Mr. Stephen Afrifa | Climate Action | Best Researcher Award
Researcher at University of Energy and Natural Resources, Ghana
Dr. Stephen Afrifa is a dedicated scientific researcher with a passion for innovation, climate science, and technology-driven solutions. With extensive experience in artificial intelligence, machine learning, data science, and geospatial techniques, he applies computational methods to address pressing global challenges, including climate change, public health, and cybersecurity. As a lecturer at the University of Energy and Natural Resources (UENR), he mentors students while leading cutting-edge research initiatives. Dr. Afrifa is also actively engaged in software development, project management, and academic publishing. His strong analytical skills, problem-solving abilities, and leadership in research make him a key figure in advancing knowledge in his field. He has contributed significantly to academia through numerous peer-reviewed publications, conference presentations, and collaborations with international researchers. His commitment to climate activism and educational outreach highlights his dedication to using technology for societal good.
Professional Profile
Education
Dr. Afrifa is currently pursuing a Ph.D. in Information and Communication Engineering at Tianjin University, China, with a focus on speech enhancement, deep learning, and signal processing. He holds a Master of Science in Engineering (Information and Communication Engineering) from the same institution, where he explored machine learning models for climate change analysis. He earned his Bachelor of Science in Information Technology (First Class Honors) from the University of Energy and Natural Resources (UENR), Ghana. His academic foundation is further strengthened by a background in the sciences from Kumasi High School, where he studied Biology, Chemistry, Physics, and Mathematics. Throughout his education, Dr. Afrifa has demonstrated excellence in research, earning prestigious scholarships and academic awards.
Professional Experience
Dr. Afrifa has held various roles in academia and industry. Currently, he is a lecturer at UENR’s Department of Information Technology and Decision Sciences, where he teaches, supervises research, and contributes to faculty projects. Previously, he worked as a senior research assistant in the same department, assisting in student supervision, research design, and data analysis. He has also served as a software application developer and research lead at CY Technologies, where he designed and developed software solutions while leading research initiatives. His experience includes roles in IT support, national service, and research internships, where he contributed to innovative projects such as fire detection systems and AI-driven business solutions. His multidisciplinary expertise spans IT, machine learning, geospatial analysis, and cybersecurity.
Research Interests
Dr. Afrifa’s research focuses on artificial intelligence, machine learning, data science, geospatial analysis, and climate change modeling. He is particularly interested in applying deep learning techniques to areas such as medical imaging, speech recognition, cybersecurity, and environmental monitoring. His work explores the intersection of AI and sustainability, using computational models to assess climate change impacts on groundwater levels and natural disasters. Additionally, he has contributed to studies on public sentiment analysis, network security, and disease detection using AI-driven techniques. His diverse research interests reflect a commitment to leveraging technology for problem-solving and innovation.
Research Skills
Dr. Afrifa is proficient in various programming languages, including Python, R, C/C++, Java, HTML5, JavaScript, and PHP. He has expertise in statistical and AI-based tools such as SPSS, NVIVO, GIS, and GenStat. His skills extend to network security, data analysis, cloud computing, and enterprise resource planning (ERP) systems. He is adept at designing and implementing AI models for predictive analytics, classification, and decision-making. His experience in mentoring students, leading research teams, and publishing in high-impact journals further solidifies his reputation as a skilled researcher. Additionally, his ability to integrate AI, machine learning, and geospatial techniques in real-world applications makes him a valuable contributor to the scientific community.
Awards and Honors
Dr. Afrifa has been recognized for his academic and research excellence. He was awarded the Best Graduating Student in the Department of Computer Science and Informatics at UENR in 2020. He was also a recipient of the Absa Tertiary Scholarship from 2017 to 2020. His research contributions have led to invitations as a peer reviewer for several reputable journals, including those published by Elsevier, Springer, and Emerald. His work has been presented at international conferences, further solidifying his status as a thought leader in his field. His achievements underscore his dedication to advancing knowledge and innovation through rigorous scientific inquiry.
Conclusion
Dr. Stephen Afrifa’s impressive academic and professional journey demonstrates his commitment to research, innovation, and education. His expertise in artificial intelligence, machine learning, climate science, and cybersecurity enables him to address complex global challenges through technology. As a researcher, educator, and mentor, he continues to inspire students and collaborate with international scholars to push the boundaries of scientific discovery. His numerous publications, leadership roles, and industry experience position him as a strong candidate for the Best Researcher Award. His dedication to research excellence, combined with his problem-solving skills and contributions to knowledge, make him a deserving recipient of this recognition.
Publications Top Notes
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Mathematical and machine learning models for groundwater level changes: a systematic review and bibliographic analysis
- Authors: S Afrifa, T Zhang, P Appiahene, V Varadarajan
- Year: 2022
- Citations: 62
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Detection of anemia using conjunctiva images: A smartphone application approach
- Authors: P Appiahene, EJ Arthur, S Korankye, S Afrifa, JW Asare, ET Donkoh
- Year: 2023
- Citations: 32
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Ensemble machine learning techniques for accurate and efficient detection of botnet attacks in connected computers
- Authors: S Afrifa, V Varadarajan, P Appiahene, T Zhang, EA Domfeh
- Year: 2023
- Citations: 31
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VAR, ARIMAX and ARIMA models for nowcasting unemployment rate in Ghana using Google trends
- Authors: WK Adu, P Appiahene, S Afrifa
- Year: 2023
- Citations: 26
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Cyberbullying detection on Twitter using natural language processing and machine learning techniques
- Authors: S Afrifa, V Varadarajan
- Year: 2022
- Citations: 21
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Application of ensemble models approach in anemia detection using images of the palpable palm
- Authors: P Appiahene, SSD Dogbe, EEY Kobina, PS Dartey, S Afrifa, ET Donkoh, …
- Year: 2023
- Citations: 13
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Analyzing sentiments towards e-levy policy implementation in Ghana using Twitter data
- Authors: P Appiahene, S Afrifa, EK Akwah, A Choudhry, I Khatri, C Raj, M Prasad
- Year: 2024
- Citations: 10
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Climate change impact assessment on groundwater level changes: A study of hybrid model techniques
- Authors: S Afrifa, T Zhang, X Zhao, P Appiahene, MS Yaw
- Year: 2023
- Citations: 8
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Using Machine Learning to Classify Network Abnormalities into Legitimate or Assault in IoT-based Cyber Physical System
- Authors: S Afrifa, V Varadarajan, P Appiahene, T Zhang
- Year: 2023
- Citations: 5
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Experiences of sexual minorities on social media: A study of sentiment analysis and machine learning approaches
- Authors: P Appiahene, V Varadarajan, T Zhang, S Afrifa
- Year: 2023
- Citations: 5