Blessing Guembe | Advanced Computing | Best Researcher Award

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Dr. Blessing Guembe | Advanced Computing | Best Researcher Award

PHD at Covenant University, Nigeria

Blessing Guembe is a Research Fellow at the University of Milan, specializing in Explainable AI, Federated Learning, misinformation, privacy, and security. With a Ph.D. in Computer Science from Covenant University, his notable projects include federated learning for asthma prediction and deep learning techniques for malaria diagnosis. He has extensive experience as a senior software developer, having led significant projects at Teesoft Innovations and Reconsoft Nigeria Limited. His technical expertise spans AWS, Azure, Google Cloud, Python, Java, and DevOps, making significant contributions to data analytics and privacy-preserving technologies. Advanced Computing

Professional Profiles

Strengths

Research Contributions:

Explainable AI and Federated Learning: Blessing’s research focuses on cutting-edge areas like explainable AI, federated learning, misinformation, privacy, and security. These topics are highly relevant and impactful in today’s technological landscape.
Publications: Blessing has several notable publications, including reviews on AI-driven cyberattacks and trustworthy machine learning approaches. These publications indicate a strong research output and expertise in cybersecurity and AI.
Projects: Active participation in the KURAMi Project at the University of Milan under Prof. Giovanni Livraga showcases involvement in significant research projects. Advanced Computing

Professional Experience

Research Fellow: Current role at the University of Milan, working on privacy and data protection in social media, demonstrates a focus on real-world applications of research.
Research Assistant: Experience at Covenant University, working on federated learning for medical applications and homomorphic encryption, highlights the practical and impactful nature of Blessing’s work.
Software Development: Extensive experience as a senior software developer at Teesoft Innovations and Reconsoft Nigeria Limited, leading large-scale projects and mentoring junior developers. This indicates strong leadership and technical skills. Advanced Computing

Education

Doctor of Philosophy in Computer Science: Obtained from Covenant University in 2023, reflecting advanced knowledge and research capabilities in the field. Advanced Computing

Technical Skills

Core Competence: Proficiency in various programming languages, cloud platforms, and data science tools (AWS, Azure, Google Cloud Platform, Python, Java, Machine Learning, Deep Learning, XAI, Federated Learning, Privacy-Preserving techniques).
Interdisciplinary Skills: Ability to integrate AI, cybersecurity, and data privacy into research and development projects.

Areas for Improvement

Diversity of Publications:

While the existing publications are strong, increasing the diversity in terms of co-authors and exploring different journals and conferences could enhance visibility and impact. Advanced Computing

Collaborations:

Engaging in more international collaborations and interdisciplinary projects could broaden the scope and application of Blessing’s research.

Grants and Funding:

Securing more research grants and funding would not only support Blessing’s work but also demonstrate the ability to attract resources for innovative projects.

Community Engagement:

Increasing involvement in academic and professional communities, such as presenting at conferences, participating in workshops, and contributing to professional societies, could further establish Blessing as a thought leader in the field.

Publications

  1. Federated Bayesian Optimization XGBoost Model for Cyberattack Detection in Internet of Medical Things, Publication date: 2024.
  3. A Deep Learning Approach For Cassava Leaf Disease Diagnosis, Publication date: 2023.
  4. Explainable artificial intelligence, the fourth pillar of zero trust security, Publication date: 2022.
  5. Machine Learning Techniques for Automatic Long Text Examination in Open and Distance Learning, Publication date: 2022.
  6. The Emerging Threat of Ai-driven Cyber Attacks: A, Publication date: 2022.
  7. Multivariate and Univariate Anomaly Detection in Machine Learning: A Bibliometric Analysis, Publication date: 2022.
  8. Trustworthy Machine Learning Approaches for Cyberattack Detection: A Review, Publication date: 2022.
  9. A machine learning prediction of automatic text based assessment for open and distance learning: a review, Publication date: 2021.
  10. The emerging threat of ai-driven cyber attacks: A review, Publication date: 2022.

 

Conclusion

Blessing Guembe is a strong candidate for the Best Researcher Award due to their significant contributions to explainable AI, federated learning, and cybersecurity. The combination of advanced research, impactful publications, extensive professional experience, and robust technical skills positions Blessing as an influential researcher in the field. Advanced Computing

By enhancing the diversity of publications, seeking more collaborations, securing additional grants, and engaging with the academic community, Blessing could further solidify their standing and potential for future contributions. Overall, Blessing’s profile is highly suitable for consideration for the Best Researcher Award.

 

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Thomas Odey Magu | Computational Method | Best Researcher Award

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Dr. Thomas Odey Magu | Computational Method | Best Researcher Award

PHD at  the University of Florida, United States

Thomas Odey Magu is a Ph.D. candidate in the Department of Chemistry at the University of Florida, specializing in Inorganic Chemistry. He holds an M.Sc. in Physical Chemistry from the University of Calabar, Nigeria, and a B.Sc. in Chemistry from Cross River University of Technology. His research focuses on heterogeneous catalysis, surface science, and computational chemistry. With extensive teaching and research experience, Thomas has received several grants and awards, including from the American Chemical Society and the Royal Society of Chemistry. He is proficient in various analytical techniques and computational tools and is passionate about advancing sustainable energy and environmental solutions.

Professional Profiles

Education

Ph.D. in Chemistry University of Florida, Gainesville, United States (2022-2026) Project: Synthesis, Characterization and Density Functional Theory (DFT) study of Catalysts and their Application in Wastewater treatment and Renewable energy. Status: Currently ongoing M.Sc. in Physical Chemistry University of Calabar, Calabar, Nigeria (2015-2017) Thesis: The Production of biodiesel from Jatropha curcas seeds oil using CoMgFe2O4 and MgFe2O4 as nanocatalysts. GPA: 3.47 B.Sc. in Chemistry Cross River University of Technology (CRUTECH), Calabar, Nigeria (2012-2012) Project: Proximate and Mineral Composition of Cnidoscolus carumbium (Hospital far). GPA: 3.45

Professional Experience

Independent National Electoral Commission (INEC) 2019-03: Collation Officer, Calabar Southward III, Cross River State 2017-11: Collation Officer, Nnewi South Ukpor ward V, Anambra State 2015-02: Presiding Officer, Yala 1 Constituency Idigbo Okpoma-Yala 2012-02: Poll Clerk, Yala 11 Constituency Ntrigon/Mfuma ward

Previous Work Experience

Teaching / Research Assistant Department of Chemistry, University of Florida, USA (2022/08 – 2022/12) Responsibilities: Lead 2 discussion sections and 3 office hours a week Proctor assembly exams Record attendance during discussions Maintain discussion workspace Uphold safety standards Grade discussion assignments (worksheets) Attend weekly TA training Answer student emails Meet instructor prior to exam to be assigned to a room Bring exam materials to an assigned exam room and distribute Walk around during the exam to monitor students Contact the instructor if there is an issue (copies, illness, errors) Collect materials from students (check ID)

Research Interests

Heterogeneous Catalysis and Surface Science Computational/Theoretical Chemistry Energy, Environment and Sustainability

Skills and Expertise

Research and Analytical Skills: Acquired at the University of Florida, USA, and Institute of Chemistry, University of Chinese Academy of Sciences, Beijing, China Basic knowledge of SEM, NMR, GC-MS, X-ray diffractometer Basic knowledge of computational software such as Gaussian, Avogadro, Quantum Espresso, Crystal Explorer, ChemDraw, VEDA, ORCA, Origin, Molden, IboView, VMD, SPSS, Lammps

Grant Awards Received

2022: American Chemical Society, University of Florida Graduate Student Organization (GSO) grant Chapter Start-up 2022: American Chemical Society, Green Chemistry Student Chapter Award, University of Calabar, Nigeria 2021: Research mobility Grant, Royal Society of Chemistry (RSC), Postgraduate Researcher Development Grant

Publications

  1. Solvation effects on the excitation dynamics, structural and photorelaxation, quantum chemical investigation, and photophysical properties of 2D p-expanded quinoidal, Publication date: 2024.
  2. Indonesian Journal of Science & Technology, Publication date: 2024.
  3. Hydrogen storage capacity of Al, Ca, Mg, Ni, and Zn decorated phosphorus-doped graphene: Insight from theoretical calculations, Publication date: 2023.
  4. Electronic, optical, phonon properties, elastic, and the hydrogen storage density of CsXBr3 (X: Be, Mg, Ca) perovskites: Ab-initio calculations and molecular dynamic (MD, Publication date: 2023.
  5. Experimental and theoretical study of the dye-sensitized solar cells using Hibiscus sabdariffa plant pigment coupled with polyaniline/graphite counter electrode, Publication date: 2023.
  6. Eigensolution and Expectation Values of the Hulthen and Generalized Inverse Quadratic Yukawa Potential, Publication date: 2022. 
  7. Density functional theory study of the influence of activating and deactivating groups on Naphthalene, Publication date: 2021.
  8. Solar energy: A panacea for the electricity generation crisis in Nigeria, Publication date: 2021.
  9. Approximate l-States solutions to the Schrodinger equation with Manning-Rosen plus Hellmann potential via WKB approximation scheme, Publication date: 2018.
  10. Evaluation of nutritional value of the termite, Macrotermes bellicosus (Smeathman) and beef,Publication date: 2018.
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Computational Particle Physics

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Introduction to Computational Particle Physics:

Computational Particle Physics represents a vital branch of scientific research at the intersection of particle physics, computer science, and data analysis. It involves the use of advanced computational techniques and high-performance computing to simulate, model, and analyze the behavior of subatomic particles, their interactions, and the outcomes of high-energy experiments. Computational methods are essential for interpreting the vast amount of data produced by particle accelerators and for making precise predictions within the framework of particle physics theories.

Monte Carlo Simulations:

Explore the use of Monte Carlo methods to simulate particle interactions, detector responses, and event generation, crucial for understanding experimental data and developing analysis strategies.

Lattice Quantum Chromodynamics (QCD):

Investigate lattice QCD simulations, which use a discretized spacetime lattice to study the behavior of quarks and gluons within the strong nuclear force, enabling the calculation of hadron properties and masses.

Event Reconstruction and Data Analysis:

Delve into the development of algorithms and software tools for event reconstruction and data analysis in particle physics experiments, including techniques for particle identification and background rejection.

Machine Learning and Artificial Intelligence:

Focus on the integration of machine learning and artificial intelligence techniques for particle physics data analysis, feature extraction, and pattern recognition, aiding in the discovery of new particles and phenomena.

Grid and Cloud Computing:

Examine the use of distributed computing environments, such as grid computing and cloud computing, to handle the immense computational demands of particle physics simulations and data processing.

 

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