Avraham Lalum | Machine Learning | Best Researcher Award

Published on by Computer Scientists Awards

Mr. Avraham Lalum | Machine Learning | Best Researcher Award

PhD | University of Córdoba | Israel

Avraham (Avi) Lalum is a distinguished legal scholar and researcher specializing in the intersection of real estate law, artificial intelligence, and conflict resolution. His research explores advanced AI-driven models for risk management in real estate transactions, integrating decision-oriented mediation (DOM), behavioral analytics, and deep learning to enhance investment decision frameworks. Lalum’s scholarly contributions bridge the gap between legal regulation and computational modeling, offering innovative methodologies for explainable AI in property law, negotiation, and human–machine interaction. His studies emphasize how artificial intelligence can simulate human reasoning to mitigate financial risk and promote fairness in high-stakes negotiations. His works are widely recognized in Scopus and Web of Science-indexed journals, contributing significantly to the fields of law, data science, and behavioral AI. With a growing academic impact reflected in over 300 citations and an h-index of 6 on Scopus (and 9 on Google Scholar), Lalum’s publications demonstrate both theoretical depth and practical application in LegalTech and AI ethics.

Profile

ORCID

Featured Publications 

Lalum, A., López del Río, L. C., & Villamandos, N. C. (2024). Synthetic reality mapping of real estate using deep learning-based object recognition algorithms. SN Business & Economics, Springer.
Lalum, A., Caridad López del Río, L., & Ceular Villamandos, N. (2025). Multi-dimensional AI-based modeling of real estate investment risk: A regulatory and explainable framework for investment decisions. Mathematics, MDPI.

 

Mr. Muhammad Tauqeer Iqbal | Machine Learning | Best Researcher Award

Published on by Computer Scientists Awards

Mr. Muhammad Tauqeer Iqbal | Machine Learning | Best Researcher Award

Mr. Muhammad Tauqeer Iqbal , Yangzhou University, China

Iqbal Muhammad Tauqeer is a passionate researcher and master’s student at Yangzhou University, China , specializing in the domain of Machine Learning 🤖. With a solid foundation in both industry and academia, he has combined practical management experience with cutting-edge AI research. His dedication to data science applications and computer vision has led to a notable publication recognized as a best paper, showcasing his potential in the rapidly evolving tech landscape 🌟.

Professional Profile

ORCID

🎓 Education Background

Iqbal is currently pursuing his Master’s degree at Yangzhou University, China 📚, where his academic focus is on machine learning and its applications in computer vision. His academic pursuits have been driven by a commitment to advancing AI-driven solutions in environmental monitoring and digital recognition systems.

💼 Professional Experience

Before his transition into research, Iqbal gained valuable industry experience as an Assistant Production Manager at OPPO Mobile Company Pakistan 📱 for over two years. This role provided him with deep insights into production workflows and industry standards, bridging the gap between theoretical learning and practical application.

🏆 Awards and Honors

Iqbal’s research has already earned accolades, with his paper titled “A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy” being recognized as a Best Paper 🥇. This early recognition is a testament to the impact and novelty of his contributions to AI-powered environmental diagnostics.

🔬 Research Focus

His research interests lie primarily in Machine Learning, Deep Learning, Transfer Learning, and Computer Vision 🧠📊. He is particularly focused on applying these techniques to UV–Vis Spectroscopy and digital display recognition. He is currently working on a second research project that extends his work in pattern recognition and visual AI.

🔚 Conclusion

With a unique blend of industrial management experience and academic rigor, Iqbal Muhammad Tauqeer is emerging as a promising contributor to the field of Artificial Intelligence. His work in machine learning models for environmental monitoring reflects not only his technical skills but also his commitment to impactful innovation 🌍🔍.

📚 Publication Top Note

  1. Title: A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy
    Journal: Journal of Imaging
    Publisher: MDPI
    Published Year: 2025