Bonface Onyango | Conservation | Best Researcher Award

Posted on by sciencefather

Mr. Bonface Onyango | Conservation | Best Researcher Award

Graduate research fellow at Pwani University/icipe, Kenya.

Bonface Onyango is a dedicated professional with a passion for bioinformatics and computational biology. With a strong educational background in both biochemistry and bioinformatics, Bonface has honed his skills in data analysis, programming, and research methodologies. His extensive experience includes roles as a Graduate Research Fellow at the International Centre of Insect Physiology and Ecology (icipe), where he contributed to the development of biocollections databases and integrative digital platforms. Additionally, Bonface has served as a Medical Representative at Surgipharm Ltd- Abbott Nutrition Int and as a Research Assistant at the Kenya National Bureau of Statistics (KNBS), where he conducted household surveys and field data collection on various research projects. His teaching experience as both a high school teacher and an online tutor reflects his commitment to knowledge dissemination and capacity building. Bonface has also demonstrated leadership and technical expertise in various bioinformatics projects and hackathons, showcasing his ability to innovate and collaborate in multidisciplinary settings. With a keen interest in leveraging data science and machine learning techniques for biological research, Bonface continues to make significant contributions to the field and is poised to excel in his future endeavors.

Professional Profiles:

Education

Bonface Onyango pursued a Bachelor of Science in Biochemistry at Egerton University, Nakuru, Kenya, graduating in 2019. Subsequently, he embarked on his academic journey in Bioinformatics by enrolling in a Master’s program at Pwani University, Kilifi, Kenya, in 2021. He is currently pursuing his Master’s degree, aiming to deepen his knowledge and expertise in this interdisciplinary field.

Professional Experience

Bonface Onyango has accumulated diverse professional experiences across various sectors. As a Graduate Research Fellow at the International Centre of Insect Physiology and Ecology (icipe) in Nairobi, Kenya, from 2021 to 2023, he spearheaded the development of a biocollections database and constructed an integrative digital platform. Prior to this, he served as a Medical Representative at Surgipharm Ltd- Abbott Nutrition Int in Nairobi, Kenya, from 2020 to 2021. In this role, he meticulously detailed products to doctors, conducted continuous medical education to healthcare professionals, and actively participated in scientific webinars focusing on nutritional products. Additionally, his tenure as a Research Assistant at the Kenya National Bureau of Statistics (KNBS) in Kisumu, Kenya, from 2019 to 2020, involved conducting household data collection surveys on post-COVID-19 impact and supervising field data collection on the contribution of Non-Profit Institutions (NPIs) to the country’s economy. His proficiency and leadership skills were further demonstrated during his time as a Content Supervisor at the Kenya National Bureau of Statistics (KNBS) in Siaya, Kenya, in 2019, where he supervised enumerators during the Kenya Population and Housing Census.

Research Interest

Bonface Onyango’s research interests encompass a broad spectrum of topics within the realm of bioinformatics and computational biology. His primary focus lies in leveraging machine learning techniques for the analysis of genomic data, with specific emphasis on predicting the source of pathogens like Salmonella Enterica from whole genome sequencing data. Additionally, he is deeply involved in exploring microbial diversity in COVID-19 patients using AI-driven approaches. His expertise extends to the development of bioinformatics pipelines for ancestry prediction using whole exome data, reflecting his commitment to unraveling complex biological phenomena through computational methods. Moreover, he has a keen interest in reproducible research practices and machine learning applications in diverse biological contexts.

Award and Honors

Throughout his career, Bonface Onyango has received recognition and accolades for his contributions to various fields. Notable among these honors are his appointments as project lead and technical lead in prestigious bioinformatics hackathons and codeathons organized by institutions like the African Society of Bioinformatics and Computational Biology (ASBCB) and Founders Factory Africa. Furthermore, his outstanding performance as a graduate research fellow at the International Centre of Insect Physiology and Ecology (icipe) has been acknowledged, reflecting his dedication and proficiency in developing biocollections databases and integrative digital platforms. Additionally, his role as a content supervisor during the 2019 Kenya Population and Housing Census highlights his commitment to excellence in data collection and management.

Research Skills

Bonface Onyango possesses a diverse set of research skills that enable him to excel in his field. With a solid foundation in bioinformatics and computational biology, he demonstrates proficiency in data analysis, particularly in handling large-scale genomic datasets and applying machine learning algorithms for predictive modeling. His expertise extends to programming languages such as Python, R, and Bash, along with familiarity with Linux environments. Bonface is adept at utilizing various libraries and tools, including Sklearn, Pandas, Numpy, Git, and Docker, to streamline research workflows and facilitate collaboration. Moreover, his proficiency in citation management software such as Zotero, Mendeley, and Latex underscores his meticulous approach to academic writing and publication. Overall, Bonface’s research skills are instrumental in advancing scientific knowledge and addressing complex biological challenges.

 

 

Linzhe Wang | Environmental Science | Best Researcher Award

Posted on by sciencefather

Mr. Linzhe Wang | Environmental Science | Best Researcher Award

Postgraduate at Beijing Information Science & Technology University, China.

Linzhe Wang is a dedicated researcher currently pursuing a master’s degree in electronic information engineering at Beijing Information Science & Technology University. His research interests primarily focus on developing paper-based microfluidic chips for water quality detection and microsensors for detecting heavy metals in water. Linzhe possesses a diverse set of research skills, including experimental design, data analysis, instrumentation, literature review, problem-solving, and collaboration. These skills enable him to conduct rigorous scientific investigations, interpret complex datasets, and contribute meaningfully to advancements in his field. Linzhe’s commitment to addressing critical environmental challenges underscores his potential to make significant contributions to the field of water quality monitoring and management.

Professional Profiles:

Education:

Linzhe Wang completed his bachelor’s degree in automation from Henan University, Kaifeng, Henan, China. Currently, Linzhe is pursuing a master’s degree in electronic information engineering at Beijing Information Science & Technology University, Beijing, China. His academic journey showcases a strong foundation in engineering, particularly in the fields of automation and electronic information engineering.

Research Interest

Linzhe Wang’s research interests encompass two key areas: paper-based microfluidic chips for water quality detection and microsensors for detecting heavy metals in water. In the realm of paper-based microfluidic chips, Linzhe is engaged in the development of innovative platforms aimed at accurately assessing water quality parameters. This pursuit likely involves exploring novel fabrication techniques and integrating advanced sensing technologies into paper-based systems. Additionally, Linzhe is committed to advancing the field of microsensor technology, particularly in the realm of heavy metal detection in water. His research involves designing and optimizing sensitive and selective sensor platforms capable of detecting specific heavy metal contaminants, such as cadmium, lead, and mercury. Linzhe’s work underscores his dedication to addressing critical environmental challenges and advancing the field of water quality monitoring and management.

Research Skills

Linzhe Wang’s research skills are multifaceted and tailored to his field of study. He excels in experimental design, adept at crafting controlled experiments and protocols to ensure reliable outcomes. With a keen grasp of statistical methods and data analysis tools, Linzhe interprets complex datasets with precision, extracting meaningful insights to drive his research forward. Linzhe is well-versed in instrumentation, confidently operating an array of laboratory equipment crucial for his experiments. His meticulous literature reviews contextualize his work within existing scholarship, guiding the trajectory of his research endeavors. Linzhe’s problem-solving prowess enables him to navigate challenges seamlessly, refining methodologies and optimizing protocols. Additionally, his collaborative spirit fosters synergistic teamwork, enhancing innovation and propelling scientific progress. Linzhe Wang’s comprehensive research skills empower him to undertake rigorous investigations, contribute significant findings, and advance knowledge in his field.

Publications

  1. An Electrochemical Sensor Based on Three-Dimensional Porous Reduced Graphene and Ion Imprinted Polymer for Trace Cadmium Determination in Water
    • Authors: Wang, L., Hu, J., Wei, W., Gao, G., Qin, L.
    • Year: 2023
    • Publication: Sensors, 23(23), 9561
  2. Ion Imprinted Polymers Integrated into a Multi-Functional Microfluidic Paper-Based Analytical Device for Trace Cadmium Detection in Water
    • Authors: Hu, J., Wang, L., Song, Y., Wu, J., Mulchandani, A.
    • Year: 2023
    • Publication: Analytical Methods, 16(2), pp. 179–188

 

 

 

Abdulrahman Ahmed Al-Fakih | Renewable Energy Technologies | Best Researcher Award

Posted on by sciencefather

Dr. Abdulrahman Ahmed Al-Fakih | Renewable Energy Technologies | Best Researcher Award

PhD Candidate at College of Petroleum Engineering and Geosciences, King Fahd university of Petroleum & Minerals, Saudi Arabia.

Abdulrahman Ahmed Al-Fakih is a leading researcher specializing in geothermal energy exploration and reservoir characterization, with a focus on applying machine learning techniques in the petroleum industry. His work encompasses a diverse array of topics, including the study of geothermal energy resources, reservoir property prediction, and the application of artificial intelligence in static formation temperature estimation. Through his numerous publications in reputable journals and conference proceedings, Abdulrahman has demonstrated a keen insight into leveraging advanced data analysis methods to enhance understanding and utilization of geothermal resources. He is recognized for his collaborative efforts and interdisciplinary approach, which have contributed significantly to advancing knowledge in geothermal energy exploration and reservoir characterization. Abdulrahman’s dedication to research excellence underscores his commitment to addressing critical challenges and driving innovation in the energy sector.

Professional Profiles:

Education

Abdulrahman Ahmed Al-Fakih is currently pursuing his Ph.D. at King Fahd University of Petroleum and Minerals in Dhahran, Saudi Arabia, from September 2021 to July 2025. His research focuses on the application of artificial intelligence in geophysics, petroleum, and geothermal fields. Prior to this, he obtained his Master’s degree in Energy Resources from the Department of Oil and Gas Fields Development Engineering at China University of Geosciences (Beijing), China, from September 2017 to July 2020. His master’s research centered on Geothermal Energy and Petroleum Engineering, alongside machine and deep learning. Abdulrahman holds a Bachelor’s degree in Petroleum Engineering from Hadhramout University of Science & Technology in Hadhramout, Yemen, which he completed between September 2007 and July 2012. His undergraduate studies covered various aspects of petroleum engineering, including drilling, directional drilling, mud logging, wireline, reservoir engineering, and production engineering. His educational journey began at AbdulNasser, Capital Trust Secondary School in Sana’a, Yemen, where he completed his high school education from September 2003 to July 2006, with a strong emphasis on foundational sciences and mathematics.

Professional Experience

Abdulrahman Ahmed Al-Fakih is currently a Teaching Assistant at King Fahd University of Petroleum and Minerals in Dhahran, where he has been assisting in geophysics courses since September 2021. Previously, he taught Arabic to bachelor’s and master’s students at Beijing Language and Culture University from 2016 to 2020. His industry experience includes internships at Weatherford Oil Tool Middle East Ltd. (2013-2014), where he worked on Tubular Running Services and Wireline Services, and Safer Exploration and Production Operation Company (SEPOC) (2014), where he gained experience in production and safety systems. Additionally, he interned at Calvalley Petroleum in Yemen (2012-2013), focusing on well-site and CPF operations, and at the Petroleum Exploration and Production Authority (PEPA) (2012-2014), training in exploration, drilling, reservoir engineering, and production operations. These experiences have honed his technical skills and adaptability in various practical environments.

Research Interest

Abdulrahman Ahmed Al-Fakih’s research interests focus on the intersection of artificial intelligence and geosciences. His work primarily involves the application of machine learning and deep learning techniques to geophysics, petroleum, and geothermal fields. Abdulrahman is dedicated to exploring innovative AI solutions for complex problems in these areas, leveraging his expertise to advance the understanding and efficiency of subsurface resource exploration and extraction. His research aims to enhance predictive models, optimize resource management, and improve the accuracy of geological and geophysical data interpretation. Through his contributions, he seeks to bridge the gap between cutting-edge technology and practical applications in energy resources and geophysical engineering.

Award and Honors

Abdulrahman Ahmed Al-Fakih has received several prestigious awards and honors throughout his academic and professional journey. In March 2023, he secured second place in the SPWLA Paper Contest, organized by SPWLA-KFUPM-Aramco RDD, recognizing his outstanding research presentation and paper submission. Demonstrating his leadership and community engagement, Abdulrahman was elected Vice-President of the Yemeni Students Union in Beijing, serving from December 2016 to December 2017. In March 2019, he showcased his research expertise by presenting on the Yemen-China Belt and Road Initiative and geothermal energy at the Seventh Annual Deep Geothermal Energy Conference in Beijing. Additionally, Abdulrahman excelled in the First Iranian Statistical Competition held in Tehran, Iran, in 2000. He achieved second place in the individual category for statistical software, highlighting his analytical skills, and also secured second place as part of a team, emphasizing his collaborative problem-solving abilities. These accolades underscore his commitment to excellence and his significant contributions to his field.

Research Skills

Abdulrahman Ahmed Al-Fakih is equipped with advanced research skills essential for his work in geophysics, petroleum, and geothermal energy. Proficient in machine learning and deep learning, he employs Python and MATLAB for data analysis and modeling. With strong analytical capabilities, Abdulrahman interprets complex datasets using geophysical and petroleum engineering software like Petrel and Eclipse. His adeptness in project management and teamwork ensures efficient collaboration and goal achievement. Known for his leadership and mentorship, he inspires others in their research pursuits. With a collaborative approach and commitment to excellence, Abdulrahman contributes significantly to advancing knowledge and innovation in his field.

Publications

  1. Study of geothermal energy resources of Yemen for electric power generation”
    • Authors: A. Al-Fakih, K. Li
    • Year: 2018
    • Citations: 7
  2. “Estimating electrical resistivity from logging data for oil wells using machine learning”
    • Authors: A. Al-Fakih, AF Ibrahim, S. Elkatatny, A. Abdulraheem
    • Year: 2023
    • Citations: 4
  3. “Estimation of bottom-hole temperature based on machine/deep learning”
    • Authors: A. Al-Fakih, KW Li
    • Year: 2021
    • Citations: 3
  4. “Application of Artificial Intelligence in static Formation temperature estimation”
    • Authors: A. Al-Fakih, S. Kaka
    • Year: 2023
    • Citations: 2
  5. “Reservoir Property Prediction in the North Sea Using Machine Learning”
    • Authors: A. Al-Fakih, S. Kaka, AI Koeshidayatullah
    • Year: 2023
    • Citations: 2
  6. “Neuro-Fuzzy Approach for Gas Compressibility Factor Prediction”
    • Authors: AA Al-Gathe, AM Al-Khudafi, A. Al-Fakih, AA Al-Wahbi
    • Year: 2021
    • Citations: 2
  7. “Exploring Machine Learning Techniques for Predicting Geothermal Temperature in Western Yemen”
    • Authors: SIK Abdulrahman Al-Fakih, Abbas Alkhudafi, A. Koeshidayatullah
    • Year: 2024
  8. “Deep Learning in Reservoir Characterization: a GAN-based Approach”
    • Authors: AAA Al-Fakih, S. Kaka, A. Koeshidayatullah
    • Year: 2024
  9. “Enhancing Geoscience Analysis: AI-Driven Imputation of Missing Data in Well Logging Using Generative Models”
    • Authors: A. Al-Fakih, A. Koeshidayatullah
    • Year: 2024
  10. “Unlocking the Potential of Geothermal Energy in Yemen: A Comparative Analysis with Global Trends”
    • Authors: A. Al-Fakih, A. Al-Khudafi
    • Year: 2024