Prof. Mohammed Almulla | Machine Learning | Best Researcher Award

Published on by Civil Engineering

Prof. Mohammed Almulla | Machine Learning | Best Researcher Award

VP Academic Affairs, Kuwait University, Kuwait

Professor Mohammed Ali Almulla is a distinguished Kuwaiti academic and researcher. With a career spanning over three decades, he has significantly contributed to the field of computer science, particularly in areas such as web services, emotion recognition, and fuzzy logic techniques. He is currently a Professor at Kuwait University and has held various leadership positions, including Chairman of the Department of Computer Science. His work has garnered recognition through several publications, research awards, and innovations in the realm of machine learning, artificial intelligence, and medical expert systems. Professor Almulla is known for his comprehensive research approach and deep engagement with emerging technologies, bridging academia and industry. His scholarly contributions are frequently cited, underlining his influence within the academic community.

Profile

Education

Professor Almulla completed his B.Sc. (1986), M.Sc. (1990), and Ph.D. (1995) in Computer Science from McGill University, Canada. His Ph.D. thesis, titled “Analysis of the Use of Semantic Trees in Automated Theorem Proving”, laid the foundation for his future research endeavors. With a deep understanding of theoretical and applied computer science, he has focused on machine learning, fuzzy systems, and semantic analysis. His education from McGill University, a globally recognized institution, has helped him build a solid academic foundation. Additionally, he possesses a comprehensive grasp of Arabic and English, enabling him to communicate and collaborate across cultures and academic circles.

Experience

Professor Almulla’s career at Kuwait University started in 1986 when he began as an Instructor. He progressed to Assistant Professor (1995–2006), then Associate Professor (2006–2021), and is currently serving as a Professor (2021–present). He has also been actively involved in departmental administration, having served as Chairman (2015–2020) and Graduate Program Director (2010–2013). Under his leadership, the Department of Computer Science achieved ABET accreditation, an outstanding accomplishment. His role as Acting Chairman in Mathematics and Computer Science in various periods further exemplifies his leadership skills. His dedication to advancing higher education and research has been integral to the development of the computer science field in Kuwait.

Awards and Honors

Professor Almulla’s academic excellence has been recognized through several Incentive Rewards for Unfunded Research in 2014, 2015, and 2017, with impactful papers published in journals such as Knowledge-Based Systems. His work on service trust behaviors, web services ranking, and fuzzy techniques has earned him significant recognition. He was also honored with Distinctive Teaching Awards in both the College of Computer Science and Engineering (2011/2012) and the Faculty of Science (2001/2002). These awards underscore his excellence in teaching, his commitment to innovative research, and his positive impact on student education.

Research Focus

Professor Almulla’s research focuses on a wide array of cutting-edge topics in computer science. Key areas of expertise include machine learning, fuzzy systems, service trust behaviors, and medical expert systems. His recent work explores emotion recognition systems, federated learning, and web services ranking. In addition, he has contributed to advancements in semantic similarity, automated theorem proving, and healthcare applications. With an eye toward the future, his research continues to bridge the gap between theoretical models and real-world applications, particularly in healthcare and artificial intelligence.

Publication top Notes

  • A Trust-based Global Expert System for Disease Diagnosis Using Hierarchical Federated Learning 🏥🤖
  • A Novel CLIPS-based Medical Expert System for Migraine Diagnosis and Treatment Recommendation 💡🧠
  • On the Effect of Prior Knowledge in Text-Based Emotion Recognition 🧠💬
  • A Multimodal Emotion Recognition System Using Deep Convolution Neural Networks 🖥️🔍
  • Location-based Expert System for Diabetes Diagnosis and Medication Recommendation 🏥💊
  • Measuring Semantic Similarity between Services Using Hypergraphs 🧠🌐
  • Specification and Recognition of Service Trust Behaviors 💻✅
  • Next-Generation Sequencing in Familial Breast Cancer Patients from Lebanon 🧬🎗️
  • A New Framework for the Verification of Service Trust Behaviors 🛡️💡
  • GeoCover: An Efficient Sparse Coverage Protocol for RSU Deployment over Urban VANETs 🚗🌍
  • A New Fuzzy Hybrid Technique for Ranking Real World Web Services 🌐🔍

 

 

 

Mahad Rashid | Machine Learning | Best Researcher Award

Published on by Civil Engineering

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 learning, deep 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 visualization, statistical 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.