestigious organizations, he has demonstrated exceptional expertise and innovation. His 50+ publications in high-impact journals, 60 patents, and multiple software copyrights reflect his leadership in applied research. His work aligns with global infrastructure development strategies, including the Belt and Road Initiative. Additionally, his recognition as an “Excellent Instructor” underscores his dedication to academia. Mr. Wang’s research not only pushes theoretical boundaries but also translates into real-world applications, making him an outstanding candidate for the Best Researcher Award. πŸ…πŸ”¬

πŸ“š Education

  • Ph.D. in Bridge and Tunnel Engineering (2007–2010) – Wuhan University of Technology πŸŽ“

    • Dissertation: “Geometric Nonlinear Analysis of Long-Span Three-Tower Composite Girder Cable-Stayed Bridges”
    • Awarded Outstanding PhD Dissertation Award
    • Supervised by Prof. Liu Muyu, Director of the Hubei Provincial Key Laboratory of Road and Bridge Engineering
  • Visiting Scholar (2019–2020) – The University of Queensland, Australia 🌏

    • Fully funded by the China Scholarship Council
    • Collaborated with Prof. Chien Ming Wang on nonlinear dynamics of long-span cable structures

His education provided a strong foundation in computational mechanics, structural stability, and interdisciplinary engineering applications, enabling his impactful research in bridge safety and AI-driven assessment methods. πŸŽ“πŸ“–

πŸ‘¨β€πŸ”¬ ExperienceΒ 

  • Associate Professor, China Three Gorges University (2015–Present) πŸ—οΈ

    • Conducts research in bridge engineering, computational analysis, and AI-driven infrastructure assessment
    • Supervises Master’s students in civil and electrical engineering
  • Lecturer, China Three Gorges University (2011–2015) πŸ“š

    • Promoted to Associate Professor in 2015
  • Assistant Engineer, China Communications Construction Company (2002–2004) 🚧

    • Worked on highway base and surface construction
  • Visiting Researcher, The University of Queensland (2019–2020) 🌏

    • Specialized in long-span cable structure dynamics

With over two decades of experience in academia and industry, Mr. Wang has contributed to major engineering projects and advanced computational methods in structural analysis. πŸ”πŸ—οΈ

πŸ… Awards and Honors

  • Outstanding PhD Dissertation Award (2010) – Wuhan University of Technology πŸŽ“πŸ†
  • Excellent Instructor Award (2014, 2017, 2018) – “Gaojiao Cup” National College Students’ Advanced Drawing Technology Competition πŸ…πŸ‘¨β€πŸ«
  • National Natural Science Foundation of China (NSFC) Grant Recipient – Led multiple funded research projects πŸ’°πŸ”¬
  • China Scholarship Council Award (2019–2020) – Fully funded visiting scholar at The University of Queensland πŸ‡¨πŸ‡³πŸŒ
  • 60+ Patents & 5 Software Copyrights – Innovations in bridge engineering, AI models, and disaster protection πŸ—οΈπŸ’‘

Mr. Wang’s recognitions highlight his research excellence, innovation, and contributions to structural engineering and education. πŸŒŸπŸŽ–οΈ

πŸ”¬ Research FocusΒ 

Mr. Feng Wang’s research revolves around computational structural analysis, AI-driven assessment models, and disaster protection technologies for large-scale infrastructure. His work in geometric nonlinear analysis enhances bridge safety and longevity, while his vibration suppression techniques improve the stability of ultra-long stay cables. He has pioneered AI-based models to assess bridge components, ensuring optimal maintenance and damage prevention. His research extends to dynamic catastrophe protection, helping safeguard overhead transmission lines from extreme environmental conditions. πŸŒ‰πŸ’‘

By integrating Big Data Analytics, AI, and engineering mechanics, he develops predictive models that optimize bridge resilience. His interdisciplinary approach aligns with China’s Belt and Road Initiative, focusing on sustainable infrastructure. His contributions advance both fundamental research and practical applications, making a lasting impact on structural engineering. πŸ—οΈπŸ”

Publication Top Notes:

Title : Coupled Parametric Vibration Model and Response Analysis of Single Beam and Double Cable Under Deterministic Harmonic and Random Excitation
Published Year : 2024