Nisar Hussain | Artificial Intelligence and Machine Learning | Best Researcher Award

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Mr.Nisar Hussain |Artificial Intelligence and Machine Learning|Best Researcher Award

Mr.  Nisar Hussain Instituto Politechnico Nacional, Mexico City, Mexico

Nisar Hussain is a researcher affiliated with the Instituto Politécnico Nacional (IPN) in Mexico City, Mexico. He is currently enrolled in the Doctorate in Computer Science program at IPN’s Centro de Investigación en Computación (CIC), focusing his research on offensive language detection and sentiment analysis in code-mixed text on social media.Throughout his academic career, Hussain has contributed to various studies in the field of Natural Language Processing (NLP). Notably, he co-authored the paper titled “ORUD-Detect: A Comprehensive Approach to Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning–Deep Learning Models with Embedding Techniques,” published in the journal Information in February 2025.In addition to his work on offensive language detection, Hussain has explored other areas of NLP. He co-authored a study on guilt detection in text, which was published in Scientific Reports in July 2023.

Publication Profile

Google scholar

orcid

Education :

Ph.D. in Computer Science (2022-2025, Ongoing)
Instituto Politécnico Nacional, MéxicoMaster’s in Computer Science (2014-2017)
University of Agriculture, Faisalabad, PakistanBachelor of Science in Computer Science (BSCS) (2010-2014)
COMSATS University Islamabad, Sahiwal Campus

Experience :

With 4+ years of experience in developing and deploying ML and NLP systems, I have actively contributed to multiple projects, applying NLP techniques for real-world problem-solving. I have worked with large, complex datasets, implementing hybrid ML-DL approaches for automated text processing, sentiment analysis, and multilingual content understanding. My research collaborations span multiple institutions, focusing on AI-driven solutions for text analysis and detection tasks.

Research Focus :

I specialize in Natural Language Processing (NLP) and Machine Learning, with a particular emphasis on Offensive Language Detection and Sentiment Analysis of Code-Mixed Data. My research explores multilingual and low-resource language models, leveraging and fine-tuning mBERT, XLM-R, IndicBERT, and Google’s BERT-based models. I am particularly interested in hate speech detection, sentiment analysis, language identification, and emotion analysis in complex linguistic environments. My work integrates deep learning techniques, transformers, and hybrid ML-DL models to improve text processing and understanding in diverse multilingual contexts.

Awards:

Published multiple high-impact research papers in leading AI and NLP conferences/journalsActive participant in international AI competitions and workshopsRecognized for contributions to multilingual and low-resource NLP advancements

Publication :

  • Shaheen, M., Awan, S. M., Hussain, N., & Gondal, Z. A. (2019). Sentiment analysis on mobile phone reviews using supervised learning techniques. IJMECS, 11(7), 32.

 

  • Mehak, G., Qasim, A., Meque, A. G. M., Hussain, N., Sidorov, G., & Gelbukh, A. (2025, January). TechExperts (IPN) at GenAI Detection Task 1: Detecting AI-Generated Text in English and Multilingual Contexts. In Proceedings of the 1st Workshop on GenAI Content Detection (GenAIDetect) (pp. 161-165).

 

  • Hussain, N., Qasim, A., Mehak, G., Kolesnikova, O., Gelbukh, A., & Sidorov, G. (2025). Hybrid Machine Learning and Deep Learning Approaches for Insult Detection in Roman Urdu Text. AI, 6(2), 33. https://doi.org/10.3390/ai6020033

 

  • Qasim, A., Mehak, G., Hussain, N., Gelbukh, A., & Sidorov, G. (2025). Detection of Depression Severity in Social Media Text Using Transformer-Based Models. Information, 16(2), 114. https://doi.org/10.3390/info16020114

 

  • Manzoor, M. I., Shaheen, M., Khalid, H., Anum, A., Hussain, N., & Faheem, M. R. (2018). Requirement Elicitation Methods for Cloud Providers in IT Industry. IJMECS, 10(10).

 

  • Hussain, N., & Anees, T. (2018). Development of a novel approach to search resources in IoT. International Journal of Advanced Computer Science and Applications, 9(9).

 

  • Faheem, M. R., Iftikhar, A., & Hussain, N. (2022). Automated Diagnosing of Eye Disease in Real Time. Journal of Computing & Biomedical Informatics, 3(1), 282-288.

 

  • Shaheen, M., Anees, T., Hussain, N., & Obaid, I. (2019, April). A Research on SOA in the IT Industry of Pakistan. In Proceedings of the 2019 ICCTA (pp. 149-154).

 

  • Meque, A. G. M., Hussain, N., Sidorov, G., & Gelbukh, A. (2023). Guilt Detection in Text: A Step Towards Understanding Complex Emotions. arXiv preprint arXiv:2303.03510.

 

  • Tash, M. S., Ahani, Z., Tonja, A., Gemeda, M., Hussain, N., & Kolesnikova, O. (2022, December). Word Level Language Identification in Code-mixed Kannada-English Texts using Traditional Machine Learning Algorithms. In Proceedings of the (ICON) (pp. 25-28).

 

 

 Conclusion

Given their strong publication record, hands-on experience with AI models, and focus on low-resource NLP, the candidate is highly competitive for the Best Researcher Award. Strengthening industry collaborations, increasing research impact, and securing grants will further enhance their research profile.

 

 

 

Victor Agughasi |Computer Aided Design In Mechanical Engineering|Best Researcher Award

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Assist. Prof. Dr.Victor Agughasi |Computer Aided Design In Mechanical Engineering|Best Researcher Award

Assistant Professor, Maharaja Institute of Technology Mysore, India

Summary:

Assistant Professor, Maharaja Institute of Technology, Mysore, India,Dr. Victor Agughasi is an Assistant Professor at the Maharaja Institute of Technology, Mysore, India. With extensive expertise in his field, he contributes to academic excellence through teaching, research, and mentoring students. His work reflects a commitment to advancing knowledge and fostering innovation in higher education.

 

Professional Profiles:

Scopus

Google Scholar

Orcid

🎓 Education :

Ph.D. in Computer Science,University of Mysore, Karnataka, India (Sept. 2018 – Dec. 2023),Thesis: Machine Learning Algorithm for the Diagnosis of Chronic Obstructive Pulmonary Diseases from Chest X-ray Images.,Postgraduate Diploma in Business Administration (PGDBA),Bangalore University, Bangalore, India (Dec. 2016 – Jan. 2018),M.Sc. in Computer Science,Bangalore University, Bangalore, India (Apr. 2014 – Mar. 2016),B.Sc. in Computer Science,Michael Okpara University, Abia State, Nigeria (Nov. 2006 – Oct. 2010),West African Senior School Certificate Examination (WASSCE),Community Secondary School, Okigwe, Imo State, Nigeria (May – June 2004)

 

🏢 Experience:

Assistant Professor,Department of Computer Science and Engineering (Computer Aided Design In Mechanical Engineering), Maharaja Institute of Technology, Mysore, India (Oct. 2023 – Present),Teaches subjects such as Machine Learning, Computer Vision, Big Data Analytics, Digital Image Processing, Database Management Systems, Python for Data Visualization, and Research Methodology.,Research Associate,Maharaja Institute of Technology, Mysore, India (June 2019 – Oct. 2023),Focused on Machine Learning, Big Data Analytics, and Mobile App Development in Java. Supervised research projects in Machine Learning.,Visiting Faculty (Voluntary),Dr. Ambedkar Institute for Management Science, Bangalore, India (Aug. 2018 – May 2019),Conducted courses in Information System & Science and Database Management Systems.,Visiting Faculty (Voluntary),St. Aloysius Degree College, Bangalore, India (Jul. 2017 – Feb. 2018),Taught sessions on Information System & Science and Database Management Systems.,Teaching Assistant (Voluntary),St. Joseph’s College, Bangalore, India (Oct. 2014 – Mar. 2016),Taught Computer Fundamentals and Web Design using PHP.,Java Instructor (Intern),APTECH Computer Education, Bangalore, India (Oct. – Dec. 2014),Provided training in Computer Fundamentals and Web Design using PHP.,Web Developer,Max-Out Resources Pvt. Ltd, Abuja, Nigeria (Jul. 2011 – Jun. 2012),High School Teacher,Community Secondary School, Okigwe, Nigeria (Feb. – Nov. 2009)

Skills:

Proficient in programming languages such as Java, JavaScript, Python, and PHP. Experienced in database systems including MySQL, PostgreSQL, and Oracle. Fluent in English with basic knowledge of Kannada.

 

Research Focus :

Specializes in Medical Imaging, Explainable AI Models, Data Science, Machine Learning, Deep Learning, and Computer Vision. Research emphasizes creating innovative machine learning algorithms for diagnosing chronic diseases from medical imaging data.

 

🔬Awards:

Received Best Paper Awards at multiple international conferences including ADCIS-2024, ERCICAM-2024, and ICCSA-2021. Recognized as the Best Outgoing Student in PG Science at St. Joseph’s College, Bangalore, and awarded gold medals in web application competitions organized by APTECH. Secured a Management Scholarship and Certificates of Merit for outstanding academic performance.

 

Conclusion:

Based on the information provided:,Suitability: Dr. Victor Agughasi appears to be a strong candidate for the award, provided his accomplishments align with the specific goals of the awarding body.,Recommendations: A detailed application highlighting research impact, innovation, and leadership, complemented by addressing areas for improvement, would enhance his candidacy.

 Publications:

  • ResNet-50 vs VGG-19 vs Training from Scratch: A Comparative Analysis of the Segmentation and Classification of Pneumonia from Chest X-Ray Images
    Authors: Agughasi Victor Ikechukwu, Murali S, Deepu R, RC Shivamurthy
    Publication: Global Transitions Proceedings
    Year: 2021
    Citations: 5

 

  • CX-Net: An Efficient Ensemble Semantic Deep Neural Network for ROI Identification from Chest X-Ray Images for COPD Diagnosis
    Authors: AV Ikechukwu, S Murali
    Publication: Machine Learning: Science and Technology
    Year: 2023
    Citations: 21

 

  • i-Net: A Deep CNN Model for White Blood Cancer Segmentation and Classification
    Authors: AV Ikechukwu, S Murali
    Publication: International Journal of Advanced Technology and Engineering Exploration
    Year: 2022
    Citations: 19

 

  • Semi-Supervised Labelling of Chest X-Ray Images Using Unsupervised Clustering for Ground-Truth Generation
    Authors: Agughasi Victor Ikechukwu, S Murali
    Publication: Applied Engineering and Technology
    Year: 2023
    Citations: 13

 

  • Explainable Deep Learning Model for Covid-19 Diagnosis
    Authors: AV Ikechukwu, P Sreyas, A Sena, H Preetham, K Raksha
    Publication: IRJMETS
    Year: 2022
    Citations: 10

 

  • Energy-Efficient Deep Q-Network: Reinforcement Learning for Efficient Routing Protocol in Wireless Internet of Things
    Authors: AV Ikechukwu, S Bhimshetty
    Publication: Indonesian Journal of Electrical Engineering and Computer Science
    Year: 2024
    Citations: 8

 

  • xAI: An Explainable AI Model for the Diagnosis of COPD from CXR Images
    Authors: Agughasi Victor Ikechukwu, S Murali
    Publication: 2023 IEEE 2nd International Conference on Data, Decision, and Systems (ICDDS)
    Year: 2023
    Citations: 6

 

  • COPDNet: An Explainable ResNet50 Model for the Diagnosis of COPD from CXR Images
    Authors: AV Ikechukwu, S Murali, B Honnaraju
    Publication: 2023 IEEE 4th Annual Flagship India Council International Subsections Conference
    Year: 2023
    Citations: 6

 

  • The Superiority of Fine-Tuning Over Full-Training for the Efficient Diagnosis of COPD from CXR Images
    Authors: Agughasi Victor Ikechukwu
    Publication: Inteligencia Artificial
    Year: 2024
    Citations: 3

 

  • Leveraging Transfer Learning for Efficient Diagnosis of COPD Using CXR Images and Explainable AI Techniques
    Authors: Agughasi Victor Ikechukwu
    Publication: Inteligencia Artificial
    Year: 2024
    Citations: 2

 

  • Diagnosis of Chronic Kidney Disease Using Naïve Bayes Algorithm Supported by Stage Prediction Using eGFR
    Authors: Agughasi Victor Ikechukwu, Nivedha K, Prakruthi NM, Fathima Farheen, Harini K
    Publication: Not specified in detail
    Year: 2020
    Citations: 1

 

  • Advances in Thermal Imaging: A Convolutional Neural Network Approach for Improved Breast Cancer Diagnosis
    Authors: Agughasi Victor Ikechukwu, Sampoorna Bhimshetty, Deepu R, M.V Mala
    Publication: IEEE Xplore
    Year: 2024
    Citations: Not provided

 

  • Effective Approach for Fine-Tuning Pre-Trained Models for the Extraction of Texts from Source Codes
    Authors: D Shruthi, HK Chethan, VI Agughasi
    Publication: ITM Web of Conferences
    Year: 2024
    Citations: Not provided

Patrícia Takaki | Computer Aided Design In Mechanical Engineering | Best Researcher Award

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 Prof . Patrícia Takaki | Computer Aided Design In Mechanical Engineering | Best Researcher Award

 Prof , Patrícia Takaki ,State University of Montes Claros, Brazil

Prof. Patrícia Takaki is a distinguished academic at the State University of Montes Claros, Brazil. She holds a PhD in [specific field, if known], showcasing her deep expertise and commitment to advancing knowledge in her area of specialization. Prof. Takaki has made significant contributions through her research, which includes numerous publications in reputed journals and conference presentations. Her work primarily focuses on [specific research interests, if known], where she has developed innovative approaches and solutions. In addition to her research, Prof. Takaki is dedicated to teaching and mentoring students, fostering the next generation of scholars and professionals. She is actively involved in various academic and professional communities, contributing to the broader discourse in her field. Prof. Takaki’s dedication to excellence in both research and education has earned her recognition and respect within the academic community.

 

Professional Profiles:

Scopus

Education :

Doctorate in Information Science,Universidade Federal de Santa Catarina (UFSC), Florianopolis, Brazil, 2019
Title: Ciência de Dados aplicada à EaD
Advisor: Moisés Lima Dutra,Keywords: Information Science, Educational Data Mining,Knowledge Areas: Information Science, Computer Science, Information Management,Master’s in Computer Science,Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil, 2001 – 2007,Title: Variações e aplicações do algoritmo de Dijkstra
Advisor: Prof. Dr. Orlando Lee,Keywords: Dijkstra’s Algorithm, Graph Theory, Shortest Paths, Data Structures, Point-to-Point Problem
Knowledge Areas: Graph Theory, Analysis of Algorithms and Computational Complexity,Specialization in Computação Aplicada à Educação
Universidade de São Paulo (USP), Sao Paulo, Brazil, 2018 – 2020,Title: Predição de reprovação na educação a distância: um estudo comparativo,Advisor: Seiji IsotaniGraduation in Computação – ênfase em Sistemas de Informação
Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil, 1996 – 2000,Graduation in Biologia – Licenciatura
Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil,,1997 – 2000Improvement Course in Engenharia de Software,Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil,,2007

Professional Experience:

Universidade Estadual de Montes Claros (UNIMONTES), 2003 – Present,Position: Full-time University Professor at the Department of Computer Science (DCC), Center for Exact and Technological Sciences (CCET),Responsibilities,Faculty member involved in various teaching, research, and administrative roles.,Active in distance education projects at the Open University of Brazil (UAB) at UNIMONTES since 2008.,Coordinated the largest institutional proposal in Brazil under Call 015/CAPES/DED for promoting the use of ICT in undergraduate programs.,Developed educational materials and interactive objects for the training of 43,000 PMMG police officers for TCO registration.,Coordinated the Information Systems Course and Pedagogical Support at the Distance Education Center at UNIMONTES.,Member of the Editorial Board of Unimontes Press and the Business Incubator at Unimontes (Inemontes).

Research and Projects:

Project: Construção de um supercomputador de baixo custo para processamento de alto desempenho utilizando o sistema Beowulf (2008-2009),Description: Installation, configuration, and comparative testing of a high-performance Beowulf cluster.,Members: Patrícia Takaki Neves, Renato Dourado Maia, Hércules Mohamed.

Awards and Recognitions:

  • 2023:,Madrinha da Turma, Formandos do Curso de Sistemas de Informação – UNIMONTES.,Orientadora do trabalho vencedor do Prêmio de Melhor Iniciação Científica da área de Ciências Exatas – UNIMONTES.
  • 2022: Approved for the position of Agente de Tecnologia da Informação, Banco do Brasil.
  • 2020: Professora Homenageada, Formandos do Curso de Sistemas de Informação – UNIMONTES.
  • 2018: Professora Homenageada, Formandos do Curso de Sistemas de Informação – UNIMONTES.
  • 2017:  Madrinhade Formatura Formandos do Curso de istemas de Informação – UNIMONTES.

Publications :

  • 2023: Text mining applied to distance higher education in Education and Information Technologies.
  • 2022: A Proposed Framework for Evaluating the Academic-failure Prediction in Distance Learning in Mobile Networks and Applications.
  • 2012: Utilização de um framework metodológico para avaliação da usabilidade do ambiente virtual de aprendizagem da Unimontes: Virtualmontes in Revista Multitexto.
  • 2012: Sistema de informação para apoio ao controle da leishmaniose visceral na cidade de Montes Claros/MG in Revista Clique.
  • 2002: Interval graphs with repeats and the DNA fragment assembly problem in IC Technical Reports.
  • 2021: Ciência de Dados na Educação: contribuições interdisciplinares at IV Workshop de Informação, Dados e Tecnologia.
  • 2021: Lançamentos dos livros on Competência em Informação at IV Seminário de Pesquisas e Práticas sobre Competência em Informação de Santa Catarina.
  • 2021: Mineração de Dados Educacionais at Congresso Internacional de Tecnologia na Educação.