Mahad Rashid | Machine Learning | Best Researcher Award

Mr Mahad Rashid | Machine Learning | Best Researcher Award

Senior Analytics Consultant at WorkSafe VIC, Australia

Mahad Rashid is an enthusiastic and skilled Analytics Consultant with a Master’s degree in Data Science from Deakin University. With over six years of experience in data analysis, machine learning, and software engineering, Mahad has a proven track record of developing data-driven solutions to enhance business operations and customer experiences. Proficient in Python, SAS, SQL, and data visualization tools like Power BI and Qlik, he has worked in diverse roles, including Senior Analytics Consultant at WorkSafe Victoria and Research Engineer at the Applied Artificial Intelligence Institute. Mahad is passionate about leveraging data to drive innovation and deliver impactful results. His expertise spans machine learning, deep learning, and statistical analysis, with a strong focus on MLOps and AI deployment. Mahad is also an effective communicator, capable of translating complex technical concepts for non-technical stakeholders.

Professional Profile

Scopus

Education 🎓

Mahad Rashid holds a Master of Data Science from Deakin University, Burwood (2019–2021), where he honed his skills in data analysis, machine learning, and AI. Prior to this, he completed his Bachelor of Software Engineering from the National University of Sciences and Technology, Pakistan (2014–2018), gaining a strong foundation in programming, software development, and data structures. Throughout his academic journey, Mahad demonstrated a keen interest in applying data science to solve real-world problems. He has also pursued additional certifications, including Getting Started with SAS Programming and Git and GitHub on Coursera (2024), showcasing his commitment to continuous learning and professional development.

Experience 💼

Mahad Rashid has a rich professional background spanning over six years. As a Senior Analytics Consultant at WorkSafe Victoria (2023–Present), he excels in data extraction, cleaning, and machine learning using Python and SQL. He also mentors junior consultants and creates insightful dashboards using Power BI. Previously, as a Research Engineer at the Applied Artificial Intelligence Institute, Deakin (2021–2023), he developed and deployed ML models, applied MLOps principles, and collaborated on AI research. Earlier, as a Software Engineer at CureMD, Pakistan (2018–2019), he designed machine learning applications and advanced data visualizations. Mahad’s expertise lies in leveraging data to drive innovation, improve decision-making, and deliver impactful solutions across industries.

Awards and Honors 🏆

While specific awards and honors are not explicitly mentioned in the provided profile, Mahad Rashid’s contributions to data science and AI research are evident through his publications and professional achievements. His work on high-voltage lithium cathode materials, published in ACS Applied Energy Materials (2024), highlights his involvement in cutting-edge research. Additionally, his role in mentoring junior consultants and leading analytics projects at WorkSafe Victoria underscores his recognition as a skilled and reliable professional. Mahad’s commitment to continuous learning, evidenced by his certifications in SAS and Git, further reflects his dedication to excellence in the field of data science.

Research Focus 🔍

Mahad Rashid’s research focuses on applying machine learningdeep learning, and AI to solve complex problems across various domains. His work includes developing and deploying ML models for classification, regression, and image detection, as well as applying MLOps principles to streamline data science workflows. He has also contributed to research on high-voltage lithium cathode materials using Bayesian optimization and first-principles studies, showcasing his interdisciplinary expertise. Mahad is passionate about leveraging data-driven approaches to improve business operations, enhance customer experiences, and drive innovation. His research interests extend to data visualizationstatistical analysis, and AI-driven decision-making, with a strong emphasis on delivering practical, impactful solutions.

Publication Top Notes 📚

  1. High-Voltage, High Capacity Aluminum-Rich Lithium Cathode Materials: A Bayesian Optimization and First-Principles Study – ACS Applied Energy Materials, 2024.

Conclusion 🌟

Mahad Rashid is a highly skilled and passionate data science professional with a strong academic background and extensive industry experience. His expertise in data analysis, machine learning, and AI, combined with his ability to communicate complex ideas effectively, makes him a valuable asset to any organization. Mahad’s commitment to innovation, continuous learning, and delivering impactful results positions him as a leader in the field of data science and analytics.

 

Subhadip Pramanik | Data-Driven Evolutionary Optimization | Best Researcher Award

Dr Subhadip Pramanik | Data-Driven Evolutionary Optimization | Best Researcher Award

Assistant Professor, Kalinga Institute of Industrial Technology (KIIT) Deemed to Be University, India

Dr. Subhadip Pramanik is an accomplished academic and researcher specializing in Data Science and Artificial Intelligence. He earned his Ph.D. in Data Science & AI from IIT Kharagpur in 2023. With a strong educational foundation in applied mathematics and computer science, Dr. Pramanik has made significant contributions to the field of evolutionary optimization and machine learning. Currently, he serves as an Assistant Professor at the Kalinga Institute of Industrial Technology, Bhubaneswar, India, where he teaches advanced topics in computer science. His prolific research has been published in leading journals, and he has received accolades such as the Best Paper Award at IEEE INDICON 2021.

PROFILE

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Orcid

Scopus

STRENGTHS FOR THE AWARD

  1. Academic Excellence:
    • Holds a Ph.D. in Data Science and AI from IIT Kharagpur, one of the most prestigious institutions in India.
    • Demonstrated exceptional academic performance throughout, including high scores in M.Tech and M.Sc.
  2. Significant Research Contributions:
    • Published extensively in reputed journals and conferences, including Mathematics, Structural and Multidisciplinary Optimization, and Applied Intelligence.
    • Innovations such as adaptive model selection frameworks and nature-inspired algorithms showcase expertise in solving real-world optimization problems.
    • The award-winning research on “GL-DDEA” highlights the practical impact and originality of contributions in AI and Data Science.
  3. Recognitions:
    • Best Paper Award in the AI & Data Science Track at IEEE INDICON 2021, a testament to the quality and impact of his work.
    • Strong citation and publication record reflecting a high level of research engagement.
  4. Diverse Work Experience:
    • Currently serving as an Assistant Professor at KIIT, mentoring undergraduate students in advanced topics such as Data Analytics, AI, and DBMS.
    • Prior experience as a Research Fellow at IIT Kharagpur involved developing groundbreaking methods for engineering optimization.
  5. Technical Expertise:
    • Specialized in cutting-edge domains such as evolutionary algorithms, surrogate modeling, and high-utility itemset mining.
    • Proficiency in applying research methodologies to solve expensive, data-driven optimization problems, bridging theory and application.

AREAS FOR IMPROVEMENT

  1. Broader Collaborative Research:
    • While his contributions are notable, expanding collaborations with international researchers could elevate the global visibility of his work.
  2. Industry Engagement:
    • Engagement in industry-funded projects or partnerships could demonstrate real-world applications of his research.
  3. Interdisciplinary Applications:
    • Exploring applications of his frameworks in areas beyond engineering optimization, such as healthcare or environmental science, may further diversify his portfolio.

EDUCATION

Dr. Pramanik has an extensive academic background:

  • Ph.D. in Data Science & AI, IIT Kharagpur (2018–2023)
  • M.Tech. in Computer Science & Data Processing, IIT Kharagpur (2016–2018, CGPA 8.61/10)
  • M.Sc. in Applied Mathematics, Vidyasagar University (2014–2016, 77%)
  • B.Sc. in Mathematics, Vidyasagar University (2011–2014, 65.75%)
  • Higher Secondary (82.8%) and Secondary (83.5%) Examinations completed in West Bengal.

This foundation underscores his expertise in applying mathematical rigor to solve complex engineering problems using AI and data science.

EXPERIENCE

Dr. Pramanik is currently an Assistant Professor at Kalinga Institute of Industrial Technology, where he teaches Data Analytics, AI, and Python to undergraduates. His research fellowship at IIT Kharagpur (2018–2023) resulted in pioneering contributions like developing evolutionary algorithms for solving expensive engineering optimization problems. His notable projects include a novel framework utilizing ant colony systems for mining high-utility itemsets and innovative surrogate modeling approaches for multi-objective optimization. With practical teaching and research experience, Dr. Pramanik bridges academic rigor with real-world applications.

AWARDS & HONORS 🏆

  • Best Paper Award in AI & Data Science Track, IEEE INDICON 2021
  • GATE 2016 Qualified: Scored 532 in Mathematics
  • Numerous accolades for his impactful publications and contributions to Data Science & AI research.

RESEARCH FOCUS 🔬

Dr. Pramanik focuses on evolutionary optimization, active learning, and data-driven decision-making. His research interests include:

  • Data-Driven Multi-Objective Optimization: Using adaptive and reliable frameworks for engineering challenges.
  • High-Utility Pattern Mining: Ant colony systems for large transactional datasets.
  • Surrogate Modeling: Combining global and local models for efficiency in offline and incremental data optimization.

PUBLICATION TOP NOTES 📚

  1. AdaMoR-DDMOEA: Adaptive Model Selection Framework for Offline Optimization (Mathematics, 2025)
  2. ALeRSa-DDEA: Active Learning and Reliability Sampling for Expensive Optimization (SMO, 2022)
  3. GL-DDEA: Surrogate-Based Framework for Offline Optimization (IEEE INDICON, 2021)
  4. Ant Colony Algorithm: Mining Closed High-Utility Itemsets (Applied Intelligence, 2021)

CONCLUSION

Subhadip Pramanik is an outstanding candidate for the Best Researcher Award due to his exemplary academic record, innovative research contributions, and impactful publications. His award-winning work and continued commitment to advancing Data Science and AI demonstrate his potential to excel further in his field. With additional focus on interdisciplinary and global collaborations, he could strengthen his position as a leading researcher in his domain.

Sina Fard Moradinia | Machin Learning | Best Researcher Award

Assist. Prof. Dr Sina Fard Moradinia | Machine Learning | Best Researcher Award

Reviewer&Editor, Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

Dr. Sina Fard Moradinia is an Assistant Professor in the Department of Civil Engineering at Islamic Azad University, Tabriz Branch, Iran. He specializes in water resource management, hydrology, hydraulic engineering, computational fluid dynamics, and the application of machine learning in civil engineering. With a strong academic background and a focus on integrating advanced technologies, Dr. Fard Moradinia has contributed significantly to research in sustainable construction, water management, and infrastructure optimization. His work is recognized for its innovative approaches to environmental and structural challenges, particularly in dam construction, flood prediction, and water resource forecasting. He has authored several peer-reviewed papers and participated in numerous academic and professional conferences.

Profile

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Strengths for the Award

Dr. Sina Fard Moradinia is a highly accomplished researcher and educator in civil engineering, particularly in the areas of water resource management, hydrology, hydraulics, and computational fluid dynamics. His research contributions are diverse and impactful, addressing key challenges in dam construction, flood risk prediction, and sustainable water management. Dr. Fard Moradinia’s ability to integrate machine learning with traditional engineering models to solve complex problems stands out as a significant strength. His extensive body of work, evidenced by multiple publications in high-impact journals, reflects his proficiency in both theoretical and applied research, especially in projects that integrate Building Information Modeling (BIM), System Dynamics, and ANFIS models for project optimization.

Dr. Fard Moradinia has demonstrated leadership in his field through innovative research in human resource risk analysis in construction, water quality management, and the use of computational models to optimize construction project time and cost. His work on flood flow prediction and seepage analysis in earth dams is a testament to his ability to address real-world infrastructure challenges with advanced methodologies.

Areas for Improvements

While Dr. Fard Moradinia has a robust and impressive portfolio of research, there are a few areas where improvements or further development could enhance his profile for recognition.

  1. Broader Global Collaboration: Although his work is highly relevant within the local context of Iran, expanding his collaborative efforts with international researchers, especially in global water management issues or climate change adaptation strategies, could increase the global impact of his research.
  2. Interdisciplinary Approaches: There is an opportunity for Dr. Fard Moradinia to explore more interdisciplinary research areas, such as the integration of civil engineering with environmental science, data analytics, or sustainable urban planning. This could make his work even more relevant to the global discourse on climate change and urban sustainability.
  3. Public Engagement and Outreach: While his academic and research credentials are strong, increasing his presence in public and policy-making circles, particularly in the context of water crisis management and sustainable infrastructure, could make his work more impactful outside academia.

Education 

Dr. Sina Fard Moradinia holds a Ph.D. in Civil Engineering, focusing on hydrology and water resources management, from an esteemed institution in Iran. His academic journey includes both Bachelor’s and Master’s degrees in Civil Engineering, where he developed a solid foundation in fluid dynamics, hydrology, and structural engineering. Dr. Fard Moradinia has continually expanded his expertise through advanced research in the application of computational techniques, including machine learning algorithms for solving complex civil engineering problems. His educational background reflects a commitment to both theoretical and practical aspects of civil engineering, preparing him for an impactful academic career in the field.

Experience 

Dr. Sina Fard Moradinia has accumulated a wealth of experience in both academic and research settings. As an Assistant Professor at Islamic Azad University in Tabriz, he teaches and mentors students in civil engineering, with an emphasis on hydrology, water resource management, and advanced computational methods. In addition to his teaching role, he is actively involved in high-impact research projects, collaborating with professionals in the fields of water resources, infrastructure, and construction management. His research spans areas such as flood prediction, water quality management, construction project optimization, and the use of artificial intelligence for infrastructure analysis. Dr. Fard Moradinia has also applied his expertise in industry-focused projects, working with governmental and private organizations to enhance the design and management of civil infrastructure, particularly in dam construction, flood mitigation, and reservoir management.

Awards and Honors

Dr. Sina Fard Moradinia’s research has garnered recognition from various academic and professional institutions. His publications have received multiple citations, attesting to the impact of his work in civil engineering, hydrology, and water resource management. He has been honored with awards for his contributions to research and education, including recognition for excellence in the application of machine learning techniques to civil engineering problems. Dr. Fard Moradinia has been invited to speak at international conferences and serve on editorial boards for leading journals in his field. Additionally, his role as a reviewer for numerous scholarly publications further solidifies his standing as a respected figure in his domain. His collaborative efforts with industry partners have also resulted in several successful projects aimed at improving infrastructure sustainability and management in Iran.

Research Focus

Dr. Sina Fard Moradinia’s research focuses on applying advanced computational techniques to solve pressing issues in civil engineering, particularly in the areas of water resources management, hydrology, and hydraulic engineering. His work explores innovative solutions for flood prediction, aquifer management, and sustainable water usage, with a strong emphasis on integrating machine learning and artificial intelligence. Dr. Fard Moradinia also investigates the optimization of construction projects, particularly in the context of dam and reservoir management, where he applies Building Information Modeling (BIM) and system dynamics to improve project efficiency and reduce risks. Another key area of his research is the analysis of environmental factors influencing civil infrastructure, such as the impact of sludge discharge in wastewater systems. Through his work, he aims to advance both the scientific understanding of hydrological systems and the practical tools available for managing water resources and infrastructure projects.

Publication Top Notes

  • “Toward Nearly Zero Energy Building Designs: A Comparative Study of Various Techniques” 🌱🏢
  • “Time and Cost Management of Dam Construction Projects Based on BIM” 💼🏞️
  • “The Role of BIM in Reducing the Number of Project Dispute Resolution Sessions” ⚙️💬
  • “Wavelet-ANN Hybrid Model Evaluation in Seepage Prediction in Nonhomogeneous Earth Dams” 🌊🧠
  • “Optimization of Quantitative and Qualitative Indicators of Construction Projects” ⚙️📊
  • “An Approach for Flood Flow Prediction Using New Hybrids of ANFIS” 🌧️🔮
  • “Forecasting the Level of Aquifers in the Ajab Shir Plain with Different Management Scenarios” 💧🔍
  • “Development of an ANFIS Model for Human Resource Risk Analysis in Construction” 🏗️🧑‍💼
  • “Using Umbrella Arch Method in Design of Tunnel Lining” 🏞️⚒️
  • “Evaluation of Water Diversion Tunnel Lining Using Numerical Model” 🔢🌍
  • “Analysis and Investigation of Hydrological Drought Indicators in Mahenshan” 🌵💧
  • “A Novel Approach to Flood Risk Zonation: Integrating Deep Learning Models with APG” 💻🌊
  • “The Prediction of Precipitation Changes in the Aji-Chay Watershed Using CMIP6 Models” 🌧️📈
  • “Applying Project Knowledge Management to Enhance Time and Cost Efficiency in Water Reservoir Projects” 🕒💡
  • “Developing a System Dynamics Model to Study Human Resource Motivation and Time Productivity” 🕹️💼
  • “Investigating Strategies for Implementing Knowledge Management in Dam Construction Projects” 🏗️📚
  • “Simulation of Delay Factors in Dam Construction Projects with System Dynamics” ⏳🏞️
  • “Mathematical Equations for Grouting Pressure and Intensity in Joint Rocks” 🏔️🛠️
  • “Investigation of Excavation Behavior in Soil Nailing for Construction” 🏗️🌍
  • “Study of the Effects of Sludge Discharge from Water Treatment Plants” ♻️💧

Conclusion

Dr. Sina Fard Moradinia’s exceptional contributions to civil engineering, particularly in water resource management, hydrology, and construction project optimization, make him a strong candidate for the Best Researcher Award. His work, combining cutting-edge computational techniques and practical engineering solutions, addresses some of the most pressing challenges in sustainable development and infrastructure resilience. His innovative approaches in dam construction, flood prediction, and water quality management not only benefit academia but also have significant implications for real-world applications. With his continued focus on advancing research methodologies and expanding his influence both nationally and internationally, Dr. Fard Moradinia has the potential to be a leading figure in shaping the future of civil engineering and environmental management.

Pramod Patil – Deep Learning and Smart Grid – Best Researcher Award

Pramod Patil - Deep Learning and Smart Grid - Best Researcher Award

Dr.D.Y.Patil Institute of Technology - India

AUTHOR PROFILE

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ACADEMIC EXCELLENCE AND PROFESSIONAL JOURNEY 🎓

Pramod Patil's academic odyssey commenced with a Bachelor's degree in Computer Science and Engineering from S.G.G.S. College of Engineering and Technology, Nanded, followed by a Master's and Ph.D. in Computer Engineering from Govt. College of Engineering, Pune. Since November 2001, he has been an integral part of Dr.D.Y.Patil Institute of Technology, Pune, where he has held various academic positions, culminating in his current role as Professor.

EXEMPLARY ADMINISTRATIVE ROLES AND LEADERSHIP 🏢

Throughout his tenure, Patil has demonstrated exemplary leadership and administrative acumen. From serving as Dean and Principal to holding pivotal roles such as Vice Principal and Head of Department, his leadership has been instrumental in shaping the academic and administrative landscape of his institution.

COMMITMENT TO ACADEMIC ACCREDITATION AND ASSESSMENT 📚

Patil's commitment to academic quality and accreditation is evidenced through his involvement in various accreditation processes at both the institute and university levels. His expertise in accreditation, coupled with his roles as a member of inquiry committees and subject expert, underscores his dedication to upholding academic standards and fostering institutional growth.

PROFESSIONAL ENGAGEMENT AND MEMBERSHIPS 🔬

As a lifelong learner and academic stalwart, Patil is actively engaged in professional societies such as the Indian Society for Technical Education (ISTE), Computer Society of India (CSI), and Association of Computing Machinery (ACM). His membership and contributions to these esteemed organizations reflect his commitment to advancing the field of computer engineering.

RECOGNITION AND AWARDS 🏆

Patil's contributions to academia have garnered widespread recognition and acclaim. From receiving Best Paper Awards to being appointed as Dean of the Faculty of Science and Technology at Savitribai Phule Pune University, his accolades underscore his scholarly prowess and leadership excellence.

INSPIRING FUTURE GENERATIONS AND MENTORSHIP 🌱

As a mentor and guide, Patil has played a pivotal role in shaping the careers of numerous students and researchers. His dedication to nurturing talent and fostering academic excellence has left an indelible mark on the academic community, inspiring generations of scholars to pursue their academic and professional aspirations.

INNOVATIVE RESEARCH ENDEAVORS AND CONTRIBUTIONS 🚀

Patil's research endeavors have spanned diverse domains such as machine learning, data security, blockchain, and smart grid technology. His prolific publication record, patent contributions, and research projects highlight his commitment to advancing knowledge and addressing real-world challenges through innovative research methodologies.

NOTABLE PUBLICATION

Skewed Evolving Data Streams Classification with Actionable Knowledge Extraction using Data Approximation and Adaptive Classification Framework 2023 (7)

Context-aware clustering and the optimized whale optimization algorithm: An effective predictive model for the smart grid 2023 (9)

Blockchain-based security services for fog computing 2021 (16)

EFFECT OF EARLY FUNCTIONAL MOBILITY ON FUNCTIONAL INDEPENDENCE IN INCOMPLETE PARAPLEGIC INDIVIDUALS. 2022 (3)

Dalhatu Muhammed – Computer Science – Best Researcher Award

Dalhatu Muhammed - Computer Science - Best Researcher Award

Institut Supérieur D’electronique De Paris - France

AUTHOR PROFILE

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EARLY ACADEMIC PURSUITS

Dalhatu Muhammed embarked on his educational journey at Adamu Suleman Ninzamiyya Primary School Aliero from 1993 to 1999, where he obtained his Primary Certificate. He then attended Haliru Abdu Arabic Secondary School Jega (1999-2002), earning his Junior Leaving Certificate. Muhammed continued his secondary education at Government Technical College Bunza (2002-2005) and obtained his Secondary School Certificate (NABTEB) in 2005. Following this, he attended Usmanu Danfodiyo University, School of Matriculation in Sokoto in 2006 before enrolling in Usmanu Danfodiyo University Sokoto, Nigeria, where he earned a BSc in Computer Science (Second Class Upper Division) in 2011.

Muhammed's pursuit of higher education took him to the University of Malaya, Malaysia, where he specialized in Sensor Networks and completed an MSc in Computer Science in 2017. Currently, he is undertaking a PhD in Computer Science with a specialization in AIoT for Smart Agriculture at Sorbonne University Paris, France (2022 to date).

PROFESSIONAL ENDEAVORS

Muhammed's professional career is marked by significant contributions to the field of Computer Science, particularly in academia and technical instruction. His career began with the National Youth Service Corps (NYSC) in 2011-2012, followed by a teaching position at Raudatus Sunnah Academy Jega (2010-2011). He then joined Kebbi State University of Science and Technology Aliero (KSUSTA) as a System Analyst/Higher Technical Officer (2012-2014) and subsequently progressed through various academic positions: Graduate Assistant (2014-2017), Assistant Lecturer (2017-2019), Lecturer II (2019-2022), and currently, Lecturer I (2022-date). Additionally, he has served as a part-time lecturer at the School of Remedial Studies, KSUSTA (2017-2018) and as a CCNA Instructor at KSUSTA Networking Academy (2015-date).

CONTRIBUTIONS AND RESEARCH FOCUS

Throughout his career, Muhammed has been actively involved in numerous committees and responsibilities, including roles such as Departmental Examination Officer, Secretary of the Departmental Course Allocation Committee, and Chairman of the Departmental Committee on Accreditation Staff Grouping. His research focus is centered on the integration of Artificial Intelligence and Internet of Things (AIoT) in Smart Agriculture, which is also the theme of his ongoing PhD.

He has taught a wide array of courses, such as Fundamentals of Computer (CSC 101), Introduction to the Internet (INT 201), Web Technology and Scripting Language (INT 401), and Advanced Java Programming (CSC 408). His dedication to teaching is evident from his extensive involvement in student project supervision, guiding students in projects related to online systems for recruitment, hospital record management, and student attendance management.

IMPACT AND INFLUENCE

Muhammed's impact is also reflected in the numerous workshops and training programs he has attended, including international workshops on pervasive sensing and multimedia understanding, and professional development workshops on HMM-Based Speech Synthesis Systems. His contributions to academic conferences, such as the International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), further highlight his active engagement with the global research community.

ACADEMIC CITATIONS

Muhammed's scholarly work is widely recognized, with citations in various academic publications. His research and teaching in Computer Science have significantly contributed to the academic discourse in his field, particularly in sensor networks and AIoT applications.

LEGACY AND FUTURE CONTRIBUTIONS

Dalhatu Muhammed's legacy in Computer Science is marked by his commitment to education, research, and professional development. His future contributions are expected to further advance the fields of AIoT and smart agriculture, providing innovative solutions to contemporary challenges. His ongoing PhD research at Sorbonne University will likely yield significant advancements in these areas, solidifying his impact and influence in the global academic and professional community.

In summary, Dalhatu Muhammed's journey in Computer Science, marked by academic excellence, professional dedication, and impactful research, continues to inspire and influence the next generation of computer scientists. His ongoing efforts and future contributions promise to leave a lasting legacy in the field.

NOTABLE PUBLICATION

Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions 2024

Performance Evaluation of Machine Learning Algorithms for a Cluster-based Crop Recommendation System 2023

A User-friendly AIoT-Based Crop Recommendation system (UACR): concept and architecture 2022 (6)

A Cross-Lingual Text-To-Speech System for Hausa using DNN-Based Approach 2020

An Enhanced Scalable Design Approach for Managing Large Scale Variability in Software Product Lines (SPLs) 2020