Olukayode Oki | Artificial Intelligence | Best Researcher Award

Dr. Olukayode Oki | Artificial Intelligence | Best Researcher Award 

Senior Lecturer at Walter Sisulu University, South Africa

Dr. Olukayode A. Oki is a prominent figure in the field of computer science, specializing in cognitive radio networks, wireless communications, and cybersecurity. With a robust academic career, he currently serves as a Senior Lecturer in the Information Technology Department at Walter Sisulu University, South Africa. Dr. Oki is renowned for his contributions to both teaching and research, focusing on innovative approaches to spectrum decision-making and the application of machine learning in cybersecurity. His dedication to fostering academic excellence and mentorship is evident in his involvement in guiding numerous undergraduate and postgraduate students through their research projects.

Profile

ORCID

Education

Dr. Oki’s educational background is distinguished by three significant academic achievements. He completed his Ph.D. in Computer Science at the University of Zululand, South Africa, in 2019. His doctoral research focused on “Spectrum Decision Making in Distributed Cognitive Radio Networks using an Optimal Foraging Approach,” highlighting his expertise in cognitive radio technology. Prior to this, he obtained his M.Sc. in Computer Science from the same institution in 2014, where he evaluated the impact of quality of service mechanisms in power-constrained wireless mesh networks. His academic journey began with a B.Tech (Hons.) in Computer Science and Engineering from Ladoke Akintola University of Technology, Nigeria, in 2007, where he explored data mining in educational databases.

Experience

Dr. Oki has garnered extensive teaching experience over the years. Since January 2023, he has held the position of Senior Lecturer at Walter Sisulu University, following his tenure as a Lecturer in the same department from March 2020 to December 2022. His teaching philosophy emphasizes practical learning, team collaboration, and a learner-centered approach, aiming for a 70% pass rate among his students. Dr. Oki has developed and delivered a range of courses at both undergraduate and postgraduate levels, including Application Development Technology, Python Programming for Data Science, and Wireless Ad Hoc Networks. He has also contributed significantly to curriculum development, course design for new programs, and the creation of teaching materials.

Additionally, Dr. Oki has a notable research background, having supervised several Master’s and Honours candidates and having published collaboratively with students. His experience includes examining dissertations for multiple universities, which demonstrates his engagement with the academic community.

Research Interests

Dr. Oki’s research interests span a variety of critical areas within computer science. His primary focus lies in cognitive radio networks, where he investigates optimal spectrum decision-making strategies. He is also interested in wireless mesh networks and their quality of service mechanisms. In recent years, Dr. Oki has delved into cybersecurity, particularly the application of machine learning to enhance data security and develop intelligent systems for fraud detection. His active participation in research projects has led him to mentor both Master’s and PhD candidates, fostering a new generation of researchers in the field.

Awards

Dr. Oki has received several prestigious awards in recognition of his research contributions and academic excellence. He has been honored as a South Africa National Research Foundation (NRF) Rated Researcher for the period 2022-2027, which highlights his significant contributions to the field. In addition, he received the Vice Chancellor’s Distinguished Research Award in 2022 and was recognized as a Highly Productive Emerging Researcher by Walter Sisulu University in the same year. His affiliation with the London Journal Press as an Honorary Rosalind Member further underscores his impact on academic publishing and research.

Publications

Dr. Oki has an extensive list of publications, showcasing his commitment to advancing knowledge in computer science. His work includes contributions to books, refereed journals, and conference proceedings, with a focus on topics such as machine learning, cognitive radio technology, and education in technology. Some notable publications include:

Oki, O. A., Uleanya, C., & Mbanga, S. (2023). “Echoing the effect of information and communications technology on rural education development.” Technology Audit and Production Reserves, 1(2), 6–14. Link

Rawat, R., Oki, O.A., Sankaran, K.S., Florez, H., & Ajagbe, S. (2023). “Techniques for predicting dark web events focused on the delivery of illicit products and ordered crime.” International Journal of Electrical and Computer Engineering (IJECE), 13(5), 5354-5365. Link

Nigar, N., Shahzad, M. K., Islam, S., Oki, O., & Lukose, J. (2023). “Multi-Objective Dynamic Software Project Scheduling: A Novel Approach.” IEEE Access, 11, 39792-39806. Link

Rawat, R., Oki, O.A., Chakrawarti, R., Adekunle, T., Lukose, J., & Ajagbe, S. (2023). “Autonomous Artificial Intelligence Systems for Fraud Detection and Forensics in Dark Web Environments.” Informatica, 47, 51–62. Link

Ajiboye, O. K., Ofosu, E. A., Gyamfi, S., & Oki, O. (2023). “Hybrid Renewable Energy System Optimization via Slime Mould Algorithm.” International Journal of Engineering Trends and Technology, 71(6), 83-95. Link

Lukose, J., Mwansa, G., Ngandu, R., & Oki, O. (2023). “Investigating the Impact of Social Media Usage on the Mental Health of Young Adults in Buffalo City, South Africa.” International Journal of Social Science Research and Review, 6(6), 303-314. Link

Nigar, N., Shahzad, M. K., Islam, S., Oki, O., & Lukose, J. “A Novel Multi-Objective Evolutionary Algorithm to Address Turnover in the Software Project Scheduling Problem.” IEEE Access, 11, 89742-89756, 2023.

Nigar, N., Faisal, H. M., Shahzad, M. K., Islam, S., & Oki, O. (2022). “An Offline Image Auditing System for Legacy Meter Reading Systems in Developing Countries: A Machine Learning Approach.” Journal of Electrical and Computer Engineering, 2022, Article ID 4543530. Link

Oki, O.A., Ajagbe, S.A., Mahanjana, A., & Afolabi, O.S. (2022). “Investigating the adoption of Smart Healthcare Monitoring System in the Rural Area.” PONTE International Scientific Researches Journal, 78(9). Link

Oki, O.A., & Lawrence, M.O. (2022). “The cost-effectiveness of fibre optic technology deployment in rural areas: a case study of Mdantsane.” Journal on Innovation and Sustainability RISUS, 13(2), 111-123. Link

Nigar, N., & Oki, O.A. (2022). “Software Project Scheduling: A Systematic Literature Review.” COJ Robotics and Artificial Intelligence, 2(3).

Oki, O.A., Olwal, T.O., & Adigun, M.O. (2021). “Performance Analysis of FISSER Model in Rural-Urban Cognitive Radio Networks.” Journal of Physics: Conference Series, 1995, 012013. Link

Conclusion

Olukayode A. Oki is a highly qualified and deserving candidate for the Best Researcher Award. His academic achievements, numerous awards, and significant contributions to research in Computer Science, especially in wireless networks, AI, and cognitive radio, highlight his excellence. Enhancing industry collaboration, interdisciplinary research, and international visibility could further solidify his standing as a global leader in his field.

Xinyu Gu | Artificial Intelligence | Excellence in Research

Dr. Xinyu Gu | Artificial Intelligence | Excellence in Research 

Researcher | The University of Wollongong | Australia

Based on the provided details about Xinyu Gu, here’s an analysis of their suitability for a Research for Excellence in Research award with a focus on “Strengths for the Award, Areas for Improvement, and Conclusion”:

Strengths for the Award

  1. Advanced Expertise in Machine Learning and AI:
    • Xinyu Gu has a solid proficiency in various machine learning and deep learning models (e.g., SVM, RNN, LSTM, CNN, BERT), which demonstrates a high level of technical expertise in the field.
    • Their skill set includes Python programming and familiarity with popular frameworks like PyTorch and TensorFlow, which are crucial for cutting-edge research in AI.
  2. Relevant Academic Background:
    • Xinyu holds a Ph.D. in Artificial Intelligence and a Master’s degree in the same field from prestigious universities (University of Wollongong and University of New South Wales). Their academic credentials are complemented by awards such as the University Postgraduate Scholarship and China National Scholarship.
  3. Strong Publication Record:
    • The individual has published multiple high-impact papers in SCI Q1 journals and conferences. This includes first-author papers in journals with high impact factors like Energy, Journal of Power Sources, and International Journal of Rock Mechanics and Mining Sciences. This track record indicates significant contributions to the field and recognition by peers.
  4. Diverse Research Experience:
    • Xinyu’s work history includes substantial research experience in industry and academia, with contributions to projects involving advanced lithium-ion battery technologies and innovative power solutions for mining applications.
    • Their involvement in research projects with renowned institutions like CSIRO and UNSW reflects strong collaborative skills and the ability to work on impactful research.
  5. Technical and Soft Skills:
    • They exhibit strong skills in data analysis, visualization, and literature review, essential for conducting high-quality research.
    • Their effective communication in English, both in writing and speaking, is supported by a high IELTS score and active engagement in academic conferences.

Areas for Improvement

  1. Broader Research Impact:
    • While Xinyu has an impressive publication record, expanding research contributions to more diverse areas within AI or interdisciplinary fields could further enhance their profile. Exploring applications in emerging areas such as quantum computing or ethical AI could be beneficial.
  2. Leadership and Mentorship Experience:
    • There is limited information on leadership roles or mentoring experience. Taking on more leadership responsibilities in research projects or guiding junior researchers could strengthen their profile as a leading researcher.
  3. Grant Acquisition:
    • Experience in securing research grants or funding is not highlighted. Demonstrating success in obtaining research grants could add a valuable dimension to their research profile.
  4. Broader Dissemination and Outreach:
    • Increasing efforts in public engagement, such as participating in outreach activities or public science communication, could enhance the societal impact of their research and increase visibility.

Short Bio

Xinyu Gu is a skilled researcher specializing in artificial intelligence, with a profound expertise in machine learning and deep learning techniques. Currently a Research Associate at Azure Mining Technology Pty Ltd in Sydney, Xinyu excels in applying advanced AI models to solve real-world problems in energy and mining industries. With a Ph.D. in Artificial Intelligence from the University of Wollongong, Xinyu has made significant contributions to the field through both academic research and industry projects, showcasing a strong commitment to innovation and problem-solving.

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Google Scholar

Education

Xinyu Gu completed a Ph.D. in Artificial Intelligence at the University of Wollongong in November 2023, where they were awarded the University Postgraduate Scholarship and Tuition Fees Waiver Award. Prior to this, they earned a Master’s degree in Artificial Intelligence from the University of New South Wales in December 2020, and a Bachelor’s degree in Mechanical Engineering from Nanjing Technology University, China, in June 2018. Xinyu’s academic journey has been marked by excellence and recognition, including the China National Scholarship Award.

Experience

In their current role as a Research Associate at Azure Mining Technology Pty Ltd since February 2020, Xinyu Gu has managed and coordinated numerous research projects in collaboration with top academic and research institutions, such as the University of New South Wales and CSIRO. Their work involves developing advanced power solutions for mining applications and managing cybersecurity and website development for the company. Previously, Xinyu interned as a Data Analyst at Dr Aha Data & AI Technology, where they honed their skills in data visualization and machine learning.

Research Interest

Xinyu Gu’s research interests lie at the intersection of machine learning, deep learning, and their applications in energy and mining sectors. They focus on enhancing the performance and safety of energy storage systems, particularly lithium-ion batteries, and applying AI techniques to predict and manage power sources in challenging environments. Their work includes exploring novel methods for state-of-charge estimation, state-of-health prediction, and improving safety in mining technologies.

Awards

Xinyu Gu has been recognized with several prestigious awards throughout their academic and professional career. These include the University Postgraduate Scholarship and Tuition Fees Waiver Award from the University of Wollongong, the China National Scholarship Award, and various acknowledgments for research excellence in publications and conferences.

Publication

  1. Energies, SCI Q2, Impact Factor: 3.2 (2023)
    • X. Gu, K.W. See, Y. Wang, L. Zhao, W. Pu. The sliding window and SHAP theory—an improved system with a long short-term memory network model for state of charge prediction in electric vehicle application.
    • Cited by: 15
  2. Energy, SCI Q1, Impact Factor: 9.2 (2023)
    • X. Gu, K.W. See, P. Li, K. Shan, Y. Wang, L. Zhao, K.C. Lim, N. Zhang. A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model.
    • Cited by: 22
  3. Journal of Power Sources, SCI Q1, Impact Factor: 9.72 (2023)
    • X. Gu, K.W. See, Y. Liu, B. Arshad, L. Zhao, Y. Wang. A time-series Wasserstein GAN method for state-of-charge estimation of lithium-ion batteries.
    • Cited by: 18
  4. International Journal of Rock Mechanics and Mining Sciences, SCI Q1, Impact Factor: 7.1 (2023)
    • X. Gu, C. Zang, K.W. See, B. Arshad, Y. Sun, Z. Liu, G. Xu, Y. Wang, S. Dai, X. Zhou, Y. Niu. Machine learning approaches for short-term and long-term prediction of strata pressure for coal mining applications.
    • Cited by: 12
  5. IEEE Conference 2023 (Accepted)
    • X. Gu, K.W. See, X. Wu, Y. Wang, C. Zang. Data preprocessing and machine learning approaches in battery’s state of charge and state of health estimation: a review.
    • Cited by: 7
  6. International Journal of Coal Science and Technology, SCI Q1, Impact Factor: 5.79 (2023)
    • K.W. See, G. Wang, Y. Zhang, Y. Wang, L. Meng, X. Gu*, N. Zhang, K.C. Lim, L. Zhao, B. Xie. Critical review and functional safety of a battery management system for large-scale lithium-ion battery pack technologies.
    • Cited by: 10
  7. Industrial & Engineering Chemistry Research, SCI Q1, Impact Factor: 4.2 (2023)
    • Z. Xie, X. Gu, Y. Shen. A machine learning study of predicting mixing and segregation behaviors in a bidisperse solid-Liquid Fluidized Bed.
    • Cited by: 9
  8. Journal of Environmental Management, SCI Q1, Impact Factor: 8.70 (2023)
    • X. Wu, P. Li, X. Gu*, K.W. See, J. Li. A Bpnn-Transformer for air quality index prediction.
    • Cited by: 8

Conclusion

Xinyu Gu shows strong qualifications for the Research for Excellence in Research award, with notable strengths in technical expertise, academic achievements, and research impact. Their extensive publication record and experience with advanced machine learning techniques position them as a strong candidate for recognition.

Puranam Revanth Kumar | Artificial Intelligence and Machine Learning | Best Researcher Award

Dr.Puranam Revanth Kumar | Artificial Intelligence and Machine Learning | Best Researcher Award

Assistant Professor Malla Reddy University, Hyderabad, India. 

Dr. Puranam Revanth Kumar is an Assistant Professor at Malla Reddy University, Hyderabad, specializing in Artificial Intelligence and Machine Learning. His research focuses on image processing, deep learning, and biomedical imaging, with significant contributions to neuroimaging. He holds a Ph.D. in Electronics and Communication Engineering from ICFAI University, Hyderabad.

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Google Scholar

📚 Education

  • Ph.D., Electronics and Communication Engineering, ICFAI University, Hyderabad, India, 2019-2024.
  • M.Tech, Control and Instrumentation, AMRITA University, Coimbatore, India, 2017-2019.
  • B.Tech, Electronics and Instrumentation, GITAM University, Hyderabad, India, 2012-2016.

👨‍💼 Experience

  • Assistant Professor, Department of Artificial Intelligence and Machine Learning, Malla Reddy University, Hyderabad, India (2024-present).
  • LabVIEW Software Trainee, Optomech Engineers Pvt. Ltd., Hyderabad, India (2018-2019).

🔍 Research Interests

Dr. Kumar’s research interests include image processing, deep learning, machine learning, neuroimaging, biomedical imaging, and artificial intelligence applications in healthcare.

🏆 Award

  • Deep Learning Award, NPTEL.
  • Machine Learning Award, Coursera.
  • MATLAB on-ramp Award, MathWorks.

📄 Publications